CN110119464B - Intelligent recommendation method and device for numerical values in contract - Google Patents
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Abstract
The invention provides an intelligent recommendation method and device for numerical values in contracts, which are used for acquiring a target contract and a related contract template; clustering the contract template, judging the category of the target contract in the contract template, and acquiring the contract category and the contract template content of the category; performing natural language processing analysis on the target contract to obtain a clause with a numerical type in the clause; acquiring all similar clauses of the clauses with the numerical value type in a contract template of the same category; analyzing the distribution of values in the similar clauses; judging the corresponding distribution of the numerical value of the target contract in the contract template; if the corresponding distribution ratio is smaller than a certain threshold value, giving a warning prompt; or judging whether the value of the target contract is contained in the recommended value corresponding to the contract law, and giving a warning prompt if the value is not in the recommended value interval; and gives a recommended value. The invention can help people to obtain the reference value of the numerical value in the contract, and avoid the benefit damage or cheating when signing the contract.
Description
Technical Field
The invention relates to the technical field of computer application, in particular to an intelligent recommendation method and device for numerical values in contracts.
Background
There are many types of contracts, such as purchase contracts, rental contracts, advertisement space rental contracts, patent transfer contracts, technical service contracts, app entrusted development contracts, promotion service contracts, and so on, and these various contracts basically involve a large number of values therein, such as time, quantity, term, cost price, and so on. When a contract is made, it is often unclear whether the value is within a normal range in the contract to which the contract is being made. It takes a lot of time and effort if the individual references the look-up or query.
Because the content of the contract is various, it is difficult to accurately judge what the contract is reasonable and unreasonable, and the risk assessment by personal experience has great instability and unreliability. The evaluation of the value in the contract is attached to one entity. For example, the house deposit is three-for-one, two-for-one, etc., and the profit margin permitted by the patent technology is generally 2% to 6%, which can be compared with the entity and the value accurately. When more numerical values corresponding to the entities are analyzed, higher accuracy and higher feasibility can be achieved.
Disclosure of Invention
The invention provides an intelligent recommendation method and device for numerical values in contracts, which are used for giving out recommended numerical values when the numerical values agreed in the contracts are unreasonable, so that legal risks are avoided.
The invention provides an intelligent recommendation method for numerical values in contracts, which mainly comprises the following steps:
acquiring a target contract and a related contract template;
clustering the contract template, judging the category of the target contract in the contract template, and acquiring the contract category and the contract template content of the category;
performing natural language processing analysis on the target contract to obtain a clause with a numerical type in the clause;
acquiring all similar clauses of the clauses in a contract template of the same category;
analyzing the distribution of values in the similar clauses;
judging the corresponding distribution of the target contract value in the contract template; if the corresponding distribution ratio is smaller than a certain threshold value, giving a warning prompt; or/and
judging whether the target contract value exceeds a recommended value of a corresponding contract law, and giving a warning prompt if the value is not in a recommended value interval;
and gives a recommended value.
Further optionally, in the method as described above, the clustering the contract templates mainly includes:
and searching through a contract platform and a search engine to obtain a contract template, and clustering through the title and the content of the contract template. The clustering method adopts the bitch algorithm of a scimit-spare tool.
The clustering of the same template further comprises:
and removing scattered clustering points and removing noise data of the contract template.
Further optionally, in the method as described above, the performing natural language processing analysis on the target contract to obtain the clause with the numerical type therein mainly includes:
acquiring each clause of a contract, and performing part-of-speech tagging and named entity identification on each clause;
if one or more numerical value types are identified in each clause of the target contract, extracting the clause and the numerical value of the contract;
further optionally, in the method as described above, the acquiring, in the contract template of the same category, all similar terms of the term mainly includes:
calculating the similarity between each clause in the contract template and a numerical clause in the target contract by adopting a text similarity method;
when the similarity of the clauses is larger than a certain threshold value, extracting a numerical part in the clauses;
further optionally, in the method as described above, the extracting the numerical part of the clauses mainly includes:
and analyzing the dependency entities corresponding to the numerical values by adopting a syntax dependency tool. If the value type corresponding to the target contract is the same as the entity on which the target contract depends, taking the value as a reference value of the target contract;
when the dependent entity cannot be found, but the context of the numerical part in the clause is the same as the nearest entity. This value is taken as a reference value for the target contract value.
