CN103473290B - The processing method and processing device of the attribute data of point of interest - Google Patents
The processing method and processing device of the attribute data of point of interest Download PDFInfo
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Abstract
The present invention provides a kind of processing method and processing device of POI attribute data.The embodiment of the present invention by obtain at least one data source provide POI candidate attribute data, and then according to the candidate attribute data, obtain the richness parameter and/or accuracy parameter of the candidate attribute data, make it possible to according to the richness parameter and/or the accuracy parameter, at least one attribute included at least one candidate attribute data is selected from the candidate attribute data, using the objective attribute target attribute data as the POI, can avoid in the prior art due to the POI detail informations in POI search result contains only be merely able to caused by the attribute field of several fixations to client the attribute information indicated by the attribute field of these fixations is provided the problem of, so as to improve the specific aim and validity of POI search.
Description
[ technical field ] A method for producing a semiconductor device
The present invention relates to Location Based Service (LBS) technologies, and in particular, to a method and an apparatus for processing attribute data of a Point of Interest (POI).
[ background of the invention ]
With the development of communication technology, more and more functions are integrated in the terminal, so that more and more corresponding applications are included in a system function list of the terminal. Some applications may involve Location Based Services (LBS), also called positioning services, such as a hundred degree parameter map. In the existing LBS, a client may obtain a plurality of Point of Interest (POI) search results by sending a search request to a server. In the POI search result, the POI detail information contains several fixed attribute fields, such as basic fields of name, phone, and address, and extension fields of tag, average price, comment,
however, since the POI detail information in the POI search result includes only a few fixed attribute fields, only the attribute information indicated by these fixed attribute fields can be provided to the client, resulting in a decrease in the pertinence and effectiveness of the POI search.
[ summary of the invention ]
Aspects of the present invention provide a method and an apparatus for processing attribute data of a POI, so as to improve the pertinence and the effectiveness of POI search.
In one aspect of the present invention, a method for processing attribute data of a POI is provided, including:
obtaining candidate attribute data of POI provided by at least one data source;
according to the candidate attribute data, obtaining a richness parameter and/or an accuracy parameter of the candidate attribute data;
and selecting at least one attribute contained in at least one candidate attribute data from the candidate attribute data according to the richness parameter and/or the accuracy parameter to serve as the target attribute data of the POI.
The above-mentioned aspect and any possible implementation manner further provide an implementation manner, where obtaining the richness parameter of the candidate attribute data according to the candidate attribute data includes:
performing word segmentation processing on the candidate attribute data to obtain word segmentation results;
and obtaining the richness parameter according to the number of the word segmentation results.
The above aspect and any possible implementation manner further provide an implementation manner, where obtaining an accuracy parameter of the candidate attribute data according to the candidate attribute data includes:
obtaining a diff value of each attribute contained in the candidate attribute data;
and obtaining the accuracy parameter according to the diff value of each attribute.
The above-mentioned aspect and any possible implementation manner further provide an implementation manner, where after selecting at least one attribute included in at least one candidate attribute data from the candidate attribute data according to the richness parameter and/or the accuracy parameter, the selecting at least one attribute included in at least one candidate attribute data as the target attribute data of the POI further includes:
receiving a query keyword sent by a client;
matching the POI corresponding to the query key words according to the query key words;
according to the POI, obtaining the target attribute data corresponding to the POI;
and sending the target attribute data to the client.
The above aspect and any possible implementation manner further provide an implementation manner, where after obtaining, according to the POI, the target attribute data corresponding to the POI, and before sending the target attribute data to the client, the method further includes:
acquiring industry information corresponding to the query keyword according to the query keyword;
acquiring a data organization template corresponding to the industry information according to the corresponding relation between the industry information and the data organization template;
and organizing the target attribute data by using the data organization template so as to send the organized target attribute data to the client.
The above-described aspect and any possible implementation manner further provide an implementation manner, where the candidate attribute data further includes category information, and the category information is used to identify a data category to which the candidate attribute data belongs.
The above-described aspect and any possible implementation manner further provide an implementation manner, before organizing the target attribute data by using the data organizing template, further including:
acquiring category information corresponding to industry information according to the corresponding relation between the industry information and the category information;
and obtaining the target attribute data corresponding to the category information according to the category information.
In another aspect of the present invention, an apparatus for processing attribute data of a POI includes:
an obtaining unit, configured to obtain candidate attribute data of a POI provided by at least one data source;
the obtaining unit is further configured to obtain an abundance parameter and/or an accuracy parameter of the candidate attribute data according to the candidate attribute data;
a selecting unit, configured to select at least one attribute included in at least one candidate attribute data from the candidate attribute data according to the richness parameter and/or the accuracy parameter, so as to serve as the target attribute data of the POI.
The above-mentioned aspects and any possible implementation further provide an implementation of the obtaining unit, and the obtaining unit is specifically configured to
Performing word segmentation processing on the candidate attribute data to obtain word segmentation results; and
and obtaining the richness parameter according to the number of the word segmentation results.
