CN111125322B

CN111125322B - Information searching method and device, electronic equipment and storage medium

Info

Publication number: CN111125322B
Application number: CN201911137208.7A
Authority: CN
Inventors: 周晗; 苏海萍; 柳超
Original assignee: Beijing Jindi Technology Co Ltd
Current assignee: Beijing Jindi Technology Co Ltd
Priority date: 2019-11-19
Filing date: 2019-11-19
Publication date: 2021-02-12
Anticipated expiration: 2039-11-19
Also published as: CN111125322A

Abstract

The embodiment of the disclosure discloses an information searching method and device, electronic equipment and a storage medium, wherein the information searching method comprises the following steps: receiving a search request, wherein the search request comprises a search keyword; searching based on the search keyword to obtain related information of at least one candidate object; determining a relationship between the at least one candidate object based on the related information of the at least one candidate object; obtaining a ranking value of the at least one candidate object based on a relationship between the at least one candidate object; and sorting the at least one candidate object based on the at least one candidate object sorting value, and outputting a search result. The search result ordering method and the search result ordering device enable the search results to better meet the search requirements of most users in the ordering aspect, and therefore search efficiency is improved.

Description

Information searching method and device, electronic equipment and storage medium

Technical Field

The present disclosure relates to search technologies, and in particular, to an information search method and apparatus, an electronic device, and a storage medium.

Background

In practical application, some information search related to companies, names of people, addresses and the like is often required. When the address information is searched, the address can be distinguished through the rule and the model, and the accuracy of address identification is high. The distinction degree between the company word size and the person name is not high, so that when the company word size or the person name information is searched, a search result of a plurality of information such as the person name and the company name related to a search word can be obtained, and the search experience of a user can be seriously influenced due to the lack of the discrimination of the person name. The existing name distinguishing method mainly comprises two methods, one method is to use a name database of a search word matching background, if the search word is matched with the name database, the user is considered to be a person to be searched, the method can not solve the problem of conflict between the company word size and the name, and can not identify unknown words (namely words which are not stored in the name database); the other method is based on rules, and judges whether the search word is the name of a person by matching the first character of the search word with the length with the common surname, and the method causes that a large number of search words can be judged as the name of the person when the word size of a company is searched.

Since a search word used for searching is usually a short text when information searching is performed, a word type of the search word cannot be obtained according to context, and if a person name is not determined for the search word, since a text relevance of a document of the short text and the person name is higher than a text relevance of a document of the short text and the company name, a company matching the person name in a search result is generally ranked before a company matching the company name. For example, when the user inputs the search word "safe" to perform a search, the company name of which the corporate law and the responsible person are "safe" in the search result is arranged before the company name of which "safe" is included in the company names such as "safe insurance" and "safe bank".

However, most users' search intentions are to focus on names of people or companies matched with search terms, so search results based on the prior art are not in accordance with search requirements of most users in terms of ranking, users cannot intuitively obtain focused information from the search results, and focused information needs to be further obtained from the search results, so that search efficiency is low, and user experience is affected.

Disclosure of Invention

The embodiment of the disclosure provides a technical scheme for information search.

According to an aspect of the embodiments of the present disclosure, there is provided an information search method, including:

receiving a search request, wherein the search request comprises search keywords;

searching based on the search keyword to obtain related information of at least one candidate object;

determining a relationship between the at least one candidate object based on the related information of the at least one candidate object;

and ranking the at least one candidate object based on the at least one candidate object ranking value, and outputting a search result, wherein the search result comprises the related information of the at least one candidate object.

Optionally, in the information search method according to any embodiment of the present disclosure, the obtaining a ranking value of the at least one candidate object based on a relationship between the at least one candidate object includes:

acquiring a weight value between any two candidate objects with a direct relation in the at least one candidate object based on the relation between the at least one candidate object;

and acquiring the ranking value of the at least one candidate object based on the weight value between any two acquired candidate objects with direct relation in the at least one candidate object.

Optionally, in the information search method according to any embodiment of the present disclosure, the obtaining, based on the relationship between the at least one candidate object, a weight value between any two candidate objects having a direct relationship in the at least one candidate object includes:

if the relationship between the two candidate objects with the direct relationship is the investment relationship, determining a weight value between the two candidate objects with the direct relationship based on the investment proportion between the investment amount between the two candidate objects with the direct relationship and the total investment amount of the invested object in the two candidate objects with the direct relationship;

and if the relationship between the two candidate objects with the direct relationship is a relationship other than the investment relationship, determining the weight value between the two candidate objects with the direct relationship based on a preset rule.

Optionally, in the information search method according to any embodiment of the present disclosure, the obtaining an ordering value of the at least one candidate object based on a weight value between any two obtained candidate objects having a direct relationship includes:

respectively taking one candidate object of the at least one candidate object as a current candidate object, and acquiring the ranking value of the current candidate object based on the number of the at least one candidate object, the weight value between other candidate objects having direct relations to the current candidate object and the current candidate object, the number of the other candidate objects having direct relations to the at least one candidate object, and the ranking value of the other candidate objects.

Optionally, in the information search method according to any embodiment of the present disclosure, the ranking value pr (u) of the current candidate object u is obtained based on the following formula:

wherein d is an attenuation factor and is a preset value; n is the number of the at least one candidate, nb (u) represents the set of other candidates of the at least one candidate having a direct relationship to the current candidate, d (v) represents the number of candidates of the other candidates having a direct relationship to the at least one candidate, w (u, v) represents the weight value between the other candidates v and the current candidate u, pr (v) represents the ranking value of the other candidates v.

determining an initial ranking value of each candidate object in the at least one candidate object;

and (3) performing the operation iteratively: respectively taking one candidate object of the at least one candidate object as a current candidate object, and based on a formula

And acquiring the ranking value PR (u) of the current candidate object u until a preset condition is met, and acquiring the ranking value of each candidate object in at least one candidate object.