Further optionally, in the method as described above, the analyzing the distribution of values in the similar clauses mainly includes:
counting the number of reference values, and calculating the percentage of each value;
when the number of the numerical values is too large, carrying out sectional statistics according to the numerical values, and carrying out statistics on the percentage of each section;
a distribution of numerical values in the contract is obtained.
Further optionally, in the method as described above, the determining a corresponding distribution of the target contract value in the contract template; if the corresponding distribution ratio is smaller than a certain threshold, the method mainly comprises the following steps:
counting the number of each numerical value in the contract template, and calculating the percentage of each numerical value;
when the number of different numerical values is larger than a certain threshold value, carrying out sectional statistics according to the numerical values, and carrying out statistics on the percentage of each section to obtain numerical value distribution;
judging whether the target contract value is in the value distribution, if not, giving a warning prompt;
if yes, but in the numerical distribution, the proportion is less than a certain percentage, and warning reminding is given.
Further optionally, in the method as described above, the determining that the target contract value exceeds the recommended value of the corresponding contract law, and the value is not within the recommended value interval, and giving a warning prompt mainly includes:
and obtaining a contract method corresponding to the type according to the type of the contract template, obtaining sentences related to the named entity in the corresponding contract method according to the content of the named entity, carrying out syntactic analysis on the sentences, and searching sentences of related recommended compensation amounts in the context of the named entity. If the similarity between the matched sentences in the contractual law and the contract sentences is greater than a certain threshold, the numerical value is considered as a recommended numerical value about the problem in the contractual law.
And comparing the target contract with the recommended value in the contractual law, and if the target contract is greater than or less than the current contract value, giving out a warning prompt and giving out the recommended value in the contractual law. And displayed and interpreted near the corresponding value of the current contract terms.
Further optionally, in the method as described above, the giving of the recommended value mainly includes:
carrying out early warning prompt near the value position of the contract and giving a recommended value;
an intelligent recommendation method and device for numerical values in contracts are characterized in that the device comprises:
the acquisition module is used for converting the paper contract into an electronic contract, and the electronic contract is further processed into a format which can be analyzed by a natural language processing tool;
the clustering and matching module is used for clustering the contract templates and acquiring contract data in the contract template category corresponding to the current contract to be processed;
the numerical data extraction module is used for extracting the numerical content in the corresponding contract template according to the numerical content in the target contract;
the numerical distribution calculation module is used for carrying out statistical analysis on the numerical content in the contract to obtain reasonable distribution;
and the numerical value recommending and warning module is used for warning unreasonable contract numerical values and recommending reasonable numerical values.
The technical scheme provided by the embodiment of the invention has the following beneficial effects:
the invention can analyze the conventional numerical value of the contract numerical value in various contracts and give the reference value and the percentage. The method helps people needing to sign the contract know the probable value of others when signing the contract, recommends the reference value in the contract clause, and avoids the damage or cheating of the benefit of the people.
Drawings
FIG. 1 is a flow chart of an embodiment of a method for recommending values in a contract according to the present invention;
fig. 2 is a block diagram of an embodiment of a contract value recommendation apparatus according to the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in detail with reference to the accompanying drawings and specific embodiments.
Fig. 1 is a flowchart of an embodiment of a method and an apparatus for intelligently recommending a value in a contract according to the present invention. As shown in fig. 1, the method and apparatus for intelligently recommending numerical values in a contract according to this embodiment may specifically include the following steps:
and 101, when the contract is a paper contract, taking a picture and ocr through software, if the contract is an electronic contract, directly carrying out ocr or carrying out format derivation to obtain a text of the contract to be signed.
And 102, searching through a platform or a search engine which specially collects various contracts to obtain various contract templates, and clustering the contract templates. And clustering through the contract template titles and the content to obtain template categories of various contracts. The clustering method can adopt the bitch algorithm of scimit-spare. After the contracts are subjected to word segmentation, pretreatment and feature extraction, all categories of contract templates are obtained through a bitch clustering algorithm. The Bitch clustering can automatically aggregate when the number of the types of the contracts to be aggregated is unknown, so that the optimal clustering effect is obtained, and the method is more accurate and convenient than the common kmeans clustering.