The above-mentioned aspects and any possible implementation further provide an implementation of the obtaining unit, and the obtaining unit is specifically configured to
Obtaining a diff value of each attribute contained in the candidate attribute data; and
and obtaining the accuracy parameter according to the diff value of each attribute.
The above-described aspects and any possible implementations further provide an implementation, where the apparatus further includes:
the receiving unit is used for receiving the query key words sent by the client;
the searching unit is used for matching the POI corresponding to the query key words according to the query key words;
the obtaining unit is further configured to obtain the target attribute data corresponding to the POI according to the POI;
the device further comprises:
and the sending unit is used for sending the target attribute data to the client.
The above-mentioned aspects and any possible implementation further provide an implementation of the obtaining unit, and the obtaining unit is specifically configured to
Acquiring industry information corresponding to the query keyword according to the query keyword;
acquiring a data organization template corresponding to the industry information according to the corresponding relation between the industry information and the data organization template; and
and organizing the target attribute data by using the data organization template so that the sending unit sends the organized target attribute data to the client.
The above-described aspect and any possible implementation manner further provide an implementation manner, where the candidate attribute data further includes category information, and the category information is used to identify a data category to which the candidate attribute data belongs.
The above-mentioned aspect and any possible implementation manner further provide an implementation manner, and the obtaining unit is further configured to
Acquiring category information corresponding to industry information according to the corresponding relation between the industry information and the category information; and
and obtaining the target attribute data corresponding to the category information according to the category information.
As can be seen from the foregoing technical solutions, in the embodiments of the present invention, by obtaining candidate attribute data of a POI provided by at least one data source, and further obtaining a richness parameter and/or an accuracy parameter of the candidate attribute data according to the candidate attribute data, at least one attribute included in at least one candidate attribute data can be selected from the candidate attribute data according to the richness parameter and/or the accuracy parameter to serve as target attribute data of the POI, so that a problem that attribute information indicated by fixed attribute fields can only be provided to a client due to that POI detail information in a POI search result only includes a few fixed attribute fields in the prior art can be avoided, and thus, the pertinence and the validity of POI search are improved.
[ description of the drawings ]
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed in the embodiments or the prior art descriptions will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without inventive labor.
Fig. 1 is a schematic flowchart of a method for processing attribute data of a POI according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a device for processing attribute data of a POI according to another embodiment of the present invention;
fig. 3 is a schematic structural diagram of a device for processing attribute data of a POI according to another embodiment of the present invention.
[ detailed description ] embodiments
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the terminal according to the embodiment of the present invention may include, but is not limited to, a mobile phone, a Personal Digital Assistant (PDA), a wireless handheld device, a wireless netbook, a Personal computer, a portable computer, an MP3 player, an MP4 player, and the like.
In addition, the term "and/or" herein is only one kind of association relationship describing an associated object, and means that there may be three kinds of relationships, for example, a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship.
Fig. 1 is a schematic flowchart of a method for processing attribute data of a POI according to an embodiment of the present invention, as shown in fig. 1.
101. Candidate attribute data for POIs provided by at least one data source is obtained.
Wherein each of the candidate attribute data may include, but is not limited to, attributes such as name, phone, address, official website, tag (tag), price per person, comment, etc.
102. And obtaining the richness parameter and/or the accuracy parameter of the candidate attribute data according to the candidate attribute data.
103. And selecting at least one attribute contained in at least one candidate attribute data from the candidate attribute data according to the richness parameter and/or the accuracy parameter to serve as the target attribute data of the POI.
It should be noted that the execution subject of 101 to 103 may be a search engine, and may be located in a local client to perform offline search, or may be located in a server on a network side to perform online search, which is not limited in this embodiment.
It is understood that the client may be an application installed on the terminal, or may also be a web page of a browser, as long as the LBS can be implemented to provide an objective existence form of POI search, which is not limited in this embodiment.
In this way, by obtaining candidate attribute data of a POI provided by at least one data source and further obtaining the richness parameter and/or the accuracy parameter of the candidate attribute data according to the candidate attribute data, so that at least one attribute contained in at least one candidate attribute data can be selected from the candidate attribute data according to the richness parameter and/or the accuracy parameter to be used as the target attribute data of the POI, the problem that in the prior art, due to the fact that the POI detail information in the POI search result only contains a few fixed attribute fields, the attribute information indicated by the fixed attribute fields can only be provided to the client can be avoided, and therefore the pertinence and the effectiveness of the POI search are improved.
In addition, by adopting the technical scheme provided by the embodiment, the user can perform subsequent operations in a targeted manner according to the target attribute data of the POI, so that the pertinence and the effectiveness of the POI attribute data acquisition can be further improved.
