CN112507220A

CN112507220A - Information pushing method, device and medium

Info

Publication number: CN112507220A
Application number: CN202011420101.6A
Authority: CN
Inventors: 陈岳峰
Original assignee: Ping An Life Insurance Company of China Ltd
Current assignee: Ping An Life Insurance Company of China Ltd
Priority date: 2020-12-07
Filing date: 2020-12-07
Publication date: 2021-03-16

Abstract

The application relates to an information pushing method, an information pushing device and an information pushing medium, wherein the method comprises the following steps: acquiring target social contact information of a target object according to authorization information of the target object; determining an associated object associated with the target object and a target object characteristic of the target object according to the target social information; acquiring the associated object characteristics of the associated object; determining target insurance according to the target object characteristics and the associated object characteristics; and sending the push information of the target insurance to the target object. By the aid of the method and the device, accuracy of pushing insurance is improved.

Description

Information pushing method, device and medium

Technical Field

The application relates to the technical field of intelligent recommendation, and mainly relates to an information pushing method, an information pushing device and an information pushing medium.

Background

With the increasing development of internet technology, pushing a user by using the internet technology also becomes a new pushing mode. The push speed of the internet technology is high, the coverage is wide, and the push method has certain push advantages compared with the traditional push technology. For example, in the area of insurance services, insurance can be recommended online.

At present, the technical scheme of indifferent pushing is commonly adopted for pushing insurance to users, namely pushing insurance to all users. The pushing mode is high in cost, the pushed insurance is poor in pertinence, the hit rate of a user is low, the pushed insurance is easy to shield by the user, and subsequent pushing is influenced.

Disclosure of Invention

The embodiment of the application provides an information pushing method, an information pushing device and an information pushing medium, insurance pushing can be carried out based on the characteristics of a target object and the characteristics of a related object related to the target object, and the accuracy rate of pushing can be improved.

In a first aspect, an embodiment of the present application provides an information pushing method, where:

acquiring target social contact information of a target object according to authorization information of the target object;

determining an associated object associated with the target object and a target object characteristic of the target object according to the target social information;

acquiring the associated object characteristics of the associated object;

determining target insurance according to the target object characteristics and the associated object characteristics;

and sending the push information of the target insurance to the target object.

In a second aspect, an embodiment of the present application provides an information pushing apparatus, where:

the processing unit is used for acquiring target social information of the target object according to the authorization information of the target object; determining an associated object associated with the target object and a target object characteristic of the target object according to the target social information; acquiring the associated object characteristics of the associated object; determining target insurance according to the target object characteristics and the associated object characteristics;

and the communication unit is used for sending the push information of the target insurance to the target object.

In a third aspect, an embodiment of the present application provides another information pushing apparatus, including a processor, a memory, a communication interface, and one or at least one program, where the one or at least one program is stored in the memory and configured to be executed by the processor, and the program includes instructions for some or all of the steps described in the first aspect.

In a fourth aspect, the present application provides a computer-readable storage medium, where the computer-readable storage medium stores a computer program, where the computer program makes a computer execute to implement part or all of the steps described in the first aspect.

The embodiment of the application has the following beneficial effects:

after the information pushing method, the information pushing device and the information pushing medium are adopted, the target social contact information of the target object is obtained according to the authorization information of the target object, and then the associated object associated with the target object and the target object characteristic of the target object are determined according to the target social contact information, so that the accuracy of determining the associated object and the target object characteristic is improved. And then, acquiring the associated object characteristics of the associated object, determining the target insurance according to the target object characteristics and the associated object characteristics, and sending push information of the target insurance to the target object. That is, the insurance pushed to the target object is the insurance related to the target object feature and the associated object feature, which improves the accuracy of pushing.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.

Wherein:

fig. 1 is a schematic flowchart of an information pushing method according to an embodiment of the present application;

fig. 2 is a schematic logical structure diagram of an information pushing apparatus according to an embodiment of the present disclosure;

fig. 3 is a schematic entity structure diagram of an information pushing apparatus according to an embodiment of the present disclosure.

Detailed Description

In order to make the technical solutions of the present application better understood, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments obtained by a person of ordinary skill in the art without any inventive work according to the embodiments of the present application are within the scope of the present application.

The terms "first," "second," and the like in the description and claims of the present application and in the above-described drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.

Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.

The network architecture applied by the embodiment of the application comprises a server and electronic equipment. The electronic device may be a Personal Computer (PC), a notebook computer, or a smart phone, and may also be an all-in-one machine, a palm computer, a tablet computer (pad), a smart television playing terminal, a vehicle-mounted terminal, or a portable device. The operating system of the PC-side electronic device, such as a kiosk or the like, may include, but is not limited to, operating systems such as Linux system, Unix system, Windows series system (e.g., Windows xp, Windows 7, etc.), Mac OS X system (operating system of apple computer), and the like. The operating system of the electronic device at the mobile end, such as a smart phone, may include, but is not limited to, an operating system such as an android system, an IOS (operating system of an apple mobile phone), a Window system, and the like.

