CN113672703A - User information updating method, device, equipment and storage medium - Google Patents
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Abstract
The invention discloses a method, a device, equipment and a storage medium for updating user information. The method comprises the following steps: obtaining internal user information of a user from an internal file, and obtaining external user information of the user from an external system; determining the total similarity of first characteristic information in the internal user information and second characteristic information in the external user information; and if the total similarity is larger than or equal to a first threshold value, updating the internal user information according to the external user information. According to the technical scheme, the internal user information in the internal file can be updated according to the external user information acquired from the external database based on the similarity, and the normalized management and the timely update of the user name and the address of the marketing file are realized.
Description
Technical Field
The embodiment of the invention relates to the technical field of information management, in particular to a method, a device, equipment and a storage medium for updating user information.
Background
The user profile is used as important information for knowing users and marketing management, and is the basis for providing multiple high-quality services and accurate services for the users by the national power grid. The user information such as the user name and the user address in the user file of the national power grid has the problems of non-standard user information and non-timely updating.
At present, the user file is updated mainly by checking and updating user file information through manual visit or telephone visit, so that the labor cost is high, and the working efficiency is low.
Disclosure of Invention
Embodiments of the present invention provide a method, an apparatus, a device, and a storage medium for updating user information, so as to update internal user information in an internal archive based on external user information obtained from an external database based on similarity, and implement standardized management and timely update of a name and an address of a marketing archive user.
In a first aspect, an embodiment of the present invention provides a method for updating user information, including:
obtaining internal user information of a user from an internal file, and obtaining external user information of the user from an external system;
determining the total similarity of first characteristic information in the internal user information and second characteristic information in the external user information;
and if the total similarity is larger than or equal to a first threshold value, updating the internal user information according to the external user information.
Further, the first feature information includes: the internal user name and the internal user address, and the second feature information includes: an external user name and an external user address,
correspondingly, the determining the total similarity between the first feature information in the internal user information and the second feature information in the external user information includes:
determining the product of the name similarity and the name similarity weight of the internal user name and the external user name as the name weighted similarity of the internal user name and the external user name;
determining the product of the address similarity and the address similarity weight of the internal user address and the external user address as the address weighted similarity of the internal user address and the external user address;
and determining the sum of the name weighted similarity and the address weighted similarity as the total similarity of the internal user information and the external user information.
Further, determining the name similarity between the internal user name and the external user name includes:
if the first user name is the internal user name and the second user name is the external user name, determining the relative similarity of the first user name relative to the second user name as a first relative similarity;
if the first user name is the external user name and the second user name is the internal user name, determining the relative similarity of the first user name relative to the second user name as a second relative similarity;
and determining the average value of the first relative similarity and the second relative similarity as the name similarity of the internal user name and the external user name.
Further, the step of determining the relative similarity of the first user name with respect to the second user name comprises:
performing word segmentation on the first user name to obtain a first user name keyword set;
determining a first reverse frequency sum of each first user name keyword in the first user name keyword set; the first reverse frequency sum is the sum of reverse text frequency indexes of the first user name keywords in an industry name keyword set corresponding to the industry to which the first user name belongs;
retrieving the first user name keyword set based on the second user name to obtain a first user name keyword corresponding to the second user name;
determining a second reverse frequency sum of each industry name keyword; the sum of the second reverse frequency and an inverse text frequency index of a first user name keyword retrieved for each second user name in an industry name keyword set corresponding to the industry to which the first user name belongs;
and determining the ratio of the second reverse frequency sum to the first reverse frequency sum as the relative similarity of the first user name relative to the second user name.
Further, the obtaining at least one internal name keyword by segmenting the internal user name includes:
determining a redundant word according to the type of the industry to which the internal user name belongs;
removing the redundant words from the internal user names to obtain core nouns of the internal user names;
and decomposing the core noun to obtain at least one internal name keyword.
Further, determining the address similarity between the internal user address and the external user address includes:
decomposing the internal user address and the external user address into a primary address, a secondary address and a tertiary address respectively; the first-level addresses are sequentially as follows: provincial, city and district level addresses; the secondary address includes: a multi-sublevel address;
if the primary address of the internal user address is different from the primary address of the external user address, determining that the address similarity of the internal user address and the external user address is zero;
if the primary address of the internal user address is the same as the primary address of the external user address, judging whether conflicting conflict sub-level addresses exist in the secondary addresses of the internal user address and the external user address;
if yes, determining the address similarity corresponding to the level number of the conflict sub-level address as the address similarity of the internal user address and the external user address;
if not, determining the address similarity corresponding to the tertiary addresses of the internal user address and the external user address as the address similarity of the internal user address and the external user address.