In addition, by adopting the technical scheme provided by the embodiment, the user can perform subsequent operations in a targeted manner according to the target attribute data of the POI, so that invalid selection (click) operations performed by the user through the client can be further reduced, and the processing load is reduced.
In the existing method for processing attribute data of a POI, the POI detail information only contains a few fixed attribute fields, so that the search engine can only provide the attribute information indicated by the fixed attribute fields to the client, thereby reducing the pertinence and effectiveness of the POI search.
Optionally, in a possible implementation manner of this embodiment, in 102, a method for obtaining, by a search engine, the richness parameter of the candidate attribute data according to the candidate attribute data may specifically be as follows: the search engine can specifically perform word segmentation processing (including filtering means such as stop word processing) on the candidate attribute data to obtain word segmentation results; then, the richness parameter can be obtained according to the number of the word segmentation results.
Optionally, in a possible implementation manner of this embodiment, in 102, a method for obtaining, by a search engine, an accuracy parameter of the candidate attribute data according to the candidate attribute data may specifically be as follows: the search engine may specifically obtain a change rate (diff) value of each attribute included in the candidate attribute data. The method for calculating the diff value corresponding to each attribute may be determined according to the attribute characteristics, which is not particularly limited in this embodiment. Then, the accuracy parameter may be obtained from the diff value of each attribute. The diff value of each attribute may be a diff value of each attribute relative to the current attribute corresponding to the attribute.
It will be appreciated that if the attribute is a newly added attribute, then the diff value of the attribute may be the diff value used to identify no changes, e.g., the diff value is 0.
It should be noted that the accuracy parameter may be understood as an accuracy parameter of each attribute, for example, if a diff value of an attribute is less than or equal to a preset threshold, the accuracy parameter of the attribute is 0; if the diff value of the attribute is greater than the preset threshold, the accuracy parameter of the attribute is 1. The smaller the diff value of an attribute, the higher the accuracy of the attribute can be said to be, and the greater the likelihood that this attribute is selected to be the target attribute data. Or may also be understood as the accuracy parameter of the candidate attribute data, for example, the accuracy parameter of the candidate attribute data is obtained according to the diff value of each attribute and the weight value of each attribute. The greater the accuracy parameter of the candidate attribute data, the higher the accuracy of the candidate attribute data can be said to be, and the greater the likelihood that this candidate attribute data is selected as the target attribute data. This embodiment is not particularly limited.
Specifically, in 103, the search engine may specifically select, according to the richness parameter and/or the accuracy parameter, all attributes included in one candidate attribute data, or a part of attributes included in one candidate attribute data, or all attributes included in a plurality of candidate attribute data, or a part of attributes included in a plurality of candidate attribute data from the candidate attribute data, to serve as the target attribute data of the POI.
For example, the search engine may select, from the candidate attribute data, all attributes included in one or more candidate attribute data with the greatest richness as the target attribute data of the POI according to the richness parameter.
Alternatively, for another example, the search engine may select, from the candidate attribute data, all attributes included in one or more candidate attribute data with the highest accuracy as the target attribute data of the POI, according to the accuracy parameter of the candidate attribute data.
For another example, the search engine may select, from the candidate attribute data, a partial attribute included in one or more candidate attribute data whose accuracy parameter satisfies a threshold condition according to the accuracy parameter of each attribute included in the candidate attribute data, so as to serve as the target attribute data of the POI, where the threshold condition is, for example, an attribute included in the candidate attribute data whose accuracy parameter is 0 or an attribute included in the candidate attribute data whose accuracy parameter is 1, and the like, which is not particularly limited in this embodiment.
It is understood that, in combination with the method in the foregoing examples, the search engine may further select at least one attribute included in at least one candidate attribute data from the candidate attribute data according to the richness parameter and the accuracy parameter of the candidate attribute data, or according to the richness parameter and the accuracy parameter of each attribute included in the candidate attribute data, so as to serve as the target attribute data of the POI, and the detailed description may refer to relevant contents in the foregoing examples, which is not described herein again.
Optionally, in a possible implementation manner of this embodiment, after 103, the search engine may further receive a query keyword sent by the client. Then, the search engine may further match the POI corresponding to the query keyword according to the query keyword. And then, the search engine acquires the target attribute data corresponding to the POI according to the POI and sends the target attribute data to the client as POI detail information in a POI search result. In this way, since the POI detail information in the POI search result may contain several unfixed attribute fields, the attribute information indicated by these unfixed several attribute fields can be provided to the client, thereby improving the pertinence and effectiveness of the POI search.
Specifically, after the search engine obtains the target attribute data corresponding to the POI, the search engine may further obtain industry information corresponding to the query keyword according to the query keyword, for example, industry information for identifying hotels, restaurants, movie theaters, and the like. Then, the search engine can further obtain a data organization template corresponding to the industry information according to the corresponding relationship between the industry information and the data organization template. Then, the search engine may organize the target attribute data by using the data organization template, so that the search engine performs a subsequent operation, that is, sends the organized target attribute data to the client.