The server is used for providing services for the electronic equipment. The electronic device in the embodiment of the application can install and run the application program, and the server can be a server corresponding to the application program installed in the electronic device and provide application service for the application program. The application program may be a separately integrated application program, or an applet embedded in another application, or an operating platform in the form of a web page, and the like, which is not limited herein. In the embodiment of the present application, an application program corresponding to a server and an electronic device is referred to as a target application. The target application may be any application related to insurance services, and is not limited herein. The number of the electronic devices and the number of the servers are not limited in the embodiment of the application, and the servers can provide services for the electronic devices at the same time. The server may be implemented as a stand-alone server or as a server cluster of multiple servers.

In the embodiment of the application, the electronic device or the server may store, in advance, social information that can be obtained in an application authorized by the user, where the social information may be understood as shared information that is disclosed to friends or strangers in a social network by the user, and is similar to a microblog or a circle of friends in a WeChat, and the social information may include a photo, a video, a text, an audio, and the like, which is not limited herein.

The social information may be understood as information generated by the user in the social network, such as consumption information, credit information, professional information, interest information, and the like. The consumption information may include payment information of a user performing a payment operation in an application or by using a third-party application, for example, a payment amount, a payment account, a collection account, a payment method, and the like.

The credit information may include loan information of a loan operation performed by the user at the application or a third-party application or other user, such as the amount of the loan, the time of the loan, the mortgage assets, the probability of overdue, the time of overdue, the payment method, and the like.

The career information may include information related to work such as the user's career, job title, type of career, work unit, payroll level, technical field, and the like.

The interest information may include information tagged by the user as being of interest or concern in the application, may also include information derived from information frequently viewed by the user (e.g., web pages, games, video, audio, etc.), or may be information derived from professional information, consumer information, and credit information. It can be understood that the social information can reflect the information concerned by the user to a certain extent, and the accuracy of analyzing the insurance interested by the user can be improved conveniently by analyzing the interest information in the social information. The social information, the interest information, the consumption information, the credit information and the occupation information are not limited, and the interest information, the consumption information, the credit information and the occupation information can be obtained through shared information in the social information.

In the embodiment of the application, the electronic device or the server may store a knowledge graph for describing the association relationship of each object in the social network in advance. The knowledge graph is a structural information organization mode based on semantics, describes concepts and mutual relations in a physical world in a symbolic form, and the basic composition units of the knowledge graph are entity-relation-entity triple and entities and related attribute-value pairs thereof, and the entities are mutually connected through relations to form a network knowledge structure. Through the knowledge graph, business data can realize the conversion from information to knowledge, and is particularly suitable for organizing large-scale and strongly related business concept entities.

The method for establishing the knowledge graph is not limited, and the basic information of a plurality of users can be collected and then analyzed to obtain the associated images corresponding to the users. In one possible example, the method of establishing a knowledge-graph includes the following steps A1-A4, wherein:

a1: searching a target webpage to obtain at least one first object and a first keyword corresponding to the first object.

The target webpage may be a webpage of a target application, may also be any search application, or any insurance-related application, and the like, and the target webpage is not limited in the present application. It should be noted that the target web page may include one or more web pages.

The first object may target a user involved in the web page. The first keyword may include characteristic information of the first object, for example, basic information such as name, age, address, work unit, academic calendar, etc., may also include interest characteristics of the user, for example, sports, music, etc., and may also include physical characteristics of the user, for example, genetic medical history, physical examination report, etc. The first keyword may be a word of the first object in the target webpage, or may be a word obtained according to information of the first object in the target webpage. The first keyword includes the characteristics of the first object and the characteristics of the associated object having an association relationship, and also includes an event reason, an event name, an event result, and the like of the event corresponding to the first object. It should be noted that the number of the first objects may be one or more, the first keyword may be one or more keywords corresponding to one first object, or may be one or more keywords corresponding to multiple first objects, which is not limited herein.

The method for searching the target webpage is not limited, and a crawler technology can be adopted for searching. The crawler technology is also called web crawler, web spider, web robot, or web chaser, and is a program or script that automatically captures network information according to certain rules. Specifically, the search dimensionality may be determined according to experience or information in a reference website (e.g., a social question and answer platform, a vertical domain dictionary, etc.), an initial vocabulary is determined according to each dimensionality, and a web crawler search is performed based on the initial vocabulary to obtain a first object and a plurality of first keywords corresponding to the first object. It should be noted that, when the number of searches exceeds a preset value, or the time of the search exceeds a preset time, the step of searching for the first object or the first keyword may be ended.