Optionally, in the information search method according to any embodiment of the present disclosure, the preset condition includes any one or more of the following:

the number of times of the iterative execution operation reaches a preset number of times, and/or the absolute value of the difference between the ranking values of the same candidate object in any one or more candidate objects obtained through the iterative execution operation for the last two times is smaller than a first preset threshold value.

Optionally, in the information search method according to any embodiment of the present disclosure, after the obtaining the ranking value of the at least one candidate object, the method further includes:

in response to an absolute value of a difference between ranking values between two candidates having a direct relationship among the at least one candidate being greater than a second preset threshold, compensating for a lower ranking value based on a higher ranking value of the two candidates having the absolute value of the difference being greater than the second preset threshold.

determining an entity prior compensation score of the company name based on company entity information which is a candidate of the company name;

compensating the ranking value corresponding to the company name by using the entity prior compensation score of the company name;

the sorting the at least one candidate object based on the at least one candidate object sorting value and outputting a search result comprises: and ranking the at least one candidate object based on the at least one candidate object ranking value obtained by compensating the ranking value corresponding to the company name by using the entity prior compensation score of the company name, and outputting a search result.

Optionally, in the information search method according to any embodiment of the present disclosure, the candidate object includes any one or more of: a person name, a company name matching the search keyword as a person name keyword, and a company name matching the search keyword as a company name keyword; and/or the presence of a gas in the gas,

the search keyword comprises any one or more of the following items: name of person, company name, brand name, project name; and/or the presence of a gas in the gas,

the relationship between the at least one candidate object comprises any one or more of the following items: investment relations, corporate relations, stakeholder relations, job relations, branch relations.

According to another aspect of the embodiments of the present disclosure, there is provided an information search apparatus including:

the receiving module is used for receiving a search request, wherein the search request comprises search keywords;

the search module is used for searching based on the search keyword to obtain the related information of at least one candidate object;

a determining module for determining a relationship between the at least one candidate object based on the related information of the at least one candidate object;

the obtaining module is used for obtaining the ranking value of the at least one candidate object based on the relation between the at least one candidate object;

and the sorting module is used for sorting the at least one candidate object based on the at least one candidate object sorting value and outputting a search result, wherein the search result comprises the related information of the at least one candidate object.

Optionally, in the information search apparatus according to any embodiment of the present disclosure, the candidate object includes any one or more of: a person name, a company name matching the search keyword as a person name keyword, and a company name matching the search keyword as a company name keyword; and/or the presence of a gas in the gas,

Optionally, in the information search apparatus according to any embodiment of the present disclosure, the obtaining module includes:

a first obtaining unit, configured to obtain, based on a relationship between the at least one candidate object, a weight value between any two candidate objects having a direct relationship in the at least one candidate object;

and the second obtaining unit is used for obtaining the ranking value of the at least one candidate object based on the weight value between any two obtained candidate objects with direct relation.

Optionally, in the information search apparatus according to any embodiment of the present disclosure, the first obtaining unit is specifically configured to: if the relationship between the two candidate objects with the direct relationship is the investment relationship, determining a weight value between the two candidate objects with the direct relationship based on the investment proportion between the investment amount between the two candidate objects with the direct relationship and the total investment amount of the invested object in the two candidate objects with the direct relationship; and if the relationship between the two candidate objects with the direct relationship is a relationship other than the investment relationship, determining the weight value between the two candidate objects with the direct relationship based on a preset rule.

Optionally, in the information search apparatus according to any embodiment of the present disclosure, the second obtaining unit is specifically configured to: respectively taking one candidate object of the at least one candidate object as a current candidate object, and acquiring the ranking value of the current candidate object based on the number of the at least one candidate object, the weight values between other candidate objects having direct relations to the current candidate object and the current candidate object, the number of the other candidate objects having direct relations to the at least one candidate object, and the ranking values of the other candidate objects.

Optionally, in the information searching apparatus according to any embodiment of the present disclosure, the second obtaining unit is specifically configured to obtain the ranking value pr (u) of the current candidate object u based on the following formula:

Optionally, in the information search apparatus according to any embodiment of the present disclosure, the second obtaining unit is specifically configured to:

Optionally, in the information search apparatus according to any embodiment of the present disclosure, the preset condition includes any one or more of:

Optionally, in the information search apparatus according to any embodiment of the present disclosure, the apparatus further includes:

the first compensation module is used for responding to the fact that the absolute value of the difference value between the ranking values of two candidate objects with direct relation in the at least one candidate object is larger than a second preset threshold value according to the ranking value of the at least one candidate object obtained by the obtaining module, and compensating the lower ranking value based on the higher ranking value in the two candidate objects with the absolute value of the difference value larger than the second preset threshold value;

the sorting module is specifically configured to sort the at least one candidate object based on the at least one candidate object sorting value compensated by the first compensation module, and output a search result.

the determining module is used for determining an entity prior compensation score of the company name based on company entity information which is a candidate object of the company name;

the second compensation module is used for compensating the ranking value corresponding to the company name by utilizing the entity prior compensation score of the company name;

the ranking module is specifically configured to rank the at least one candidate object based on the at least one candidate object ranking value obtained by compensating the ranking value corresponding to the company name by using the entity prior compensation score of the company name, and output a search result.

According to another aspect of the embodiments of the present disclosure, there is provided an electronic device including:

a memory for storing a computer program;

a processor, configured to execute the computer program stored in the memory, and when the computer program is executed, implement the information search method according to any of the above embodiments of the present disclosure.