Optionally, in a possible implementation manner of this embodiment, in 101, the candidate attribute data obtained by the search engine may further include category information, where the category information is used to identify a data category to which the candidate attribute data belongs, for example, a hotel, a restaurant, a movie theater, and the like.
Specifically, the search engine may further obtain the category information corresponding to the industry information according to a correspondence between the industry information and the category information. Then, the search engine may further obtain the target attribute data corresponding to the category information according to the category information.
By adopting the technical scheme provided by the invention, the attribute data of the POI can respectively belong to a plurality of data categories, and the attribute data of each data category can correspond to one data organization template, so that for the same POI, the attribute data of a plurality of data categories can be provided, and each attribute data can be applied to different data organization templates. In this way, the search engine can organize the corresponding attribute data by using different data organization templates, thereby improving the flexibility of POI search.
In order to make the method provided by the embodiment of the present invention clearer, the attribute data of this POI outside the river and city will be taken as an example.
Suppose that the search engine is currently capable of providing attribute data of the POI outside the river and city, and the attributes are as follows:
name: outside the river and city;
address: west door No. 3;
telephone: 010-666666;
the official website: http:// www.jiangbianchengwai.com;
average price per person (yuan): 33;
the category: a cat (restaurant).
The method comprises the following steps: and the search engine selects all or part of candidate attribute data provided by the partner A as a data source according to the obtained richness parameters of the candidate attribute data of the POI to serve as the target attribute data of the POI. The respective attributes contained in the candidate attribute data provided by the partner a are as follows:
name: outside the river and city;
address: xizhu men No. 4;
telephone: 010-666666, 010-55555555;
the official website: http:// www.jiangbianchengwai.com;
average price per person (yuan): 450, respectively;
the category: a cat (restaurant).
The second method comprises the following steps: the search engine preliminarily determines all or part of candidate attribute data which can be provided by the partner A as a data source to be used as target attribute data of the POI according to the obtained richness parameters of the candidate attribute data of the POI. The respective attributes contained in the candidate attribute data provided by the partner a are as follows:
name: outside the river and city;
address: xizhu men No. 4;
telephone: 010-666666, 010-55555555;
the official website: http:// www.jiangbianchengwai.com;
average price per person (yuan): 450, respectively;
the category: a cat (restaurant).
At this time, the search engine may calculate the diff value of each attribute using various calculation methods provided in the prior art, and the calculation results are as follows:
diff (name) ═ 0;
diff (address) ═ 1;
diff (telephone) ═ 0.5;
diff (official net) ═ 0;
diff (average person price) 12.6;
diff (class) ═ 0;
then, the search engine can obtain an accuracy parameter for each attribute according to the diff value of each attribute.
Specifically, if the diff value is less than or equal to the preset threshold, the accuracy parameter is 0; if the diff value is greater than the preset threshold, the accuracy parameter is 1. Wherein, the accuracy parameter of 0 represents that the accuracy is higher, and can be selected; an accuracy parameter of 1 indicates that the accuracy is low and cannot be selected. For example, the accuracy parameters for each attribute are as follows:
accuracy parameter (name) ═ 0;
accuracy parameter (address) ═ 1;
accuracy parameter (phone) ═ 0;
the accuracy parameter (official network) is 0;
the accuracy parameter (average price of people) is 1;
accuracy parameter (category) ═ 0;
in this way, the search engine may select 4 attributes with the accuracy parameter of 0, namely, the name, the telephone, the official website and the category, from the candidate attribute data according to the accuracy parameter of each attribute included in the candidate attribute data of the POI provided by the partner a, so as to serve as the target attribute data of the POI outside the city at the edge of the river.
The third method comprises the following steps: the search engine preliminarily determines all or part of candidate attribute data which can be provided by the partner A as a data source to be used as target attribute data of the POI according to the obtained richness parameters of the candidate attribute data of the POI. The respective attributes contained in the candidate attribute data provided by the partner a are as follows:
name: outside the river and city;
address: xizhu men No. 4;
telephone: 010-666666, 010-55555555;
the official website: http:// www.jiangbianchengwai.com;
average price per person (yuan): 450, respectively;
the category: a cat (restaurant).
At this time, the search engine may calculate the diff value of each attribute using various calculation methods provided in the prior art, and the calculation results are as follows:
diff (name) ═ 0;
diff (address) ═ 1;
diff (telephone) ═ 0.5;
diff (official net) ═ 0;
diff (average person price) 12.6;
diff (class) ═ 0;
the search engine may then obtain an accuracy parameter for the candidate attribute data based on the diff value for each attribute.
Specifically, the search engine may obtain the accuracy parameter of the candidate attribute data according to the diff value of each attribute and the weight of each attribute. For example,
accuracy parameter (candidate attribute data) ═ diff (name) × k1+ diff (address) × k2+ diff (telephone) × k3+ diff (official network) × k4+ diff (average price per person) × k5+ diff (category) × k6
The values of k 1-k 6 can be manually specified by an operator according to the importance degree of the attribute to the POI.