A2: and processing the first keywords to obtain at least two second keywords.

The second keyword is a word obtained by processing the first keyword, and the processing method may be merging the first keyword, expanding the first keyword, and the like. It should be noted that the number of the second keywords is at least two, that is, there are a plurality of second keywords. It can be understood that, when the objects in the social network correspond to a plurality of keywords, the social network relationship model may be constructed according to the relationship between the keywords and the relationship between the objects. The social network relationship model may be understood as a knowledge graph.

In one possible example, step A2 includes the following steps A21-A25, wherein:

a21: and searching the event information corresponding to the first object according to the first keyword.

The event information may be hot news in a target webpage or other applications, or social information that can be obtained by the first object, and the like, which is not limited herein. The hot news can be determined according to the click rate in the webpage or the application and the grade of the news. The click rate refers to the number of news viewed by the net friends and can be used for describing the attention degree of the net friends to the news. The news grade can be determined according to the influence and coverage of news events, or the type or field of news. Compared with the common news, the hot news can reflect the attention points of the net friends better, has certain timeliness, and can improve the coverage of the first keyword based on the updating of the first keyword. Compared with the information in the target webpage, the social information can better reflect the working and living attitudes of the first object, the first keyword is updated based on the social information, the coverage range of the first keyword can be improved, and comprehensiveness of the knowledge graph is improved conveniently.

The method for searching the event information is not limited, web crawler technology can be adopted for searching, weights can be set for different first keywords in advance, and then web crawler searching is carried out according to the weights of the first keywords. It can be understood that the search is performed based on different weights, so that the accuracy of the search can be further improved, and the search efficiency is improved conveniently.

It should be noted that, the event information corresponding to the first object is searched according to the first keyword, the search may be performed according to the first keyword corresponding to each first object, or the search may be performed according to the first keywords corresponding to a plurality of first objects, which is not limited herein.

A22: and acquiring a third key word corresponding to the first object according to the event information.

And the third keyword is a keyword corresponding to the first object in the event information. The third keyword may correspond to one or more first objects, may be the same as or similar to the first keyword, or may be different from the first keyword, and is not limited herein. The third key word can be obtained according to dimensions such as an event reason, an event name, an event result and the like in the event information, the method for obtaining the third key word is not limited, and the number of the third key word is not limited and can be one or more.

A23: and selecting a fourth keyword different from the first keyword from the third keyword.

The fourth keyword is a keyword in the third keyword that is different from the first keyword, that is, the third keyword except the fourth keyword is at least the same as one of the first keywords.

A24: and when a fifth keyword in the first keyword and the fourth keyword is similar to a sixth keyword in the first keyword and the fourth keyword, combining the fifth keyword and the sixth keyword to obtain a seventh keyword.

The fifth keyword may be any one of the first keyword and the fourth keyword, and when one of the first keyword and the fourth keyword is similar to the fifth keyword, the keyword is determined to be the sixth keyword. The method for judging whether the fifth keyword and the sixth keyword are similar is not limited, the similarity value between the keywords can be obtained, when the similarity value between the two keywords is larger than a preset threshold value, the two keywords are determined to be similar, and the two keywords are the fifth keyword and the sixth keyword respectively.

The seventh keyword is a word obtained by combining the fifth keyword and the sixth keyword, and may be one of the fifth keyword and the sixth keyword, or may be a unified word corresponding to the fifth keyword and the sixth keyword. It can be understood that the keywords searched from different sources are different, and similar keywords are combined, so that the keywords can be simplified, and the efficiency of subsequent search can be improved conveniently. And similar keywords are combined, so that the normalization of the vocabulary in the knowledge graph can be improved.

A25: combining keywords except the fifth keyword and the sixth keyword in the first keyword and the fourth keyword with the seventh keyword to obtain at least two second keywords.

It is understood that, in steps a 21-a 25, the event information corresponding to at least one first object is searched for according to the first keyword, and then the third keyword corresponding to the first object is obtained according to the event information. And finally, combining keywords except the fifth keyword and the sixth keyword in the first keyword and the fourth keyword with the seventh keyword to obtain at least two second keywords. That is, on the basis of the original first keyword, a new third keyword corresponding to the first object is searched according to the time information obtained by the first keyword search. The original first keywords and the similar keywords in the newly searched third keywords are combined, and the rest keywords are combined to obtain the second keywords, so that the accuracy of obtaining the second keywords is improved, the vocabularies in the knowledge graph are increased, and the comprehensiveness of the knowledge graph is improved conveniently.