According to still another aspect of the embodiments of the present disclosure, there is provided a computer-readable storage medium having a computer program stored thereon, where the computer program is executed by a processor to implement the information searching method according to any of the above embodiments of the present disclosure.

Based on the information search method and apparatus, the electronic device, and the storage medium provided by the above embodiments of the present disclosure, after receiving a search request, a search is performed based on a search keyword in the search request to obtain related information of at least one candidate object (a person name, a company name, a brand name, a project name, and the like), a relationship between the at least one candidate object is determined according to the related information, a ranking value of the at least one candidate object is obtained based on the relationship between the at least one candidate object, and then a search result is output by ranking based on the ranking value of the at least one candidate object. According to the method and the device, the candidate objects are not distinguished to be the names of people or the names of companies any more, the ranking values of the candidate objects are determined based on the relation among at least one searched candidate object, all the candidate objects are ranked uniformly, all the candidate objects matched with the search keywords, such as the names of the companies, the names of people, the names of trademarks, the names of items and the like, can be regarded as the same type of documents, the ranking values are calculated uniformly and ranked in a mixed mode, the search results are enabled to be more in line with the search requirements of most users in the ranking mode, therefore the users can obtain the attention information of the users from the search results intuitively and conveniently, the search efficiency is improved, and the user experience is improved.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the disclosure and together with the description, serve to explain the principles of the disclosure.

The present disclosure may be more clearly understood from the following detailed description, taken with reference to the accompanying drawings, in which:

fig. 1 is a flowchart of an embodiment of an information search method according to the present disclosure.

Fig. 2 is a flowchart of another embodiment of the disclosed information searching method.

Fig. 3 is a diagram of an application example in the embodiment of the present disclosure.

Fig. 4 is a schematic structural diagram of an embodiment of the information search apparatus of the present disclosure.

Fig. 5 is a schematic structural diagram of another embodiment of the information search apparatus according to the present disclosure.

Fig. 6 is a schematic structural diagram of an embodiment of an electronic device according to the present disclosure.

Detailed Description

Various exemplary embodiments of the present disclosure will now be described in detail with reference to the accompanying drawings. It should be noted that: the relative arrangement of the components and steps, the numerical expressions, and numerical values set forth in these embodiments do not limit the scope of the present disclosure unless specifically stated otherwise.

It will be understood by those of skill in the art that the terms "first," "second," and the like in the embodiments of the present disclosure are used merely to distinguish one element from another, and are not intended to imply any particular technical meaning, nor is the necessary logical order between them.

It is also understood that in embodiments of the present disclosure, "a plurality" may refer to two or more and "at least one" may refer to one, two or more.

It is also to be understood that any reference to any component, data, or structure in the embodiments of the disclosure, may be generally understood as one or more, unless explicitly defined otherwise or stated otherwise.

In addition, the term "and/or" in the present disclosure is only one kind of association relationship describing an associated object, and means that three kinds of relationships may exist, for example, a and/or B may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" in the present disclosure generally indicates that the former and latter associated objects are in an "or" relationship.

It should also be understood that the description of the various embodiments of the present disclosure emphasizes the differences between the various embodiments, and the same or similar parts may be referred to each other, so that the descriptions thereof are omitted for brevity.

Meanwhile, it should be understood that the sizes of the respective portions shown in the drawings are not drawn in an actual proportional relationship for the convenience of description.

The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the disclosure, its application, or uses.

Techniques, methods, and apparatus known to those of ordinary skill in the relevant art may not be discussed in detail but are intended to be part of the specification where appropriate.

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, further discussion thereof is not required in subsequent figures.

The disclosed embodiments may be applied to electronic devices such as terminal devices, computer systems, servers, etc., which are operational with numerous other general purpose or special purpose computing system environments or configurations. Examples of well known terminal devices, computing systems, environments, and/or configurations that may be suitable for use with electronic devices, such as terminal devices, computer systems, servers, and the like, include, but are not limited to: personal computer systems, server computer systems, thin clients, thick clients, hand-held or laptop devices, microprocessor-based systems, set-top boxes, programmable consumer electronics, networked personal computers, minicomputer systems, mainframe computer systems, distributed cloud computing environments that include any of the above, and the like.

Electronic devices such as terminal devices, computer systems, servers, etc. may be described in the general context of computer system-executable instructions, such as program modules, being executed by a computer system. Generally, program modules may include routines, programs, objects, components, logic, data structures, etc. that perform particular tasks or implement particular abstract data types. The computer system/server may be practiced in distributed cloud computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed cloud computing environment, program modules may be located in both local and remote computer system storage media including memory storage devices.

Fig. 1 is a flowchart of an embodiment of an information search method according to the present disclosure. As shown in fig. 1, the information search method of the embodiment includes:

102, a search request is received, wherein the search request comprises a search keyword.

The search keyword may be, for example, a person name, a company name, a brand name, a project name, and the like.

And 104, searching based on the search keyword to obtain the related information of at least one candidate object.

In some embodiments of the present disclosure, the candidate objects may include, but are not limited to, any one or more of the following: a person name, a company name matching the search keyword as a person name keyword, a company name matching the search keyword as a company name keyword, and the like.

In some embodiments of the present disclosure, when the candidate object is a name of a person, the related information of the candidate object may include, but is not limited to, any one or more of the following: information on the job title of the company, information on the legal person, investment information, information on the stockholder, etc.; when the candidate is a company name, the related information of the candidate may include, but is not limited to, any one or more of the following: registered funds of the company, the legal person, the shareholder, investment information, head office-affiliate information, and the like. The present embodiment does not limit this.