The contract platform is a platform for providing contract template making, contract verification and other services, and has a large number of contracts submitted by users. Desensitization treatment may be done on the same day, which does not include numerical type desensitization. Search engine search is mainly based on a crawler technology to capture various contracts. The above process can obtain training data for a large number of contract templates.
And 103, removing the template noise. And removing scattered clustering points, namely removing classes with the data volume smaller than a certain threshold value. Since such too unique a stencil may cause noise. The special header is removed. For example, some contracts in a same category are clearly distinguished from others in title, and even if similar in content, such templates are denoised.
When a new target contract is obtained, step 104, it is necessary to calculate which template class the target contract belongs to. The distance between the content of the target contract and each contract template clustering center needs to be calculated, and then the target contract is clustered into a corresponding template category. The text characteristics of the current contract are calculated, the similarity between the current contract and each category template is calculated, the category with the highest similarity is selected, and the target contract is classified into the template contracts of the category. And then, calculating the similarity between the title of the target contract and other contracts in the template library, and confirming that the contract in the template library and the target contract belong to the same contract when the similarity of the standard-reaching questions also reaches a certain threshold value.
And acquiring all similar clauses of the clauses in a contract template of the same category. Calculating the similarity between each clause in the contract template and a numerical clause in the target contract by adopting a text similarity method; and when the similarity of the clauses is greater than a certain threshold, identifying by adopting a part-of-speech tagging tool and a named entity tool, and extracting a numerical part in the clauses.
And step 107, counting the number of each numerical value in the contract template, and calculating the percentage of each numerical value. And when the different numerical values are excessive, carrying out sectional statistics according to the numerical values, and carrying out statistics on the percentage of each section to obtain the numerical value distribution. For example, if the contract is for indemnity responsibility, the indemnity amount in the contract template is 3000, 3500, 4902, 4508, etc. If there are various amounts, then statistical analysis can be performed on the values, and segmentation can be performed to obtain the distribution of 3000 + 3500: 30%, 3500 and 4000 yuan: 20%, 4000-4500 membered: 40%, others: 10 percent.
And obtaining a contract method corresponding to the type according to the type of the contract template, obtaining sentences related to the named entity in the corresponding contract method according to the content of the named entity, performing syntactic analysis on the sentences, and searching sentences of related recommended indemnity amounts. If the similarity between the matched sentences in the contractual law and the contract sentences is greater than a certain threshold, the numerical value is considered as a recommended numerical value about the problem in the contractual law.
And 108, comparing the target contract with the recommended value in the contractual law, and giving out a warning prompt and a recommended value in the contractual law if the target contract is larger than or smaller than the current contract value. And displayed and interpreted near the corresponding value of the current contract terms.
And acquiring all values of which the ratio is greater than a certain proportion in the contract value distribution, calculating the average of the values, and giving a reminding mark when the ratio of the value of the target contract to the average value in the contract template is greater than a preset multiple. And recommend the average in the contract template. And displaying and recommending the contract in the vicinity of the corresponding value of the current contract clause.
Fig. 2 is a flowchart of an embodiment of a method and an apparatus for intelligently recommending a value in a contract according to the present invention. As shown in fig. 2, the intelligent recommendation apparatus for numerical values in a contract in this embodiment may specifically include:
the acquisition module is used for converting the paper contract into an electronic contract, and the electronic contract is further processed into a format which can be analyzed by a natural language processing tool;
the clustering and matching module is used for clustering the contract templates and acquiring contract data in the contract template category corresponding to the current contract to be processed;
the numerical data extraction module is used for extracting the numerical content in the corresponding contract template according to the numerical content in the target contract;
the numerical distribution calculation module is used for carrying out statistical analysis on the numerical content in the contract to obtain reasonable distribution;
and the numerical value recommending and warning module is used for warning unreasonable contract numerical values and recommending reasonable numerical values.
The implementation principle and technical effect of the intelligent recommendation device for the numerical value in the contract implemented by using the module are the same as those of the related method embodiment, and the details of the related method embodiment may be referred to, and are not described herein again.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (10)
1. An intelligent recommendation method for numerical values in contracts is characterized by comprising the following steps:
acquiring a target contract and a related contract template;
clustering the contract template, judging the category of the target contract in the contract template, and acquiring the contract category and the contract template content of the category;
performing natural language processing analysis on the target contract to obtain a clause with a numerical type in the clause;
acquiring all similar clauses of the clauses in a contract template of the same category;
analyzing the distribution of values in the similar clauses;
judging the corresponding distribution of the target contract value in the contract template; if the corresponding distribution ratio is smaller than a certain threshold value, giving a warning prompt; or/and
judging whether the target contract value exceeds a recommended value of a corresponding contract law, and giving a warning prompt if the value is not in a recommended value interval;
and gives a recommended value.