Further, determining a name similarity weight or an address similarity weight includes:
determining subjective similarity weight and objective similarity weight of the internal user information and the external user information;
determining distribution factors of the subjective similarity weight and the objective similarity weight;
determining the similarity weight of the internal user information and the external user information according to the subjective similarity weight, the objective similarity weight and the distribution factor, wherein the similarity weight comprises: the name similarity weight and the address similarity weight.
In a second aspect, an embodiment of the present invention further provides an apparatus for updating user information, where the apparatus includes:
the acquisition module is used for acquiring the internal user information of the user from the internal file and acquiring the external user information of the user from the external system;
the determining module is used for determining the total similarity of first characteristic information in the internal user information and second characteristic information in the external user information;
and the updating module is used for updating the internal user information according to the external user information if the similarity is greater than or equal to a first threshold.
In a third aspect, an embodiment of the present invention further provides a computer device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor implements the method for updating user information according to any one of the embodiments of the present invention when executing the program.
In a fourth aspect, the embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the method for updating user information according to any one of the embodiments of the present invention.
The embodiment of the invention obtains the internal user information of the user from the internal file and obtains the external user information of the user from the external system; determining a total similarity of the internal user information and the external user information; if the total similarity is larger than or equal to the first threshold, updating the internal user information according to the external user information, updating the internal user information in the internal archive according to the external user information acquired from the external database based on the similarity, solving the problems of high labor cost and low working efficiency of verifying and updating the user archive information through manual visit or telephone visit in the prior art, and realizing the standardized management and the timely updating of the marketing archive user name and address.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
Fig. 1 is a flowchart of a method for updating user information according to a first embodiment of the present invention;
fig. 2A is a flowchart of a method for updating user information according to a second embodiment of the present invention;
fig. 2B is a flowchart of another method for updating user information according to a second embodiment of the present invention;
fig. 3 is a schematic structural diagram of an apparatus for updating user information according to a third embodiment of the present invention;
fig. 4 is a schematic structural diagram of a computer device in the fourth embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures. Meanwhile, in the description of the present invention, the terms "first", "second", and the like are used only for distinguishing the description, and are not to be construed as indicating or implying relative importance.
Example one
Fig. 1 is a flowchart of a method for updating user information according to an embodiment of the present invention, where the present embodiment is applicable to a case where user information in an internal profile is updated according to user information obtained from an external system, and the method may be executed by a device for updating user information according to an embodiment of the present invention, where the device may be implemented in a software and/or hardware manner, as shown in fig. 1, and the method specifically includes the following steps:
s110, obtaining the internal user information of the user from the internal file, and obtaining the external user information of the user from the external system.
The user referred to in the embodiment of the present invention is generally an enterprise user. The internal profile may be a profile for storing user information, e.g. may be a database or a user system; the internal user information is user information stored in the internal profile and may include, for example, a name, address, or identification number of the user. The external system may be a related department for publicly releasing user information or an internet platform, and may be, for example, a business bureau, an administration department, a tax department, or a judicial department. The external user information is user information obtained from an open external system and may also include the user's name, address, license number, scope of business, legal representative, registered capital, business status, or loss of credit information.
Specifically, the internal user information of the user is obtained from the internal archive, and the internal user information may have the problems of untimely update or irregular filling. And acquiring external user information of the user from an external system, wherein the external user information is generally accurate and is updated in time.
S120, determining the total similarity of the first characteristic information in the internal user information and the first and second characteristic information in the external user information.
The feature information refers to information that can represent the identity of the user, and may be, for example, the name, address, or license number of the user.
Specifically, the sum of the similarity of the first characteristic information in the internal user information and the second characteristic information in the external user information is determined.
In a specific example, the name similarity between the internal user name and the external user name is determined, the address similarity between the internal user address and the external user address is determined, and the sum of the name similarity and the address similarity is determined as the total similarity.
In another specific example, the name weighted similarity is determined according to the name similarity and the first weight of the internal user name and the external user name, the address weighted similarity is determined according to the address similarity and the second weight of the internal user address and the external user address, and the total of the name weighted similarity and the address weighted similarity is determined as the total similarity.