And 106, determining the relation between the at least one candidate object based on the relevant information of the at least one candidate object.

In some of the embodiments of the present disclosure, the relationship between the at least one candidate object may include, for example and without limitation, any one or more of the following: investment relationships, corporate relationships, stakeholder relationships, job relationships, branch office relationships, and the like.

And 108, acquiring the ranking value of the at least one candidate object based on the relation between the at least one candidate object.

And 110, sorting the at least one candidate object based on the at least one candidate object sorting value, for example, sorting the at least one candidate object in an order from high to low according to the sorting value, and outputting a search result, where the search result includes the related information of the sorted at least one candidate object.

According to the information searching method provided by the above embodiment of the present disclosure, after a search request is received, a search is performed based on a search keyword in the search request to obtain related information of at least one candidate object (a name of a person, a name of a company, a name of a trademark, a name of an item, and the like), a relationship between the at least one candidate object is determined according to the related information, an ordering value of the at least one candidate object is obtained based on the relationship between the at least one candidate object, and then an ordering is performed based on the ordering value of the at least one candidate object and a search result is output. According to the method and the device, the candidate objects are not distinguished to be the names of people or the names of companies any more, the ranking values of the candidate objects are determined based on the relation among at least one searched candidate object, all the candidate objects are ranked uniformly, all the candidate objects matched with the search keywords, such as the names of the companies, the names of people, the names of trademarks, the names of items and the like, can be regarded as the same type of documents, the ranking values are calculated uniformly and ranked in a mixed mode, the search results are enabled to be more in line with the search requirements of most users in the ranking mode, therefore the users can obtain the attention information of the users from the search results intuitively and conveniently, the search efficiency is improved, and the user experience is improved.

Fig. 2 is a flowchart of another embodiment of the disclosed information searching method. As shown in fig. 2, operation 108 may include, based on the embodiment shown in fig. 1:

1081, obtaining a weight value between any two candidates having a direct relationship based on a relationship between at least one of the candidates.

Wherein, the two candidates have direct relation, that is, the two candidates have direct investment relation, legal relation, stockholder relation, duties relation, branches relation, etc.

1082, obtaining an ordering value of at least one candidate object based on a weight value between any two obtained candidate objects having a direct relationship.

In some of the implementations of the embodiments of the present disclosure, operation 1081 may include:

if the relationship between the two candidate objects with the direct relationship is the investment relationship, determining the weight value between the two candidate objects with the direct relationship based on the investment proportion between the investment amount between the two candidate objects with the direct relationship and the total investment amount of the invested objects in the two candidate objects with the direct relationship;

In some of the implementations of the embodiments of the present disclosure, operation 1082 may include: taking one candidate object of the at least one candidate object as a current candidate object, respectively, obtaining the ranking value of the current candidate object based on the number of the at least one candidate object, the weight values between the other candidate objects having direct relations to the current candidate object (i.e. the other candidate objects having investment relations, job relations, etc. to the current candidate object) and the current candidate object, the number of the other candidate objects having direct relations to the at least one candidate object, and the ranking values of the other candidate objects.

For example, in some optional examples, the ranking value pr (u) of the current candidate u may be obtained based on the following formula:

in the formula (1), d is an attenuation factor (damping factor) and a damping coefficient, and a preset value is taken and can take a value between 0 and 1, for example, can take a value of 0.85; n is the number of at least one candidate, nb (u) represents the set of other candidates among the at least one candidate having a direct relationship to the current candidate, d (v) represents the number of candidates among the other candidates having a direct relationship to the at least one candidate, w (u, v) represents the weight values between the other candidates v and the current candidate u, and pr (v) represents the ranking values of the other candidates v.

In some optional examples, when obtaining the ranking value of the current candidate object u based on formula (1), an initial ranking value of each candidate object in the at least one candidate object may be determined first; the following operations are then performed iteratively: respectively taking one candidate object of the at least one candidate object as a current candidate object, and obtaining the ranking value PR (u) of the current candidate object u based on a formula (1) until a preset condition is met to obtain the ranking value of each candidate object of the at least one candidate object.

The preset conditions may include, but are not limited to, any one or more of the following: the number of times of the iterative execution operation reaches a preset number of times, and/or the absolute value of the difference between the ordering values of the same candidate object in any one or more candidate objects obtained through the iterative execution operation for the last two times is smaller than a first preset threshold value.

In the embodiment of the disclosure, it is considered that the investment management of one company or people and more companies indicates that the company or people is more important, and the larger the company controlled by the company is, the more important the company or people is. In order to clearly represent the relationship between people and companies and between companies (people and companies are collectively referred to as candidate objects in the embodiment of the disclosure), the relationship between the candidate objects is represented by an association graph with weight values, and people and companies are abstractly represented as nodes in the association graph; candidate objects (person-to-company, and company-to-company relationships, such as investment relationships, corporate relationships, head office-to-branch relationships, etc.) are abstractly represented as edges between two nodes in the association graph; the weight value of an edge represents the degree of association between a person and a company, company and company. The weighted value of the edge between two nodes in the investment relationship may be represented by an investment proportion, and the weighted value of the edge between two nodes in the relationship other than the investment relationships such as the corporate relationship, the stockholder relationship, the incumbent relationship, the branch relationship and the like may be determined according to a preset rule, for example, the weighted value of the edge between two nodes in the corporate relationship and the branch relationship of the head office-branch office may be set to 1, the weighted value of the edge between two nodes in the stockholder relationship and the incumbent relationship may be set to 0.3 or set according to other rules, for example, the weighted value may be set according to the stockholder investment proportion, the importance of the incumbent position and the like. The direction of the edge between two nodes is related to the relationship type, for the investment relationship, the arrow (without arrow end) is the investor (person or company), and the arrow tail (arrow end) is the investor (company); for the relationship of a corporate, an arrow is a company, an arrow tail is a corporate of the company, and the relationship of a stockholder and an incumbent relationship are similar; for a head office-branch relationship, the arrow is the head office and the arrow is the branch office.