2. The method of claim 1, wherein the clustering of contract templates comprises:
obtaining a contract template through a contract platform and search engine search, and clustering through the title and the content of the contract template;
the clustering of the same template further comprises:
and removing scattered clustering points and removing noise data of the contract template.
3. The method of claim 1, wherein the analyzing the target contract for natural language processing to obtain the terms with numerical type therein comprises:
acquiring each clause of a contract, and performing part-of-speech tagging and named entity identification on each clause;
if one or more value types are identified in each clause of the target contract, the clause and the value of the contract are extracted.
4. The method of claim 1, wherein said obtaining all similar terms of said terms in a same category of contract template essentially comprises:
calculating the similarity between each clause in the contract template and a numerical clause in the target contract by adopting a text similarity method;
when the similarity of the clauses is larger than a certain threshold value, the numerical part in the clauses is extracted.
5. The method of claim 4, wherein the portion of the values in the extracted clause consists essentially of:
analyzing the dependency entities corresponding to the numerical values by adopting a syntax dependency tool; if the value type corresponding to the target contract is the same as the entity on which the target contract depends, taking the value as a reference value of the target contract;
when the dependent entity cannot be found, but the context of the numerical part in the clause is the same as the nearest entity; this value is taken as a reference value for the target contract value.
6. The method of claim 1, wherein said analyzing distribution of values in said similar terms comprises essentially of:
counting the number of reference values, and calculating the percentage of each value;
when the number of the numerical values is too large, carrying out sectional statistics according to the numerical values, and carrying out statistics on the percentage of each section;
a distribution of numerical values in the contract is obtained.
7. The method of claim 1, wherein the determining a corresponding distribution of target contract values in a contract template; if the corresponding distribution ratio is smaller than a certain threshold, the method mainly comprises the following steps:
counting the number of each numerical value in the contract template, and calculating the percentage of each numerical value;
when the number of different numerical values is larger than a certain threshold value, carrying out sectional statistics according to the numerical values, and carrying out statistics on the percentage of each section to obtain numerical value distribution;
judging whether the target contract value is in the value distribution, if not, giving a warning prompt;
if yes, but in the numerical distribution, the proportion is less than a certain percentage, and warning reminding is given.
8. The method according to claim 1, wherein the judging that the target contract value exceeds the recommended value corresponding to the contractual law, the value is not in the recommended value interval, and giving a warning prompt mainly comprises:
obtaining a contract method corresponding to the type according to the type of the contract template, obtaining sentences related to the named entity in the corresponding contract method according to the content of the named entity, carrying out syntactic analysis on the sentences, and searching sentences of relevant recommended indemnity amounts in the context of the named entity; if the similarity between the matched sentences in the contract law and the contract sentences is greater than a certain threshold value, determining the recommended indemnity amount as a recommended value in the contract law;
comparing the target contract with the recommended value in the contract law, if the target contract is larger than or smaller than the current contract value, giving out a warning prompt, and giving out the recommended value in the contract law; and displayed and interpreted near the corresponding value of the current contract terms.
9. The method of claim 1, wherein said presenting recommended values comprises:
and carrying out early warning prompt near the value position of the contract and giving a recommended value.
10. An intelligent recommendation device for numerical values in contracts, characterized in that the device comprises:
the acquisition module is used for converting the paper contract into an electronic contract, and the electronic contract is further processed into a format which can be analyzed by a natural language processing tool;
the clustering and matching module is used for clustering the contract templates and acquiring contract data in the contract template category corresponding to the current contract to be processed;
the numerical data extraction module is used for extracting the numerical content in the corresponding contract template according to the numerical content in the target contract;
the numerical distribution calculation module is used for carrying out statistical analysis on the numerical content in the contract to obtain reasonable distribution;
and the numerical value recommending and warning module is used for warning unreasonable contract numerical values and recommending reasonable numerical values.
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