And S130, if the total similarity is greater than or equal to a first threshold, updating the internal user information according to the external user information.
Wherein, the first threshold value can be set according to actual requirements
Specifically, if the total similarity is smaller than the first threshold, it cannot be determined that the internal user information and the external user information are information of the same user, and therefore the internal user information cannot be updated according to the external user information; and if the total similarity is greater than or equal to the first threshold, the internal user information and the external user information are information of the same user, and the internal user information is updated according to the external user information. The update behavior comprises: if the information exists in the internal user information of the internal file, the information is updated, and if the information does not exist in the internal user information, the information is added into the internal file.
For example, if the total similarity is greater than or equal to the first threshold, the internal user information existing in the internal archive system is updated according to the business license number queried in the external system, and the business range, legal representative, and registered capital of the user queried in the external system are supplemented to the internal user information of the internal archive.
According to the technical scheme of the embodiment, the internal user information of the user is acquired from the internal file, and the external user information of the user is acquired from the external system; determining a total similarity of the internal user information and the external user information; if the total similarity is within a preset range, updating the internal user information according to the external user information, updating the internal user information in the internal file according to the external user information acquired from the external database based on the similarity, and realizing the standardized management and the timely updating of the marketing file user name and address.
Example two
Fig. 2A is a flowchart of a method for updating user information according to a second embodiment of the present invention, where the present embodiment is optimized based on the foregoing embodiment, and in the present embodiment, the first feature information includes: the internal user name and the internal user address, and the second feature information includes: correspondingly, the determining the total similarity between the first feature information in the internal user information and the second feature information in the external user information includes: determining the product of the name similarity and the name similarity weight of the internal user name and the external user name as the name weighted similarity of the internal user name and the external user name; determining the product of the internal user address, the external user address similarity and the address similarity weight as the address weighted similarity of the internal user address and the external user address; and determining the sum of the name weighted similarity and the address weighted similarity as the total similarity of the internal user information and the external user information.
As shown in fig. 2A, the method of this embodiment specifically includes the following steps:
s210, obtaining the internal user information of the user from the internal file, and obtaining the external user information of the user from the external system.
S220, determining the product of the name similarity and the name similarity weight of the internal user name and the external user name as the name weighted similarity of the internal user name and the external user name.
Specifically, step S220 may include:
s221: determining name similarity Sim A, B of internal and external user namesname(ii) a Wherein, A represents the user acquired in the internal archive, and B represents the user acquired in the external system.
S222: determining a name similarity weight ω1；
S223: determining a name weighted similarity of
For example, the way of determining the name similarity between the internal user name and the external user name may be: performing word segmentation on the internal user name to obtain at least one internal name keyword; performing word segmentation on the external user name to obtain at least one external name keyword; the similarity of the internal user name keyword and the external user name keyword is calculated as the name similarity.
For example, the method for determining the name similarity weight may be determining the name similarity weight according to an analytic hierarchy process; or may be name similarity weighting determined according to an entropy weight method; name similarity weights may also be determined for weights determined from the analytic hierarchy process and weights determined by the entropy weight process.
S230, determining the product of the address similarity and the address similarity weight of the internal user address and the external user address as the address weighted similarity of the internal user address and the external user address.
Specifically, step S230 may include:
s231: determining the address similarity Sim A, B of an internal user address and an external user addressaddr；
S232: determining address similarity weights ω2；
S233: determining an address weighted similarity of
For example, the method for determining address similarity weights is the same as the method for determining name similarity weights, and details are not repeated in the embodiments of the present invention.
In a specific example, the manner of determining the address similarity between the internal user address and the external user address may be: the internal user address and the external user address are respectively decomposed into multi-level addresses, such as provincial addresses, city addresses, district addresses and addresses below the district level, the similarity of each level of the internal user address and the similarity of each level of the external user address are respectively determined, and the address similarity is determined according to the similarity of each level and the weight of the similarity of each level.
In another specific example, the manner of determining the address similarity between the internal user address and the external user address may be: segmenting each level of address, and determining the corresponding similarity of each segment of address, for example, a provincial address, a city address and a district address can be determined as a first segment, and if the first segment of address of an internal user address is different from that of an external user address, the address similarity is determined to be zero; if the internal user address is the same as the first section address of the external user address, determining the address similarity according to the similarity of the internal user address and the second end address of the external user address.
S240, determining the sum of the name weighted similarity and the address weighted similarity as the total similarity between the internal user information and the external user information.