A3: and acquiring the association relation between the first objects.

The association relationship may be a spouse, a child, a parent, a brother, a friend, a colleague, etc. The association between the first objects may include an association between one of the first objects and another of the first objects. For example, the first object includes object 1, object 2 and object 3, where object 1 and object 2 are a couple relationship and object 2 and object 3 are a sister relationship, and the association relationship between the first object includes a couple relationship between object 1 and object 2 and a sister relationship between object 2 and object 3. The association relationship may be determined by event information, or may be determined by social information of the first object, and the like, which is not limited herein.

A4: and establishing a knowledge graph according to the incidence relation and the second key words.

It can be understood that, in steps a 1-a 4, the target web page is searched to obtain at least one first object and a first keyword corresponding to the first object, and then the first keyword is processed to obtain at least two second keywords, so that the coverage of obtaining the keywords is improved. And then, acquiring the incidence relation between the first objects, and establishing a knowledge graph according to the incidence relation and the second key words, so that the coverage rate of the knowledge graph is improved, and the accuracy rate of analyzing the user characteristics based on the knowledge graph is improved.

The social information and knowledge graph described above may also be stored in a tile created on the tile chain network. The blockchain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, a consensus mechanism and an encryption algorithm. A block chain (Blockchain), which is essentially a decentralized database, is a series of data blocks associated by using a cryptographic method, and each data block contains information of a batch of network transactions, so as to verify the validity (anti-counterfeiting) of the information and generate a next block. The blockchain may include a blockchain underlying platform, a platform product services layer, and an application services layer. Therefore, data are stored in a distributed mode through the block chain, data security is guaranteed, and meanwhile data sharing of information among different platforms can be achieved.

The information pushing method provided by the embodiment of the application can be executed by an information pushing device, wherein the device can be realized by software and/or hardware, and can be generally integrated in electronic equipment or a server, so that the pushing accuracy can be improved.

Referring to fig. 1, fig. 1 is a schematic flow chart of an information pushing method provided in the present application. The method comprises the following steps S101 to S105, wherein:

s101: and acquiring the target social information of the target object according to the authorization information of the target object.

In the embodiment of the present application, when the method is executed by a server, the target object may be any user, or a user who registers information in an application related to insurance business or a target application, or a user who browses insurance information, or the like. When the method is executed by an electronic device, the target object may be a user corresponding to the electronic device, the user may be a user logged in a system or a target application of the electronic device, or may be a specified user input in the target application, or the like. The target object is not limited in the present application, and the target application may refer to the foregoing description, which is not described herein again.

The authorization information includes authority information of at least one application that the user is allowed to access, and may be understood as being accessed by a third-party application or by a server to access the third-party application. For example, the electronic device includes a first application, a second application, and a third application, and when the authorization information includes the first application and the second application, the target social information of the target object in the first application and the second application may be obtained.

The target social information may be understood as social information that can be obtained by the electronic device or the server through authorization information of the target object. The type of the target social information may include shared information uploaded by the target object, interest information, consumption information, credit information, professional information, and the like, which are not described herein again. It should be noted that the target social information may include one or more pieces of social information.

S102: and determining an associated object associated with the target object and the target object characteristic of the target object according to the target social information.

In the embodiment of the application, the associated object is associated with the target object, and the associated object can be used as a reference object for the target object to purchase insurance, for example, the associated object is a colleague or a friend of the target object, and insurance that the target object may purchase is determined according to the insurance purchased by the associated object. The associated object may alternatively be a target object for purchasing an insured in the insurance, e.g., the associated object is a family member of the target object, to which the insurance that the family member of the target object may purchase may be pushed. The method for determining the associated object is not limited in the present application, and in a possible example, the determining the associated object associated with the target object according to the target social information includes the following steps B1 to B3, where:

b1: identifying a second object involved in the target social information.

The second object is an object related to the target social information, which is other than the target object, and may be an object directly depicted in the target social information or an object included in the target social information, for example, the target social information is a picture or a video, and the second object may be a person appearing in the picture or the video. It is understood that the name of the person involved in the target social information may be an alias name such as a small name or nickname, and the identity of the second object and the formal name, for example, the name in the identification card, may be determined from the address book or other pre-stored database of the target object. When the second object involved in the target social information is a person image, the identity of the second object may be determined by the image library of the target object.

B2: and acquiring an association value between the target object and the second object according to the target social information.

The association value is used for describing the degree of association between the target object and the second object, and may be determined by the association relationship between the target object and the second object and/or the number of times that the second object appears in the target social information.

B3: when the association value is greater than or equal to a first threshold value, determining that the second object is an associated object associated with the target object.

The first threshold is not limited in the present application, and may be set according to the number of the second objects, and the like.