Fig. 3 is a diagram illustrating an application example in the embodiment of the present disclosure. Referring to fig. 3, it is assumed that a search is performed based on the search keyword, and the obtained at least one candidate object is: companies C1, C2, C3, C4, C5, C6, human P1, and the relationship between companies C1, C2, C3, C4, C5, C6, and human P1 is shown by fig. 3. The rank values for companies C1, C2, C3, C4, C5, C6, and human P1 may be obtained by:

【1】 And determining the initial ranking value of each node.

Wherein, the node is of a company, and the initial ranking value may be registered capital (in ten thousand dollars) of the company; the nodes are human, the initial ranking values can be weighted average of human external investment amount, weights in the weighted average are expressed by investment proportion, and the obtained initial ranking values are normalized.

For example, assuming that the registered capital of companies C1, C2, C3, C4, C5, C6 are 100 ten thousand, 200 ten thousand, 300 ten thousand, 430 ten thousand, 1500 ten thousand, 2000 ten thousand, respectively, the initial ranking values of the respective nodes are calculated as follows:

PR(P1)＝0.5×100+0.6×200+300＝470，

PR(C1)＝100，

PR(C2)＝200，

PR(C3)＝300，

PR(C4)＝430，

PR(C5)＝1500，

PR(C6)＝2000，

normalizing the initial ranking value to obtain a normalized initial ranking value:

PR(P1)＝0.094，

PR(C1)＝0.020，

PR(C2)＝0.040，

PR(C3)＝0.060，

PR(C4)＝0.086，

PR(C5)＝0.300，

PR(C6)＝0.400。

【2】 Assuming that the attenuation factor d is 0.85, the ranking values of the nodes are respectively obtained based on the formula (1). The first-time calculation obtains the following ordering values of the nodes:

【3】 And respectively executing the step (2) in an iterative manner based on the ranking values of the nodes obtained by the last calculation until preset conditions are met, for example, the number of times of executing the step (2) in the iterative manner reaches preset times or the absolute value of the difference between the ranking values of the same node in any one or more nodes obtained by the last two iterative calculations is less than a first preset threshold value, and stopping executing the iterative manner (2) to obtain the ranking values of the nodes.

For example, the calculated ranking value of each node is used to replace the initial ranking value, and the second calculation is performed, and the obtained ranking value of each node is as follows:

assuming the preset number of times, after two iterations, the preset number of times is reached, and the iteration is stopped to execute the above operation [ 2 ], so as to finally obtain the ranking values of the nodes P1, C1, C2, C3, C4, C5, and C6, which are 0.050, 0.021, 0.026, 0.021, 0.333, 0.039, and 0.021, respectively, and which can be used as scores for ranking the nodes.

For example, when the name of P1 is AA, and the names of C4 and C6 are AA group and AA limited company, respectively, after the user inputs the search keyword AA, the related companies C1, C2 and C3 of P1 are recalled by shareholder matching, and C4 and C6 are recalled by company name matching. If according to the existing sorting mode, the default is that the company matched with the name of the person takes precedence, and the sequence shown in the search result is as follows: c2, C1, C3, C4 and C6. After the ranking value generated based on the person-company association graph is introduced, since the score of P1 is higher than C6 and lower than C4, the order shown in the search result is as follows: c4, C2, C1, C3 and C6 accord with important company names and are arranged in front of the companies matched with the person names, and therefore the user experience is improved.

In addition, based on the above-mentioned ranking value calculation method of the embodiment of the present disclosure, the ranking value obtained by calculation is made to conform to the principle that an important company is more important than a company matching the name of the person, and the related person of the important company is more important. For example, based on the ranking values calculated by embodiments of the present disclosure, it may be achieved that "safe insurance" should be more important than "safe" ranking of the french owner "of" cooperatives, "maryun" of "acriba" is more important than "mayun county" company.

According to the method and the device, complicated name judgment is not needed, the ranking value which is the importance score of people and companies under the same measurement standard is obtained by constructing the association graph of people and companies and applying the ranking value algorithm shown in the formula (1), so that two types of companies which are recalled according to names of people and companies in the search can be ranked more accurately, the rule that the names are identified and the companies which are recalled according to names are ranked in the front is replaced, only the companies which are recalled according to names with high ranking values can be ranked in front of the company list which is recalled in a matching mode with the names of the companies, the search requirements of most users are met, the search efficiency is improved, and the user experience is improved.

In addition, in another embodiment of the information search method of the present disclosure, after obtaining the ranking value of at least one candidate object based on the above embodiments, the method may further include: in response to an absolute value of a difference between ranking values between two candidates of the at least one candidate having a direct relationship (e.g., a direct investment relationship, a branch office relationship, etc.) being greater than a second preset threshold, a lower ranking value is compensated for based on a higher ranking value of the two candidates having an absolute value of the difference being greater than the second preset threshold.

Accordingly, in operation 110, the at least one candidate object may be ranked based on the at least one candidate object ranking value compensated for the ranking value, and a search result may be output.