The greater the accuracy parameter of the candidate attribute data, the higher the accuracy of the candidate attribute data can be said to be, and the greater the likelihood that this candidate attribute data is selected as the target attribute data.
In this embodiment, by obtaining candidate attribute data of a POI provided by at least one data source, and further obtaining, according to the candidate attribute data, a richness parameter and/or an accuracy parameter of the candidate attribute data, so that at least one attribute included in at least one candidate attribute data can be selected from the candidate attribute data according to the richness parameter and/or the accuracy parameter to serve as target attribute data of the POI, a problem that attribute information indicated by fixed attribute fields can only be provided to a client due to that POI detail information in a POI search result only includes several fixed attribute fields in the prior art can be avoided, and thus, the pertinence and the effectiveness of POI search are improved.
In addition, by adopting the technical scheme provided by the embodiment, the user can perform subsequent operations in a targeted manner according to the target attribute data of the POI, so that the pertinence and the effectiveness of the POI attribute data acquisition can be further improved.
In addition, by adopting the technical scheme provided by the embodiment, the user can perform subsequent operations in a targeted manner according to the target attribute data of the POI, so that invalid selection (click) operations performed by the user through the client can be further reduced, and the processing load is reduced.
It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present invention is not limited by the order of acts, as some steps may occur in other orders or concurrently in accordance with the invention. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required by the invention.
In the foregoing embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
Fig. 2 is a schematic structural diagram of a device for processing attribute data of a POI according to another embodiment of the present invention, as shown in fig. 2. The processing device of the attribute data of the POI of the present embodiment may include the obtaining unit 21 and the selecting unit 22. The obtaining unit 21 is configured to obtain candidate attribute data of a POI provided by at least one data source; the obtaining unit 21 is further configured to obtain, according to the candidate attribute data, a richness parameter and/or an accuracy parameter of the candidate attribute data; a selecting unit 22, configured to select at least one attribute included in at least one candidate attribute data from the candidate attribute data according to the richness parameter and/or the accuracy parameter, so as to serve as the target attribute data of the POI.
Wherein each of the candidate attribute data may include, but is not limited to, attributes such as name, phone, address, official website, tag (tag), price per person, comment, etc.
It should be noted that the apparatus provided in this embodiment may be a search engine, and may be located in a local client to perform offline search, or may also be located in a server on a network side to perform online search, which is not limited in this embodiment.
It is understood that the client may be an application installed on the terminal, or may also be a web page of a browser, as long as the LBS can be implemented to provide an objective existence form of POI search, which is not limited in this embodiment.
In this way, the obtaining unit obtains the candidate attribute data of the POI provided by at least one data source, and further obtains the richness parameter and/or the accuracy parameter of the candidate attribute data according to the candidate attribute data, so that the selecting unit can select at least one attribute contained in at least one candidate attribute data from the candidate attribute data according to the richness parameter and/or the accuracy parameter as the target attribute data of the POI, and the problem that in the prior art, the attribute information indicated by fixed attribute fields can only be provided to the client due to the fact that the POI detail information in the POI search result only contains a few fixed attribute fields can be avoided, and the pertinence and the effectiveness of the POI search are improved.
In addition, by adopting the technical scheme provided by the embodiment, the user can perform subsequent operations in a targeted manner according to the target attribute data of the POI, so that the pertinence and the effectiveness of the POI attribute data acquisition can be further improved.
In addition, by adopting the technical scheme provided by the embodiment, the user can perform subsequent operations in a targeted manner according to the target attribute data of the POI, so that invalid selection (click) operations performed by the user through the client can be further reduced, and the processing load is reduced.
In the conventional processing device for attribute data of a POI, the POI detail information only contains a few fixed attribute fields, so that the search engine can only provide the attribute information indicated by the fixed attribute fields to the client, thereby reducing the pertinence and effectiveness of the POI search.
Optionally, in a possible implementation manner of this embodiment, the obtaining unit 21 may be specifically configured to perform word segmentation processing (including filtering means such as stop word processing) on the candidate attribute data to obtain a word segmentation result; and obtaining the richness parameter according to the number of the word segmentation results.
Optionally, in a possible implementation manner of this embodiment, the obtaining unit 21 may be specifically configured to obtain a diff value of each attribute included in the candidate attribute data, where a calculation method of the diff value corresponding to each attribute may be determined according to an attribute feature, and this embodiment is not particularly limited to this; and obtaining the accuracy parameter according to the diff value of each attribute, wherein the diff value of each attribute can be the diff value of each attribute relative to the current attribute corresponding to the attribute.
It will be appreciated that if the attribute is a newly added attribute, then the diff value of the attribute may be the diff value used to identify no changes, e.g., the diff value is 0.