It can be understood that, in steps B1 to B3, the second object user related to the target social information is identified, the association value between the target object and the second object is obtained according to the target social information, and the second object with the association value greater than or equal to the first threshold is selected as the association object associated with the target object, so that the accuracy of determining the association object can be improved, and the effectiveness of recommendation can be improved.

It should be noted that the associated object may be an article such as a vehicle, and the type of the associated object is not limited in the present application.

In the embodiment of the present application, the target object feature is used to describe a feature of the target object, and may include a consumption feature, an interest feature, a social feature, a credit feature, an occupation feature, and the like. The method for acquiring the target object features is not limited, corresponding features can be acquired based on corresponding dimensions of consumption, interest, social contact, credit and occupation, and consumption features, interest features and the like of the target object can be acquired based on consumption information, interest information, social contact information, credit information and occupation information.

S103: and acquiring the associated object characteristics of the associated object.

The associated object features may refer to the description of the target object features, and are not described herein again. The method for acquiring the characteristics of the associated object is not limited, and when the associated object is a person, the associated object can be acquired based on dimensions corresponding to consumption, interest, credit and occupation of the associated object. When the associated object is an item, the item parameter may be obtained based on the item parameter of the associated object, and the item parameter may include an item value, a usage time, a usage life, or a characteristic of an owner.

Step S103 includes the following three embodiments, among which:

in a first implementation manner, first social information of the associated object is acquired according to authorization information of the associated object; and acquiring the associated object characteristics of the associated object according to the first social information.

The first social information is the social information that can be obtained by the electronic device or the server through the authorization information of the associated object, and may refer to the description of the target social information, which is not described herein again. It can be understood that if the first social information of the associated object can be obtained according to the authorization information of the associated object, the associated object feature of the associated object can be obtained according to the first social information, and the accuracy of obtaining the associated object feature can be improved.

In a second implementation manner, second social information corresponding to the associated object is obtained from the target social information; and acquiring the associated object characteristics of the associated object according to the second social information.

And the second social information is the social information of the target social information and the associated object. It can be understood that the associated object feature is obtained according to the second social contact information corresponding to the associated object in the target social contact information, so that the efficiency of obtaining the second social contact information can be improved, and the success rate of obtaining the associated object feature is improved.

In a third embodiment, extracting a target keyword of the associated object from the target social information; and inputting the target key words into the knowledge graph to obtain the associated object characteristics of the associated object.

The target keywords may include names, ages, addresses, work units, academic calendars, and the like of the associated objects. The knowledge graph can be referred to above, and is not described in detail here. It can be understood that the target keywords of the associated object in the target social information are input into the knowledge graph to obtain the associated object features of the associated object, so that the efficiency of analyzing the associated object features and the success rate of obtaining the associated object features can be improved.

S104: and determining target insurance according to the target object characteristics and the associated object characteristics.

In an embodiment of the present application, the target insurance may be an insurance product recommended to the target object for purchase by the associated object. It can be understood that the target object characteristics and the associated object characteristics respectively describe characteristics of the target object and the associated object, and the target insurance determined according to the target object characteristics and the associated object characteristics is pushed to the target object, so that the success rate of purchasing insurance for the associated object by the target object can be improved.

The present application is not limited to the method for determining the target insurance, and in one possible example, the step S104 includes the following steps C1 to C3, wherein:

c1: searching for a first insurance corresponding to the associated object feature.

The first insurance corresponds to the associated object feature, and may be understood as an insurance suitable for purchase by the associated object, for example, if the associated object is a child of the target object, the target insurance may be a juvenile insurance.

C2: and acquiring a first purchase probability of the first insurance according to the target object characteristics.

The first purchase probability is used for describing the probability that the target object purchases the first insurance for the associated object. The method for obtaining the first purchase probability is not limited in the present application, and in one possible example, the target object characteristics include interest characteristics and consumption characteristics, and the step C2 includes the following steps C21 to C23, wherein:

c21: and acquiring the interest value of the target object for the first insurance according to the interest characteristics.

Wherein the interest feature is usable to determine whether the target object is interested in purchasing the first insurance. The interest features may be obtained according to dimensions based on the interest features, such as sharing information, consumption information, credit information, occupation information, and the like in the target social information, and the like, which is not limited herein. It can be understood that the interest value of the target object corresponding to the first insurance is obtained according to the interest feature, so that the success rate of analyzing the target object to purchase the first insurance can be improved, and the success rate of pushing is improved conveniently.

C22: and acquiring the payment probability of the target object for the first insurance according to the consumption characteristics.