Specifically, the name weighted similarity is
The address weighted similarity is
The total similarity Sim a, B of the internal user information and the external user informationcompComprises the following steps:
and S250, if the total similarity is within a preset range, updating the internal user information according to the external user information.
According to the technical scheme of the embodiment, the internal user information of the user is acquired from the internal file, and the external user information of the user is acquired from the external system; determining a total similarity of the internal user information and the external user information; if the total similarity is within a preset range, updating the internal user information according to the external user information, updating the internal user information in the internal file according to the external user information acquired from the external database based on the similarity, and realizing the standardized management and the timely updating of the marketing file user name and address.
Optionally, in step S221: determining name similarity of the internal user name and the external user name, including:
s2211: if the first user name is the internal user name and the second user name is the external user name, determining the relative similarity of the first user name relative to the second user name as a first relative similarity;
s2212: if the first user name is the external user name and the second user name is the internal user name, determining the relative similarity of the first user name relative to the second user name as a second relative similarity;
s2213: and determining the average value of the first relative similarity and the second relative similarity as the name similarity of the internal user name and the external user name.
Illustratively, a first relative similarity Sim of the internal username with respect to the external username is determinednameA | B; determining a second relative similarity Sim of the external username with respect to the internal usernamenameB | A; the name similarity of the internal user name and the external user name is Simname A,B＝Simname A|B+Simname B|A/2。
Optionally, step S2211 and step S2212: the step of determining the relative similarity of the first user name with respect to the second user name is:
performing word segmentation on the first user name to obtain a first user name keyword set;
determining a first reverse frequency sum of each first user name keyword in the first user name keyword set; the first reverse frequency sum is the sum of reverse text frequency indexes of the first user name keywords in an industry name keyword set corresponding to the industry to which the first user name belongs;
retrieving the first user name keyword set based on the second user name to obtain a first user name keyword corresponding to the second user name;
determining a second reverse frequency sum of each industry name keyword; the sum of the second reverse frequency and an inverse text frequency index of a first user name keyword retrieved from the second user name in an industry name keyword set corresponding to the industry to which the first user name belongs;
and determining the second reverse frequency sum and the first reverse frequency sum as the relative similarity of the first user name relative to the second user name.
Specifically, the first step: and performing word segmentation on the first user name X _ name to obtain at least one first user name keyword m, wherein a set formed by the first user name keywords m is set (X _ name), namely m belongs to set (X _ name).
The second step is that: determining an inverse text frequency index IDF m, d for each first user name keywordXWherein d isXThe method comprises the steps of summing the inverse text frequency indexes of all first user name keywords to obtain a first inverse frequency sum, wherein the first inverse text frequency indexes are the name keywords of users in the industry to which the first user name X _ name belongs, namely the industry name keywords, m is the first user name keywordsX_name,IDF＝∑IDF m,dX(ii) a Wherein the inverse text frequency index IDF m, d of the first user name keywordXThe calculation method of (2) may be:
wherein set dXSet formed by the industry name key words, i.e. industry name key word set, count m: dXFor the first user name X _ name belonging to the industry dXThe user name comprises the number of users of the first user name keyword m, and N is the total number of users in the industry to which the first user name X _ name belongs.
The third step: based on the multi-pattern matching Aho-Corasick algorithm, a first user name keyword set setX _ name is searched in a second user name Y _ name, and a first user name keyword n corresponding to the second user name is obtained through searching and is AC Y _ name and set X _ name, wherein AC represents the Aho-Corasick algorithm.
Fourthly, summing the inverse text frequency indexes corresponding to the first user name keywords retrieved from the second user name in the third step to obtain a second inverse frequency sum:
sumY_name,IDF＝∑IDF n,dX＝∑IDF AC Y_name,setX_name,dX。
the traditional IDF value calculation method only considers the relation between the name key words and the user names, and in the embodiment of the invention, the calculation method of the inverse text frequency index comprehensively considers the characteristics and differences of the user names in different industries, so that the matching degree of the user names is more accurate.
The fifth step, sum the second inverse frequency and sumY_name,IDFSum of the first inverse frequency and sumX_name,IDFIs determined as the relative similarity Sim of the first user name with respect to the second user namenameX | Y, namely:
illustratively, for step S2211, the first username X _ name is an internal username a _ name, the second username Y _ name is an external username B _ name, and the relative similarity of the first username to the second username is determined as a first relative similarity SimnameA | B, namely:
wherein d isAFor internal user name key m1In the industry to which the internal user name belongs; set A _ name is the set of internal user name keywords.