Since the ranking value is calculated based on a one-way relationship (only the head office has an investment relationship with respect to the head office), the head office cannot enjoy a high ranking value of the head office, and there may be a case where the difference between the ranking values of the head office and the head office is large, which is not in accordance with the actual situation. In the embodiment of the present disclosure, it is considered that the branch office of the important head office should also be relatively important, and after obtaining the ranking values of the candidate objects, if the difference between the ranking values of the head office and the branch office is large (that is, the absolute value of the difference between the two is greater than the second preset threshold), the ranking value of the head office may be compensated according to the preset manner based on the ranking value of the head office, so as to adjust the ranking values of the directly related companies and people with large differences, so as to obtain a more objective and reasonable ranking effect. For example, the ranking value of the branch company may be compensated based on the ranking value of the head company by: the compensated ranking value of the affiliate is the affiliate ranking value + the weight is the total affiliate ranking value, wherein the weight value can be set according to an empirical value, for example, the value can be between 0 and 0.8, and can be adjusted according to actual needs.

In addition, in yet another embodiment of the information search method of the present disclosure, after obtaining the ranking value of at least one candidate object based on the above embodiments, the method may further include: determining an entity prior compensation score of the company name based on company entity information which is a candidate of the company name; and compensating the ranking value corresponding to the company name by using the entity prior compensation score of the company name.

Accordingly, in operation 110, at least one candidate object may be ranked based on at least one candidate object ranking value compensated for the ranking value corresponding to the company name by the entity a priori compensation score of the company name, and a search result may be output.

When the ranking values of the respective candidates are calculated based on the above formula (1), the initial ranking values of all the candidates are equal, and the effect of the initial ranking values becomes smaller as the number of times of iteration execution increases. However, for the application scenario of company information search, the information such as the registered capital, the real payment capital, the company property (state, joint, etc.) of the company is the priori knowledge with high reliability, so that after the ranking values of the candidate objects are obtained, the entity priori compensation score of the company name can be determined based on the company entity information according to the preset mode to compensate the ranking value corresponding to the company name, so that the ranking result of the candidate objects in the finally obtained search result is more objective and reasonable. For example, the ranking value corresponding to the company name may be compensated as follows: and the rank value after the compensation of the company name is the rank value corresponding to the calculated company name plus the entity prior compensation score. The entity prior compensation score can be comprehensively determined based on information such as registered capital, real-time payment capital, company properties (state capital, joint capital and the like) and the like of a company, and a specific determination mode can be set according to actual requirements and can be adjusted in real time according to the actual requirements.

Any of the information search methods provided by the embodiments of the present disclosure may be performed by any suitable device having data processing capabilities, including but not limited to: terminal equipment, a server and the like. Alternatively, any of the information search methods provided by the embodiments of the present disclosure may be executed by a processor, for example, the processor may execute any of the information search methods mentioned by the embodiments of the present disclosure by calling a corresponding instruction stored in a memory. And will not be described in detail below.

Those of ordinary skill in the art will understand that: all or part of the steps for implementing the method embodiments may be implemented by hardware related to program instructions, and the program may be stored in a computer readable storage medium, and when executed, the program performs the steps including the method embodiments; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.

Fig. 4 is a schematic structural diagram of an embodiment of the information search apparatus of the present disclosure. The information search device of this embodiment can be used to implement the above-mentioned information search method embodiments of the present disclosure. As shown in fig. 4, the device information search of this embodiment includes: the device comprises a receiving module, a searching module, an obtaining module and a sequencing module. Wherein:

the receiving module is used for receiving a search request, wherein the search request comprises search keywords.

And the searching module is used for searching based on the searching keyword to obtain the related information of at least one candidate object.

In some of the disclosed embodiments, the candidate objects may include, for example, but are not limited to, any one or more of the following: a person name, a company name matching the search keyword as a person name keyword, a company name matching the search keyword as a company name keyword, and the like.

A determining module for determining a relationship between the at least one candidate object based on the relevant information of the at least one candidate object.

And the obtaining module is used for obtaining the ranking value of the at least one candidate object based on the relation between the at least one candidate object.

In some of the implementations of the embodiments of the present disclosure,

the relationship between the at least one candidate object may include, but is not limited to, any one or more of the following: investment relationships, corporate relationships, stakeholder relationships, job relationships, branch office relationships, and the like.

The sorting module is configured to sort the at least one candidate object based on the at least one candidate object sorting value, for example, sort the at least one candidate object in an order from high to low according to the sorting value, and output a search result, where the search result includes related information of the at least one candidate object after sorting.

Based on the information search device provided by the above embodiment of the present disclosure, the candidate objects are no longer distinguished as names of people or names of companies, but the ranking values of the candidate objects are determined based on the relationship between at least one searched candidate object, and all the candidate objects are ranked uniformly, all the candidate objects matching the search keyword, such as the names of companies, the names of people, the names of trademarks, the names of items, and the like, can be regarded as the same type of document, the ranking values are uniformly calculated and ranked in a mixed manner, so that the search result better meets the search requirements of most users in ranking, and thus the users can obtain the attention information from the search result intuitively and conveniently, thereby improving the search efficiency and improving the user experience.

In some implementations of embodiments of the present disclosure, the obtaining module may include: a first obtaining unit, configured to obtain, based on a relationship between the at least one candidate object, a weight value between any two candidate objects having a direct relationship in the at least one candidate object; and the second obtaining unit is used for obtaining the ranking value of the at least one candidate object based on the weight value between any two obtained candidate objects with direct relation.

In some optional examples, the first obtaining unit is specifically configured to: if the relationship between the two candidate objects with the direct relationship is the investment relationship, determining a weight value between the two candidate objects with the direct relationship based on the investment proportion between the investment amount between the two candidate objects with the direct relationship and the total investment amount of the invested object in the two candidate objects with the direct relationship; and if the relationship between the two candidate objects with the direct relationship is a relationship other than the investment relationship, determining the weight value between the two candidate objects with the direct relationship based on a preset rule.