The consumption characteristics may be used to determine whether the target object may purchase insurance, and the consumption characteristics may be obtained according to dimensions based on the consumption characteristics, such as sharing information, consumption information, credit information, and professional information, in the target social information, and the like, which are not limited herein. It can be understood that the payment probability of the target object corresponding to the first insurance is obtained according to the consumption characteristics, so that the success rate of analyzing the target object to purchase the first insurance can be improved, and the success rate of pushing is convenient to improve.

C23: and acquiring a first purchase probability of the first insurance according to the interest value and the payment probability.

The first purchase probability may be a weighted average of the interest value and the payment probability, or may be a maximum value or a minimum value corresponding to the interest value and the payment probability, and the method for obtaining the first purchase probability by the interest value and the payment probability is not limited in the present application.

It can be understood that, in steps C21 to C23, the interest value and the payment probability of the target object for the first insurance are obtained according to the interest feature and the consumption feature, and then the first purchase probability of the first insurance is obtained according to the interest value and the payment probability, so that the consumption feature and the interest feature of the target object are considered, the accuracy of obtaining the first purchase probability is improved, and the success rate of pushing is improved.

C3: determining that the first insurance is a target insurance for the associated object when the first purchase probability is greater than or equal to a second threshold.

The second threshold is not limited in the present application, and may be set according to the consumption characteristics of the target object.

It is understood that, in steps C1-C3, the first insurance corresponding to the associated object feature is searched, and the first purchase probability of the first insurance is obtained according to the target object feature of the target object. When the first purchase probability is greater than or equal to the second threshold, the first insurance is determined to be the target insurance. That is, the target insurance determined according to the target object characteristics and the associated object characteristics can be pushed to the target object, and the success rate of purchasing insurance for the associated object by the target object is improved.

In the embodiment of the present application, the target insurance may alternatively be an insurance product recommended for purchase by the target object. In one possible example, step S104 includes the following steps D1-D4, wherein:

d1: and acquiring a second insurance purchased by the associated object.

The second insurance may be purchased by the associated object itself, or purchased by a family member or an article, which is not limited herein. It should be noted that the number of the second insurance may be one or more.

D2: and acquiring a similarity value between the target object characteristic and the associated object characteristic.

The similarity value is used for describing the similarity degree between the target object feature and the associated object feature, and can be obtained by comparing feature information of each dimension.

D3: and acquiring a second purchase probability of the second insurance according to the target object characteristics and the similar value.

The second purchase probability can refer to the description of the first purchase probability, and is not described herein again. And acquiring a second purchase probability of the second insurance according to the target object characteristic and the similarity value, wherein the second purchase probability is acquired according to the target object characteristic on the basis of the similarity value, so that the accuracy of acquiring the second purchase probability is improved, and the accuracy of determining the target insurance is improved.

D4: determining that the second insurance is a target insurance when the second purchase probability is greater than or equal to a third threshold.

The third threshold is not limited in the present application, and the number of the second fuses may be determined.

It is understood that, in steps D1-D4, the second insurance purchased by the associated object is obtained, the second probability of purchasing the second insurance by the target object is obtained according to the similarity value between the target object feature and the associated object feature of the target object and the target object feature, and when the second probability of purchasing is greater than or equal to the third threshold value, the second insurance is determined as the insurance purchasable by the target object, which facilitates to improve the pushing efficiency. And the insurance is pushed to the target object according to the insurance purchased by the object associated with the user, so that the pushing efficiency can be improved.

S105: and sending the push information of the target insurance to the target object.

In the embodiment of the application, the pushed information of the target insurance may be product information of the target insurance, or product information corresponding to the associated object in the target insurance, and the like, so that the recommendation effect can be improved. The push information may be described in the form of text, image or video, and is not limited herein. When the method is executed by the server, the push information of the target insurance can be sent to the target object according to the contact way of the target object, and the contact way of the target object may be a device identifier of the electronic device pre-stored by the target object or an electronic mailbox, a telephone number and the like of the target object, which is not limited herein. When the method is executed by the electronic equipment and the user non-target object of the target application is logged in the electronic equipment, the push information of the target insurance can be sent to the target object according to the contact way of the target object. When the method is executed by the electronic equipment and the user logging in the target application in the electronic equipment is the target object, the push information of the target insurance is sent to the target object, and the push information of the target insurance can be understood to be displayed in the electronic equipment.

It can be understood that, in steps S101 to S105, the target social information of the target object is obtained according to the authorization information of the target object, and then the associated object associated with the target object and the target object feature of the target object are determined according to the target social information, so that the accuracy of determining the associated object and the target object feature is improved. And then, acquiring the associated object characteristics of the associated object, determining the target insurance according to the target object characteristics and the associated object characteristics, and sending push information of the target insurance to the target object. That is, the insurance pushed to the target object is the insurance related to the target object feature and the associated object feature, which improves the accuracy of pushing.