Illustratively, for step S2212, the first username X _ name is an external username B _ name, the second username Y _ name is an internal username a _ name, and the relative similarity of the first username to the second username is determined as a first relative similarity SimnameB | A, namely:
wherein d isBKeywords m for external user names2In the industry to which the internal user name belongs; set B _ name is the set of external user name keywords. Here IDF is the inverse text frequency index composed of external user names.
Optionally, performing word segmentation on the internal user name to obtain at least one internal name keyword, including:
determining a redundant word according to the type of the industry to which the internal user name belongs;
removing the redundant words from the internal user names to obtain core nouns of the internal user names;
and decomposing the core noun to obtain at least one internal name keyword.
Illustratively, the user names of different industries have their own industry attributes, and the redundant words are determined according to the industry types. For example, redundant words such as "manufacturing", "industry", "practice", etc. often appear in the names of users in the manufacturing industry; the names of users in the public management, social organization and international organization industries are mostly distinguished by names of administrative areas, and vocabularies of the administrative areas can be used as redundant words; except for the public service and management organization, other industry users can determine the province, the city and the like as redundant words; for the enterprise user name, fields such as "limited company", "limited responsibility company" and the like can be determined as redundant words.
Specifically, after removing the redundant words in the internal user name, the core nouns of the internal user name are obtained; at least one internal name keyword can be obtained by decomposing the core noun by adopting a decomposition tool.
Optionally, step S231: determining the address similarity Sim A, B of an internal user address and an external user addressaddrThe method comprises the following steps:
decomposing the internal user address and the external user address into a primary address, a secondary address and a tertiary address respectively; the first-level addresses are sequentially as follows: provincial, city and district level addresses; the secondary address includes: a multi-sublevel address;
if the primary address of the internal user address is different from the primary address of the external user address, determining that the address similarity of the internal user address and the external user address is zero;
if the primary address of the internal user address is the same as the primary address of the external user address, judging whether conflicting conflict sub-level addresses exist in the secondary addresses of the internal user address and the external user address;
if yes, determining the address similarity corresponding to the level number of the conflict sub-level address as the address similarity of the internal user address and the external user address;
if not, determining the address similarity corresponding to the tertiary addresses of the internal user address and the external user address as the address similarity of the internal user address and the external user address.
Specifically, the first step: performing address decomposition on the internal user address and the external user address to obtain a first-level address, a second-level address and a third-level address; the first-level addresses are sequentially as follows: provincial, city and district level addresses; the secondary address includes: a multi-sublevel address; for example, the sub-level address may be: streets and parks; the tertiary address may be a building number or floor.
The second step is that: and judging the address grade of the conflict between the internal user address and the external user address. If the primary address of the internal user address is different from the primary address of the external user address, namely: if the provincial address, the city address or the district address are different, the address similarity between the internal user address and the external user address is determined to be zero; if the primary address of the internal user address is the same as the primary address of the external user address, continuously judging whether the internal user address and the external user address have conflicting conflict secondary addresses in the secondary addresses;
the third step: if yes, determining the address similarity corresponding to the level number of the conflict sub-level address, and determining the address similarity of the internal user address and the external user address;
for example, the manner of determining the address similarity corresponding to the number of levels of the conflict sub-level address may be:
wherein, k is 1, 2,3 respectively represents the stage number corresponding to the provincial address, the city address or the district address, l > k > 3 sequentially represents the stage number corresponding to each sub-level address in the second level address, and l is the stage number corresponding to the third level address. The weight of each sub-level address decreases with increasing level according to the index of 1/2, indicating that higher addresses have a greater effect on similarity.
The fourth step: if not, determining the address similarity corresponding to the tertiary addresses of the internal user address and the external user address as the address similarity of the internal user address and the external user address.
Specifically, when the address is decomposed, the internal user address and the external user address may not be decomposed into the minimum unit, for example, only into the street, and the address below the street may not be decomposed. If the conflict sub-level addresses which conflict with each other do not exist in all levels of the first-level address and the second-level address, calculating the address similarity corresponding to the three levels of the internal user address and the external user address, and determining the address similarity corresponding to the three levels of addresses as the address similarity of the internal user address and the external user address.