In some optional examples, the second obtaining unit is specifically configured to: respectively taking one candidate object of the at least one candidate object as a current candidate object, and acquiring the ranking value of the current candidate object based on the number of the at least one candidate object, the weight value between other candidate objects having direct relations to the current candidate object and the current candidate object, the number of the other candidate objects having direct relations to the at least one candidate object, and the ranking value of the other candidate objects.

For example, the second obtaining unit is specifically configured to obtain the ranking value pr (u) of the current candidate object u based on the following formula:

in the formula (1), d is an attenuation factor and is a preset value; n is the number of the at least one candidate, nb (u) represents the set of other candidates of the at least one candidate having a direct relationship to the current candidate, d (v) represents the number of candidates of the other candidates having a direct relationship to the at least one candidate, w (u, v) represents the weight value between the other candidates v and the current candidate u, pr (v) represents the ranking value of the other candidates v.

In some optional examples, the second obtaining unit is specifically configured to: determining an initial ranking value of each candidate object in the at least one candidate object; the following operations are iteratively performed: and respectively taking one candidate object in the at least one candidate object as a current candidate object, and obtaining the ranking value PR (u) of the current candidate object u based on a formula (1) until a preset condition is met to obtain the ranking value of each candidate object in the at least one candidate object.

Fig. 5 is a schematic structural diagram of another embodiment of the information search apparatus according to the present disclosure. As shown in fig. 5, compared with the embodiment shown in fig. 4, the information search apparatus of this embodiment may further include: the first compensation module is used for responding to the fact that the absolute value of the difference value between the ranking values of two candidate objects with direct relation in the at least one candidate object is larger than a second preset threshold value according to the ranking value of the at least one candidate object obtained by the obtaining module, and compensating the lower ranking value based on the higher ranking value in the two candidate objects with the difference value larger than the second preset threshold value. Correspondingly, the sorting module is specifically configured to sort the at least one candidate object based on the at least one candidate object sorting value compensated by the first compensation module, and output a search result.

And/or, referring back to fig. 5, the information search apparatus of this embodiment may further include: the determining module is used for determining an entity prior compensation score of the company name based on company entity information which is a candidate object of the company name; and the second compensation module is used for compensating the ranking value corresponding to the company name by using the entity prior compensation score of the company name. Correspondingly, in this embodiment, the ranking module is specifically configured to rank the at least one candidate object based on the at least one candidate object ranking value obtained by compensating the ranking value corresponding to the company name by using the entity prior compensation score of the company name, and output the search result.

In addition, an embodiment of the present disclosure also provides an electronic device, including:

a memory for storing a computer program;

a processor, configured to execute the computer program stored in the memory, and when the computer program is executed, implement the information search method according to any of the above embodiments.

Next, an electronic apparatus according to an embodiment of the present disclosure is described with reference to fig. 6. The electronic device may be either or both of the first device and the second device, or a stand-alone device separate from them, which stand-alone device may communicate with the first device and the second device to receive the acquired input signals therefrom.

FIG. 6 illustrates a block diagram of an electronic device in accordance with one embodiment of the present disclosure. As shown in fig. 6, the electronic device includes one or more processors and memory. The processor may be a Central Processing Unit (CPU) or other form of processing unit having data processing capabilities and/or instruction execution capabilities, and may control other components in the electronic device to perform desired functions.

The memory may include one or more computer program products that may include various forms of computer-readable storage media, such as volatile memory and/or non-volatile memory. The volatile memory may include, for example, Random Access Memory (RAM), cache memory (cache), and/or the like. The non-volatile memory may include, for example, Read Only Memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium and executed by a processor to implement the data search processing methods of the various embodiments of the present disclosure described above and/or other desired functions. Various contents such as an input signal, a signal component, a noise component, etc. may also be stored in the computer-readable storage medium.

In one example, the electronic device may further include: an input device and an output device, which are interconnected by a bus system and/or other form of connection mechanism (not shown).

The input device may also include, for example, a keyboard, a mouse, and the like.

The output device may output various information including the determined distance information, direction information, and the like to the outside. The output devices may include, for example, a display, speakers, a printer, and a communication network and remote output devices connected thereto, among others.

Of course, for simplicity, only some of the components of the electronic device relevant to the present disclosure are shown, and components such as buses, input/output interfaces, and the like are omitted. In addition, the electronic device may include any other suitable components, depending on the particular application.

In addition, the embodiment of the disclosure also provides a computer readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the information search method described in any of the above embodiments is implemented.

In addition to the above-described methods and apparatus, embodiments of the present disclosure may also be a computer program product comprising computer program instructions that, when executed by a processor, cause the processor to perform the steps in the information search method according to various embodiments of the present disclosure described in the "exemplary methods" section above of this specification.

The computer program product may write program code for carrying out operations for embodiments of the present disclosure in any combination of one or more programming languages, including an object oriented programming language such as Java, 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 computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server.

Furthermore, embodiments of the present disclosure may also be a computer-readable storage medium having stored thereon computer program instructions that, when executed by a processor, cause the processor to perform steps in an information search method according to various embodiments of the present disclosure described in the "exemplary methods" section above of this specification.

The computer-readable storage medium may take any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may include, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, 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.

The foregoing describes the general principles of the present disclosure in conjunction with specific embodiments, however, it is noted that the advantages, effects, etc. mentioned in the present disclosure are merely examples and are not limiting, and they should not be considered essential to the various embodiments of the present disclosure. Furthermore, the foregoing disclosure of specific details is for the purpose of illustration and description and is not intended to be limiting, since the disclosure is not intended to be limited to the specific details so described.