The method of the embodiments of the present application is set forth above in detail and the apparatus of the embodiments of the present application is provided below.

Referring to fig. 2, fig. 2 is a schematic structural diagram of an information pushing apparatus according to the present application, and as shown in fig. 2, the information pushing apparatus 200 includes:

the processing unit 201 is configured to obtain target social information of a target object according to authorization information of the target object; determining an associated object associated with the target object and a target object characteristic of the target object according to the target social information; acquiring the associated object characteristics of the associated object; determining target insurance according to the target object characteristics and the associated object characteristics;

a communication unit 202, configured to send push information of the target insurance to the target object.

In a possible example, the processing unit 201 is further configured to search a target webpage to obtain at least one first object and a first keyword corresponding to the first object; processing the first keywords to obtain at least two second keywords; acquiring an incidence relation between the first objects; and establishing a knowledge graph according to the incidence relation and the second key words.

In one possible example, the processing unit 201 is specifically configured to extract a target keyword of the associated object from the target social information; and inputting the target key words into the knowledge graph to obtain the associated object characteristics of the associated object.

In a possible example, the processing unit 201 is specifically configured to search, according to the first keyword, event information corresponding to the first object; acquiring a third keyword corresponding to the first object according to the event information; selecting a fourth keyword different from the first keyword from the third keyword; when a fifth keyword in the first keyword and the fourth keyword is similar to a sixth keyword in the first keyword and the fourth keyword, combining the fifth keyword and the sixth keyword to obtain a seventh keyword; combining keywords except the fifth keyword and the sixth keyword in the first keyword and the fourth keyword with the seventh keyword to obtain at least two second keywords.

In one possible example, the processing unit 201 is specifically configured to identify a second object involved in the target social information; acquiring an association value between the target object and the second object according to the target social information; when the association value is greater than or equal to a first threshold value, determining that the second object is an associated object associated with the target object.

In one possible example, the processing unit 201 is specifically configured to search for a first insurance corresponding to the associated object feature; acquiring a first purchase probability of the first insurance according to the target object characteristics; determining that the first insurance is a target insurance for the associated object when the first purchase probability is greater than or equal to a second threshold.

In one possible example, the target object characteristics include an interest characteristic and a consumption characteristic, and the processing unit 201 is specifically configured to obtain, according to the interest characteristic, an interest value of the target object for the first insurance; acquiring the payment probability of the target object for the first insurance according to the consumption characteristics; and acquiring a first purchase probability of the first insurance according to the interest value and the payment probability.

In a possible example, the processing unit 201 is specifically configured to obtain a second insurance purchased by the associated object; acquiring a similarity value between the target object characteristic and the associated object characteristic; acquiring a second purchase probability of the second insurance according to the target object characteristics and the similar value; determining that the second insurance is a target insurance when the second purchase probability is greater than or equal to a third threshold.

For detailed processes executed by each unit in the information pushing apparatus 200, reference may be made to the execution steps in the foregoing method embodiments, which are not described herein again.

Referring to fig. 3, fig. 3 is a schematic structural diagram of another information pushing apparatus according to an embodiment of the present application, where the information pushing apparatus is a server corresponding to an electronic device or an information pushing application. As shown in fig. 3, the information pushing apparatus 300 includes a processor 310, a memory 320, a communication interface 330, and one or more programs 340. The related functions implemented by the communication unit 202 shown in fig. 2 can be implemented by the communication interface 330, and the related functions implemented by the processing unit 201 shown in fig. 2 can be implemented by the processor 310.

The one or more programs 340 are stored in the memory 320 and configured to be executed by the processor 310, the programs 340 including instructions for:

acquiring the associated object characteristics of the associated object;

and sending the push information of the target insurance to the target object.

In one possible example, before the obtaining the associated object feature of the associated object, the program 340 is further configured to execute the following steps:

searching a target webpage to obtain at least one first object and a first keyword corresponding to the first object;

processing the first keywords to obtain at least two second keywords;

acquiring an incidence relation between the first objects;

and establishing a knowledge graph according to the incidence relation and the second key words.

In one possible example, in the aspect of obtaining the associated object feature of the associated object, the program 340 is specifically configured to execute the following steps:

extracting a target keyword of the associated object from the target social information;

and inputting the target key words into the knowledge graph to obtain the associated object characteristics of the associated object.

In one possible example, in the aspect of processing the first keyword to obtain at least two second keywords, the program 340 is specifically configured to execute the following steps:

searching event information corresponding to the first object according to the first keyword;

acquiring a third keyword corresponding to the first object according to the event information;

selecting a fourth keyword different from the first keyword from the third keyword;

when a fifth keyword in the first keyword and the fourth keyword is similar to a sixth keyword in the first keyword and the fourth keyword, combining the fifth keyword and the sixth keyword to obtain a seventh keyword;

combining keywords except the fifth keyword and the sixth keyword in the first keyword and the fourth keyword with the seventh keyword to obtain at least two second keywords.