For example, if the internal user address is "level 4" of building a of guancun, zhongguancun, beijing, hai lake district, and the external user address is "level 5" of building a, zhongguancun, beijing, the decomposition into the first level address includes: "beijing" (k ═ 2), "hai lake" (k ═ 3), and the secondary address includes "zhongguancun" (k ═ 4). If the three-level address (l ═ 5) a _ addr _ Res of the internal user address is "level 4 in building a", and the three-level address B _ addr _ Res of the external user address is "level 6 in building a", the address similarity between the internal user address and the external user address is:
where Sim (a _ addr _ Res, B _ addr _ Res) is the similarity between the unresolved address a _ addr _ Res of the internal user address at level 4 a building and the unresolved address B _ addr _ Res of the external user address at level 6 a building.
Optionally, in step S222: determining a name similarity weight ω1And step S232: determining address similarity weights ω2The method comprises the following steps:
determining subjective similarity weight and objective similarity weight of the internal user information and the external user information;
determining distribution factors of the subjective similarity weight and the objective similarity weight;
and calculating the similarity weight of the internal user information and the external user information according to the subjective similarity weight, the objective similarity weight and the distribution factor.
Wherein the similarity weight comprises a name similarity weight and the address similarity weight.
Specifically, the calculation formula of the similar weight is as follows:
wherein, ω isiFor the internal user information, i ═ 1 denotes the internal user name, i ═ 2 denotes the internal user address, and x denotes the internal user addressiIs the subjective similarity weight, uiAnd m is the distribution factor of the objective similarity weight.
Illustratively, subjective similar weights of internal user information and external user information are determined through an analytic hierarchy process, which means that elements always related to weight decision are decomposed into levels such as targets, criteria and schemes, and a qualitative and quantitative analysis is performed on the basis to determine the weights. The objective similar weight of the internal user information and the external user information is determined by an entropy weight method, the entropy weight method refers to the fact that the information entropy is used for judging the dispersion degree of a certain index, the smaller the information entropy value is, the larger the dispersion degree of the index is, the larger the influence of the index on comprehensive evaluation is, namely, the larger the weight is, and the specific process of the entropy weight method is not described in detail by the embodiment of the invention.
As shown in fig. 2B, the specific steps of the embodiment of the present invention are: obtaining user name keywords only by removing redundant words and decomposing core nouns for the internal user name, calculating the inverse text frequency Index (IDF) of each user name keyword, calculating a first relative similarity of the internal user name relative to the external user name and a second relative similarity of the external user name relative to the internal user name based on the IDF value of each user name keyword, and obtaining name similarity according to the first relative similarity and the second relative similarity; performing multi-level address decomposition on the internal user address and the external user address, and if the decomposed addresses conflict, determining the similarity of conflict sub-level addresses with mutual conflict between the internal user address and the external user address; if the decomposed addresses have no conflict, calculating the similarity corresponding to the undissolved addresses of the internal user address and the external user address as the address similarity; and carrying out weighted summation on the name similarity and the address similarity to obtain the total similarity, and updating the internal user information according to the external user information if the total similarity is within a preset range.
EXAMPLE III
Fig. 3 is a schematic structural diagram of an apparatus for updating user information according to a third embodiment of the present invention. The present embodiment is applicable to a case of updating user information in an internal profile according to user information obtained from an external system, the apparatus may be implemented in a software and/or hardware manner, and the apparatus may be integrated into any device providing a user information updating function, as shown in fig. 3, where the apparatus for updating user information specifically includes: an acquisition module 310, a determination module 320, and an update module 330.
The acquiring module 310 is configured to acquire internal user information of a user from an internal profile and acquire external user information of the user from an external system;
a determining module 320, configured to determine a total similarity between first feature information in the internal user information and second feature information in the external user information;
an updating module 330, configured to update the internal user information according to the external user information if the similarity is greater than or equal to a first threshold.
Optionally, the determining module 320 includes:
a first determining unit configured to determine a product of name similarity and name similarity weight of the internal user name and the external user name as name weighted similarity of the internal user name and the external user name;
a second determining unit, configured to determine a product of address similarity and address similarity weight of the internal user address and the external user address as an address weighted similarity of the internal user address and the external user address;
a third determining unit, configured to determine a sum of the name weighted similarity and the address weighted similarity as a total similarity between the internal user information and the external user information.