In the present specification, the embodiments are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same or similar parts in the embodiments are referred to each other. For the system embodiment, since it basically corresponds to the method embodiment, the description is relatively simple, and for the relevant points, reference may be made to the partial description of the method embodiment.

The block diagrams of devices, apparatuses, systems referred to in this disclosure are only given as illustrative examples and are not intended to require or imply that the connections, arrangements, configurations, etc. must be made in the manner shown in the block diagrams. These devices, apparatuses, devices, systems may be connected, arranged, configured in any manner, as will be appreciated by those skilled in the art. Words such as "including," "comprising," "having," and the like are open-ended words that mean "including, but not limited to," and are used interchangeably therewith. The words "or" and "as used herein mean, and are used interchangeably with, the word" and/or, "unless the context clearly dictates otherwise. The word "such as" is used herein to mean, and is used interchangeably with, the phrase "such as but not limited to".

The methods and apparatus of the present disclosure may be implemented in a number of ways. For example, the methods and apparatus of the present disclosure may be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above-described order for the steps of the method is for illustration only, and the steps of the method of the present disclosure are not limited to the order specifically described above unless specifically stated otherwise. Further, in some embodiments, the present disclosure may also be embodied as programs recorded in a recording medium, the programs including machine-readable instructions for implementing the methods according to the present disclosure. Thus, the present disclosure also covers a recording medium storing a program for executing the method according to the present disclosure.

It is also noted that in the devices, apparatuses, and methods of the present disclosure, each component or step can be decomposed and/or recombined. These decompositions and/or recombinations are to be considered equivalents of the present disclosure.

The previous description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present disclosure. Various modifications to these aspects will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other aspects without departing from the scope of the disclosure. Thus, the present disclosure is not intended to be limited to the aspects shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

The foregoing description has been presented for purposes of illustration and description. Furthermore, this description is not intended to limit embodiments of the disclosure to the form disclosed herein. While a number of example aspects and embodiments have been discussed above, those of skill in the art will recognize certain variations, modifications, alterations, additions and sub-combinations thereof.

Claims

1. An information search method, comprising:

searching based on the search keyword to obtain related information of at least one candidate object; the candidate object comprises any one or more of the following: a person name, a company name matching the search keyword as a person name keyword, and a company name matching the search keyword as a company name keyword;

determining a relationship between the at least one candidate object based on the related information of the at least one candidate object; the relationship between the at least one candidate object comprises any one or more of the following items: investment relations, corporate relations, stakeholder relations, job relations, branch relations;

obtaining a ranking value of the at least one candidate object based on a relationship between the at least one candidate object;

and ranking the at least one candidate object based on the ranking value of the at least one candidate object, and outputting a search result, wherein the search result comprises the related information of the at least one candidate object.

2. The method according to claim 1, wherein obtaining the ranking value of the at least one candidate object based on the relationship between the at least one candidate object comprises:

3. The method according to claim 2, wherein the obtaining a weight value between any two directly related candidates of the at least one candidate based on the relationship between the at least one candidate comprises:

4. The method according to claim 3, wherein the obtaining the ranking value of the at least one candidate object based on the weight value between any two obtained at least one candidate objects having a direct relationship comprises:

5. The method according to claim 4, characterized in that the ranking value PR (u) of the current candidate u is obtained based on the following formula:

6. The method according to claim 5, wherein the obtaining the ranking value of the at least one candidate object based on the weight value between any two obtained at least one candidate objects having a direct relationship comprises:

7. The method according to claim 6, wherein the preset condition comprises any one or more of the following:

8. The method according to any one of claims 1-7, wherein after obtaining the ranking value of the at least one candidate object, further comprising:

9. The method of claim 8, wherein after obtaining the ranking value of the at least one candidate object, further comprising:

the sorting the at least one candidate object based on the sorting value of the at least one candidate object and outputting a search result comprises: and ranking the at least one candidate object based on the at least one candidate object ranking value obtained by compensating the ranking value corresponding to the company name by using the entity prior compensation score of the company name, and outputting a search result.

10. The method of claim 8, wherein the search keywords comprise any one or more of: name of person, company name, brand name, project name.

11. The method according to any one of claims 1-7, wherein after obtaining the ranking value of the at least one candidate object, further comprising:

12. The method of claim 11, wherein the search keyword comprises any one or more of: name of person, company name, brand name, project name.

13. The method according to any one of claims 1 to 7, wherein the search keywords comprise any one or more of: name of person, company name, brand name, project name.

14. An information search apparatus, comprising:

the search module is used for searching based on the search keyword to obtain the related information of at least one candidate object; the candidate object comprises any one or more of the following: a person name, a company name matching the search keyword as a person name keyword, and a company name matching the search keyword as a company name keyword;

a determining module for determining a relationship between the at least one candidate object based on the related information of the at least one candidate object; the relationship between the at least one candidate object comprises any one or more of the following items: investment relations, corporate relations, stakeholder relations, job relations, branch relations

and the sorting module is used for sorting the at least one candidate object based on the sorting value of the at least one candidate object and outputting a search result, wherein the search result comprises the related information of the at least one candidate object.

15. The apparatus of claim 14, wherein the obtaining module comprises:

16. The apparatus of claim 14 or 15, further comprising:

17. The apparatus of claim 16, further comprising:

18. The apparatus of claim 14 or 15, further comprising:

19. An electronic device, comprising:

a memory for storing a computer program;

a processor for executing a computer program stored in the memory, and when executed, implementing the method of any of the preceding claims 1-13.

20. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the method of any one of the preceding claims 1 to 13.