It should be noted that the accuracy parameter may be understood as an accuracy parameter of each attribute, for example, if a diff value of an attribute is less than or equal to a preset threshold, the accuracy parameter of the attribute is 0; if the diff value of the attribute is greater than the preset threshold, the accuracy parameter of the attribute is 1. The smaller the diff value of an attribute, the higher the accuracy of the attribute can be said to be, and the greater the likelihood that this attribute is selected to be the target attribute data. Or may also be understood as the accuracy parameter of the candidate attribute data, for example, the accuracy parameter of the candidate attribute data is obtained according to the diff value of each attribute and the weight value of each attribute. The greater the accuracy parameter of the candidate attribute data, the higher the accuracy of the candidate attribute data can be said to be, and the greater the likelihood that this candidate attribute data is selected as the target attribute data. This embodiment is not particularly limited.
Specifically, the selecting unit 22 may specifically select, according to the richness parameter and/or the accuracy parameter, all attributes included in one candidate attribute data, or a part of attributes included in one candidate attribute data, or all attributes included in a plurality of candidate attribute data, or a part of attributes included in a plurality of candidate attribute data from the candidate attribute data to serve as the target attribute data of the POI.
For example, the selecting unit 22 may select, from the candidate attribute data, all the attributes included in the one or more candidate attribute data having the greatest richness as the target attribute data of the POI, according to the richness parameter.
Alternatively, for another example, the selection unit 22 may select, from the candidate attribute data, all the attributes included in one or more candidate attribute data with the highest accuracy as the target attribute data of the POI, according to the accuracy parameter of the candidate attribute data.
Alternatively, for another example, the selecting unit 22 may select, from the candidate attribute data, a part of attributes included in one or more candidate attribute data whose accuracy parameters satisfy a threshold condition according to the accuracy parameter of each attribute included in the candidate attribute data, so as to serve as the target attribute data of the POI, where the threshold condition is, for example, an attribute included in the candidate attribute data whose accuracy parameter is 0, an attribute included in the candidate attribute data whose accuracy parameter is 1, or the like, and this embodiment is not particularly limited thereto.
It is understood that, in combination with the method in the foregoing examples, the selecting unit 22 may further select at least one attribute included in at least one candidate attribute data from the candidate attribute data according to the richness parameter and the accuracy parameter of the candidate attribute data, or according to the richness parameter and the accuracy parameter of each attribute included in the candidate attribute data, so as to serve as the target attribute data of the POI, and the detailed description may refer to relevant contents in the foregoing examples, which is not described herein again.
Optionally, in a possible implementation manner of this embodiment, as shown in fig. 3, the processing apparatus for attribute data of a POI provided in this embodiment may further include a receiving unit 31, a searching unit 32, and a sending unit 33.
The receiving unit 31 is configured to receive a query keyword sent by a client; the searching unit 32 is configured to match the POI corresponding to the query keyword according to the query keyword.
Accordingly, the obtaining unit 21 may be further configured to obtain the target attribute data corresponding to the POI according to the POI.
The sending unit 33 is configured to send the target attribute data to the client.
In this way, since the POI detail information in the POI search result may contain several unfixed attribute fields, the attribute information indicated by these unfixed several attribute fields can be provided to the client, thereby improving the pertinence and effectiveness of the POI search.
Specifically, the obtaining unit 21 may be specifically configured to obtain, according to the query keyword, industry information corresponding to the query keyword, for example, industry information used for identifying hotels, restaurants, movie theaters, and the like; acquiring a data organization template corresponding to the industry information according to the corresponding relation between the industry information and the data organization template; and organizing the target attribute data by using the data organization template, so that the sending unit 33 performs a subsequent operation of sending the organized target attribute data to the client.
Optionally, in a possible implementation manner of this embodiment, the candidate attribute data obtained by the obtaining unit 21 may further include category information, where the category information is used to identify a data category to which the candidate attribute data belongs, for example, a hotel, a restaurant, a movie theater, and the like.
Specifically, the obtaining unit 21 may be further configured to obtain category information corresponding to industry information according to a correspondence between the industry information and the category information; and according to the category information, obtaining the target attribute data corresponding to the category information.
By adopting the technical scheme provided by the invention, the attribute data of the POI can respectively belong to a plurality of data categories, and the attribute data of each data category can correspond to one data organization template, so that for the same POI, the attribute data of a plurality of data categories can be provided, and each attribute data can be applied to different data organization templates. In this way, the search engine can organize the corresponding attribute data by using different data organization templates, thereby improving the flexibility of POI search.
In order to make the method provided by the embodiment of the present invention clearer, the attribute data of this POI outside the river and city will be taken as an example.
Suppose that the search engine is currently capable of providing attribute data of the POI outside the river and city, and the attributes are as follows:
name: outside the river and city;
address: west door No. 3;
telephone: 010-666666;
the official website: http:// www.jiangbianchengwai.com;
average price per person (yuan): 33;
the category: a cat (restaurant).