Optionally, the first determining unit includes:
a first determining subunit, configured to determine, if the first user name is the internal user name and the second user name is the external user name, that a relative similarity of the first user name with respect to the second user name is a first relative similarity;
a second determining subunit, configured to determine, if the first user name is the external user name and the second user name is the internal user name, that the relative similarity of the first user name with respect to the second user name is a second relative similarity;
a third determining subunit, configured to determine an average of the first relative similarity and the second relative similarity as a name similarity between the internal user name and the external user name.
Optionally, the first determining subunit or the determining subunit is specifically configured to:
performing word segmentation on the first user name to obtain a first user name keyword set;
determining a first reverse frequency sum of each first user name keyword in the first user name keyword set; the first reverse frequency sum is the sum of reverse text frequency indexes of the first user name keywords in an industry name keyword set corresponding to the industry to which the first user name belongs;
retrieving the first user name keyword set based on the second user name to obtain a first user name keyword corresponding to the second user name;
determining a second reverse frequency sum of each industry name keyword; the sum of the second reverse frequency and an inverse text frequency index of a first user name keyword retrieved for each second user name in an industry name keyword set corresponding to the industry to which the first user name belongs;
and determining the ratio of the second reverse frequency sum to the first reverse frequency sum as the relative similarity of the first user name relative to the second user name.
Optionally, the first determining subunit or the determining subunit is further configured to:
determining a redundant word according to the type of the industry to which the internal user name belongs;
removing the redundant words from the internal user names to obtain core nouns of the internal user names;
and decomposing the core noun to obtain at least one internal name keyword.
Optionally, the second determining unit is specifically configured to:
decomposing the internal user address and the external user address into a primary address, a secondary address and a tertiary address respectively; the first-level addresses are sequentially as follows: provincial, city and district level addresses; the secondary address includes: a multi-sublevel address;
if the primary address of the internal user address is different from the primary address of the external user address, determining that the address similarity of the internal user address and the external user address is zero;
if the primary address of the internal user address is the same as the primary address of the external user address, judging whether conflicting conflict sub-level addresses exist in the secondary addresses of the internal user address and the external user address;
if yes, determining the address similarity corresponding to the level number of the conflict sub-level address as the address similarity of the internal user address and the external user address;
if not, determining the address similarity corresponding to the tertiary addresses of the internal user address and the external user address as the address similarity of the internal user address and the external user address.
Optionally, the first determining unit or the second determining unit is further configured to:
determining subjective similarity weight and objective similarity weight of the internal user information and the external user information;
determining distribution factors of the subjective similarity weight and the objective similarity weight;
and determining the similarity weight of the internal user information and the external user information according to the subjective similarity weight, the objective similarity weight and the distribution factor, wherein the similarity weight comprises a name similarity weight and an address similarity weight.
The product can execute the method provided by any embodiment of the invention, and has corresponding functional modules and beneficial effects of the execution method.
Example four
Fig. 4 is a schematic structural diagram of a computer device in the fourth embodiment of the present invention. FIG. 4 illustrates a block diagram of an exemplary computer device 12 suitable for use in implementing embodiments of the present invention. The computer device 12 shown in FIG. 4 is only one example and should not bring any limitations to the functionality or scope of use of embodiments of the present invention.
As shown in FIG. 4, computer device 12 is in the form of a general purpose computing device. The components of computer device 12 may include, but are not limited to: one or more processors or processors 16, a system memory 28, and a bus 18 that connects the various system components (including the system memory 28 and the processors 16).
The system memory 28 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM)30 and/or cache memory 32. Computer device 12 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 34 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 4, and commonly referred to as a "hard drive"). Although not shown in FIG. 4, a magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 18 by one or more data media interfaces. Memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the invention.
A program/utility 40 having a set (at least one) of program modules 42 may be stored, for example, in memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which examples or some combination thereof may comprise an implementation of a network environment. Program modules 42 generally carry out the functions and/or methodologies of the described embodiments of the invention.
The processor 16 executes various functional applications and data processing by executing programs stored in the system memory 28, for example, implementing the user information updating method provided by the embodiment of the present invention: obtaining internal user information of a user from an internal file, and obtaining external user information of the user from an external system; determining the total similarity of first characteristic information in the internal user information and second characteristic information in the external user information; and if the total similarity is larger than or equal to a first threshold value, updating the internal user information according to the external user information.
EXAMPLE five
An embodiment five of the present invention provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the method for updating user information provided in all the inventive embodiments of the present application: obtaining internal user information of a user from an internal file, and obtaining external user information of the user from an external system; determining the total similarity of first characteristic information in the internal user information and second characteristic information in the external user information; and if the total similarity is larger than or equal to a first threshold value, updating the internal user information according to the external user information.