The method comprises the following steps: the selecting unit selects all or part of candidate attribute data provided by the partner A as a data source according to the obtained richness parameters of the candidate attribute data of the POI as the target attribute data of the POI. The respective attributes contained in the candidate attribute data provided by the partner a are as follows:
name: outside the river and city;
address: xizhu men No. 4;
telephone: 010-666666, 010-55555555;
the official website: http:// www.jiangbianchengwai.com;
average price per person (yuan): 450, respectively;
the category: a cat (restaurant).
The second method comprises the following steps: the selection unit preliminarily determines all or part of candidate attribute data which can be provided by the partner A as a data source to be used as target attribute data of the POI according to the obtained richness parameters of the candidate attribute data of the POI. The respective attributes contained in the candidate attribute data provided by the partner a are as follows:
name: outside the river and city;
address: xizhu men No. 4;
telephone: 010-666666, 010-55555555;
the official website: http:// www.jiangbianchengwai.com;
average price per person (yuan): 450, respectively;
the category: a cat (restaurant).
At this time, the obtaining unit may calculate the diff value of each attribute using various calculation methods provided in the related art, the calculation results being as follows:
diff (name) ═ 0;
diff (address) ═ 1;
diff (telephone) ═ 0.5;
diff (official net) ═ 0;
diff (average person price) 12.6;
diff (class) ═ 0;
then, the obtaining unit may obtain the accuracy parameter of each attribute from the diff value of each attribute.
Specifically, if the diff value is less than or equal to the preset threshold, the accuracy parameter is 0; if the diff value is greater than the preset threshold, the accuracy parameter is 1. Wherein, the accuracy parameter of 0 represents that the accuracy is higher, and can be selected; an accuracy parameter of 1 indicates that the accuracy is low and cannot be selected. For example, the accuracy parameters for each attribute are as follows:
accuracy parameter (name) ═ 0;
accuracy parameter (address) ═ 1;
accuracy parameter (phone) ═ 0;
the accuracy parameter (official network) is 0;
the accuracy parameter (average price of people) is 1;
accuracy parameter (category) ═ 0;
in this way, the selection unit may select 4 attributes with the accuracy parameter of 0, namely, the name, the telephone, the official website and the category, from the candidate attribute data according to the accuracy parameter of each attribute included in the candidate attribute data of the POI provided by the partner a, so as to serve as the target attribute data of the POI outside the city in the river.
The third method comprises the following steps: the selection unit preliminarily determines all or part of candidate attribute data which can be provided by the partner A as a data source to be used as target attribute data of the POI according to the obtained richness parameters of the candidate attribute data of the POI. The respective attributes contained in the candidate attribute data provided by the partner a are as follows:
name: outside the river and city;
address: xizhu men No. 4;
telephone: 010-666666, 010-55555555;
the official website: http:// www.jiangbianchengwai.com;
average price per person (yuan): 450, respectively;
the category: a cat (restaurant).
At this time, the obtaining unit may calculate the diff value of each attribute using various calculation methods provided in the related art, the calculation results being as follows:
diff (name) ═ 0;
diff (address) ═ 1;
diff (telephone) ═ 0.5;
diff (official net) ═ 0;
diff (average person price) 12.6;
diff (class) ═ 0;
then, the obtaining unit may obtain the accuracy parameter of the candidate attribute data based on the diff value of each attribute.
Specifically, the obtaining unit may obtain the accuracy parameter of the candidate attribute data according to the diff value of each attribute and the weight of each attribute. For example,
accuracy parameter (candidate attribute data) ═ diff (name) × k1+ diff (address) × k2+ diff (telephone) × k3+ diff (official network) × k4+ diff (average price per person) × k5+ diff (category) × k6
The values of k 1-k 6 can be manually specified by an operator according to the importance degree of the attribute to the POI.
The greater the accuracy parameter of the candidate attribute data, the higher the accuracy of the candidate attribute data can be said to be, and the greater the possibility that the selection unit selects this candidate attribute data as the target attribute data.
In this embodiment, the obtaining unit obtains candidate attribute data of the POI provided by at least one data source, and further obtains the richness parameter and/or the accuracy parameter of the candidate attribute data according to the candidate attribute data, so that the selecting unit can select at least one attribute included in at least one candidate attribute data from the candidate attribute data according to the richness parameter and/or the accuracy parameter as the target attribute data of the POI, and can avoid a problem that in the prior art, since the POI detail information in the POI search result only includes several fixed attribute fields, only the attribute information indicated by the fixed attribute fields can be provided to the client, thereby improving the pertinence and the effectiveness of the POI search.
In addition, by adopting the technical scheme provided by the embodiment, the user can perform subsequent operations in a targeted manner according to the target attribute data of the POI, so that the pertinence and the effectiveness of the POI attribute data acquisition can be further improved.
In addition, by adopting the technical scheme provided by the embodiment, the user can perform subsequent operations in a targeted manner according to the target attribute data of the POI, so that invalid selection (click) operations performed by the user through the client can be further reduced, and the processing load is reduced.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the embodiments provided in the present invention, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.
The integrated unit implemented in the form of a software functional unit may be stored in a computer readable storage medium. The software functional unit is stored in a storage medium and includes several instructions to enable a computer device (which may be a personal computer, a server, or a network device) or a processor (processor) to execute some steps of the methods according to the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A method for processing attribute data of a point of interest is characterized by comprising the following steps:
obtaining candidate attribute data of interest points provided by at least one data source;
according to the candidate attribute data, obtaining a richness parameter and/or an accuracy parameter of the candidate attribute data;
selecting at least one attribute contained in at least one candidate attribute data from the candidate attribute data according to the richness parameter and/or the accuracy parameter to serve as target attribute data of the interest point; wherein,
the obtaining of the richness parameter of the candidate attribute data according to the candidate attribute data includes:
performing word segmentation processing on the candidate attribute data to obtain word segmentation results;
obtaining the richness parameter according to the number of the word segmentation results;
the obtaining an accuracy parameter of the candidate attribute data according to the candidate attribute data includes:
obtaining a change rate value of each attribute contained in the candidate attribute data;
and obtaining the accuracy parameter according to the change rate value of each attribute.
2. The method according to claim 1, wherein said selecting at least one attribute contained in at least one candidate attribute data from the candidate attribute data as the target attribute data of the point of interest according to the richness parameter and/or the accuracy parameter further comprises:
receiving a query keyword sent by a client;
matching the interest points corresponding to the query keywords according to the query keywords;
obtaining the target attribute data corresponding to the interest points according to the interest points;
and sending the target attribute data to the client.
3. The method according to claim 2, wherein after obtaining the target attribute data corresponding to the interest point according to the interest point and before sending the target attribute data to the client, further comprising:
acquiring industry information corresponding to the query keyword according to the query keyword;
acquiring a data organization template corresponding to the industry information according to the corresponding relation between the industry information and the data organization template;
and organizing the target attribute data by using the data organization template so as to send the organized target attribute data to the client.
4. The method of claim 3, wherein the candidate attribute data further comprises category information, and the category information is used to identify a data category to which the candidate attribute data belongs.
5. The method of claim 4, wherein before organizing the target property data using the data organization template, further comprising:
acquiring category information corresponding to industry information according to the corresponding relation between the industry information and the category information;
and obtaining the target attribute data corresponding to the category information according to the category information.
6. An apparatus for processing attribute data of a point of interest, comprising:
the obtaining unit is used for obtaining candidate attribute data of the interest points provided by at least one data source;
the obtaining unit is further configured to obtain an abundance parameter and/or an accuracy parameter of the candidate attribute data according to the candidate attribute data;
a selecting unit, configured to select at least one attribute included in at least one candidate attribute data from the candidate attribute data according to the richness parameter and/or the accuracy parameter, so as to serve as target attribute data of the interest point; wherein,
the obtaining unit is particularly used for
Performing word segmentation processing on the candidate attribute data to obtain word segmentation results; and
obtaining the richness parameter according to the number of the word segmentation results;
the obtaining unit is particularly used for
Obtaining a change rate value of each attribute contained in the candidate attribute data; and
and obtaining the accuracy parameter according to the change rate value of each attribute.
7. The apparatus of claim 6, further comprising:
the receiving unit is used for receiving the query key words sent by the client;
the searching unit is used for matching the interest points corresponding to the query keywords according to the query keywords;
the obtaining unit is further configured to obtain the target attribute data corresponding to the interest point according to the interest point;
the device further comprises:
and the sending unit is used for sending the target attribute data to the client.
8. Device according to claim 7, characterized in that said obtaining unit is in particular adapted to
Acquiring industry information corresponding to the query keyword according to the query keyword;
acquiring a data organization template corresponding to the industry information according to the corresponding relation between the industry information and the data organization template; and
and organizing the target attribute data by using the data organization template so that the sending unit sends the organized target attribute data to the client.
9. The apparatus of claim 8, wherein the candidate attribute data further comprises category information, and the category information is used to identify a data category to which the candidate attribute data belongs.
10. The apparatus of claim 9, wherein the obtaining unit is further configured to obtain the data
Acquiring category information corresponding to industry information according to the corresponding relation between the industry information and the category information; and
and obtaining the target attribute data corresponding to the category information according to the category information.
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| CN105574019B (en) * | 2014-10-14 | 2020-07-31 | 阿里巴巴（中国）有限公司 | Query parameter processing method and device |
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| CN102142003A (en) * | 2010-07-30 | 2011-08-03 | 华为软件技术有限公司 | Method and device for providing point of interest information |
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| CN102142003A (en) * | 2010-07-30 | 2011-08-03 | 华为软件技术有限公司 | Method and device for providing point of interest information |
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