Any combination of one or more computer-readable media may be employed. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (10)
1. A method for updating user information, comprising:
obtaining internal user information of a user from an internal file, and obtaining external user information of the user from an external system;
determining the total similarity of first characteristic information in the internal user information and second characteristic information in the external user information;
and if the total similarity is larger than or equal to a first threshold value, updating the internal user information according to the external user information.
2. The method of claim 1, wherein the first feature information comprises: the internal user name and the internal user address, and the second feature information includes: an external user name and an external user address,
correspondingly, the determining the total similarity between the first feature information in the internal user information and the second feature information in the external user information includes:
determining the product of the name similarity and the name similarity weight of the internal user name and the external user name as the name weighted similarity of the internal user name and the external user name;
determining the product of the address similarity and the address similarity weight of the internal user address and the external user address as the address weighted similarity of the internal user address and the external user address;
and determining the sum of the name weighted similarity and the address weighted similarity as the total similarity of the internal user information and the external user information.
3. The method of claim 2, wherein determining the name similarity of the internal username and the external username comprises:
if the first user name is the internal user name and the second user name is the external user name, determining the relative similarity of the first user name relative to the second user name as a first relative similarity;
if the first user name is the external user name and the second user name is the internal user name, determining the relative similarity of the first user name relative to the second user name as a second relative similarity;
and determining the average value of the first relative similarity and the second relative similarity as the name similarity of the internal user name and the external user name.
4. The method of claim 3, wherein the step of determining the relative similarity of the first username to the second username is:
performing word segmentation on the first user name to obtain a first user name keyword set;
determining a first reverse frequency sum of each first user name keyword in the first user name keyword set; the first reverse frequency sum is the sum of reverse text frequency indexes of the first user name keywords in an industry name keyword set corresponding to the industry to which the first user name belongs;
retrieving the first user name keyword set based on the second user name to obtain a first user name keyword corresponding to the second user name;
determining a second reverse frequency sum of each industry name keyword; the sum of the second reverse frequency and an inverse text frequency index of a first user name keyword retrieved for each second user name in an industry name keyword set corresponding to the industry to which the first user name belongs;
and determining the ratio of the second reverse frequency sum to the first reverse frequency sum as the relative similarity of the first user name relative to the second user name.
5. The method of claim 4, wherein the tokenizing the internal usernames to obtain at least one internal name keyword comprises:
determining a redundant word according to the type of the industry to which the internal user name belongs;
removing the redundant words from the internal user names to obtain core nouns of the internal user names;
and decomposing the core noun to obtain at least one internal name keyword.
6. The method of claim 2, wherein determining the address similarity of the internal user address and the external user address comprises:
decomposing the internal user address and the external user address into a primary address, a secondary address and a tertiary address respectively; the first-level addresses are sequentially as follows: provincial, city and district level addresses; the secondary address includes: a multi-sublevel address;
if the primary address of the internal user address is different from the primary address of the external user address, determining that the address similarity of the internal user address and the external user address is zero;
if the primary address of the internal user address is the same as the primary address of the external user address, judging whether conflicting conflict sub-level addresses exist in the secondary addresses of the internal user address and the external user address;
if yes, determining the address similarity corresponding to the level number of the conflict sub-level address as the address similarity of the internal user address and the external user address;
if not, determining the address similarity corresponding to the tertiary addresses of the internal user address and the external user address as the address similarity of the internal user address and the external user address.
7. The method of claim 2, wherein determining a name similarity weight or an address similarity weight comprises:
determining subjective similarity weight and objective similarity weight of the internal user information and the external user information;
determining distribution factors of the subjective similarity weight and the objective similarity weight;
and determining the similarity weight of the internal user information and the external user information according to the subjective similarity weight, the objective similarity weight and the distribution factor, wherein the similarity weight comprises a name similarity weight and an address similarity weight.
8. An apparatus for updating user information, comprising:
the acquisition module is used for acquiring the internal user information of the user from the internal file and acquiring the external user information of the user from the external system;
the determining module is used for determining the total similarity of first characteristic information in the internal user information and second characteristic information in the external user information;
and the updating module is used for updating the internal user information according to the external user information if the similarity is greater than or equal to a first threshold.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the method of updating user information according to any one of claims 1 to 7 when executing the program.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out a method of updating user information according to any one of claims 1 to 7.
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