In one possible example, in the aspect of determining the associated object associated with the target object according to the target social information, the program 340 is specifically configured to execute the following steps:

identifying a second object involved in the target social information;

acquiring an association value between the target object and the second object according to the target social information;

when the association value is greater than or equal to a first threshold value, determining that the second object is an associated object associated with the target object.

In one possible example, in the aspect of determining a target insurance based on the target object characteristics and the associated object characteristics, the program 340 is specifically configured to execute the following steps:

searching for a first insurance corresponding to the associated object feature;

acquiring a first purchase probability of the first insurance according to the target object characteristics;

determining that the first insurance is a target insurance for the associated object when the first purchase probability is greater than or equal to a second threshold.

In one possible example, the target object characteristics include interest characteristics and consumption characteristics, and the program 340 is specifically configured to execute the following steps in the obtaining of the first purchase probability of the first insurance based on the target object characteristics:

obtaining an interest value of the target object for the first insurance according to the interest feature;

acquiring the payment probability of the target object for the first insurance according to the consumption characteristics;

and acquiring a first purchase probability of the first insurance according to the interest value and the payment probability.

acquiring a second insurance purchased by the associated object;

acquiring a similarity value between the target object characteristic and the associated object characteristic;

acquiring a second purchase probability of the second insurance according to the target object characteristics and the similar value;

determining that the second insurance is a target insurance when the second purchase probability is greater than or equal to a third threshold.

Embodiments of the present application also provide a computer storage medium, where the computer storage medium stores a computer program for causing a computer to execute to implement part or all of the steps of any one of the methods described in the method embodiments, and the computer includes an electronic device and a server.

Embodiments of the application also provide a computer program product comprising a non-transitory computer readable storage medium storing a computer program operable to cause a computer to perform to implement some or all of the steps of any of the methods recited in the method embodiments. The computer program product may be a software installation package, the computer comprising an electronic device and a server.

It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present application is not limited by the order of acts described, as some steps may occur in other orders or concurrently depending on the application. Further, those skilled in the art will also appreciate that the embodiments described in this specification are presently preferred and that no particular act or mode of operation is required in the present application.

In the foregoing embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.

In the embodiments provided in the present application, it should be understood that the disclosed apparatus may be implemented in other manners. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, a division of a unit is merely a logical division, and an actual implementation may have another division, for example, at least one unit or component may be combined or integrated with another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of some interfaces, devices or units, and may be an electric or other form.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may also be distributed on at least one network unit. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a hardware mode or a software program mode.

The integrated unit, if implemented in the form of a software program module and sold or used as a stand-alone product, may be stored in a computer readable memory. With such an understanding, the technical solution of the present application may be embodied in the form of a software product, which is stored in a memory and includes several instructions for causing a computer device (which may be a personal computer, a server, a network device, or the like) to perform all or part of the steps of the method according to the embodiments of the present application. And the aforementioned memory comprises: various media capable of storing program codes, such as a usb disk, a read-only memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and the like.

Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by associated hardware instructed by a program, which may be stored in a computer-readable memory, which may include: flash disk, ROM, RAM, magnetic or optical disk, and the like.

The foregoing detailed description of the embodiments of the present application has been presented to illustrate the principles and implementations of the present application, and the above description of the embodiments is only provided to help understand the method and the core concept of the present application; meanwhile, for a person skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.

Claims

1. An information pushing method, comprising:

acquiring the associated object characteristics of the associated object;

and sending the push information of the target insurance to the target object.

2. The method of claim 1, wherein prior to said obtaining the associated object feature of the associated object, the method further comprises:

processing the first keywords to obtain at least two second keywords;

acquiring an incidence relation between the first objects;

establishing a knowledge graph according to the incidence relation and the second key words;

the acquiring of the associated object feature of the associated object includes:

3. The method of claim 2, wherein the processing the first keyword to obtain at least two second keywords comprises:

4. The method according to any one of claims 1-3, wherein the determining the associated object associated with the target object according to the target social information comprises:

identifying a second object involved in the target social information;

5. The method according to any one of claims 1-3, wherein said determining a target insurance based on said target object characteristics and said associated object characteristics comprises:

searching for a first insurance corresponding to the associated object feature;

determining that the first insurance is a target insurance when the first purchase probability is greater than or equal to a second threshold.

6. The method of claim 5, wherein the target object features comprise interest features and consumption features, and wherein obtaining the first purchase probability of the first insurance based on the target object features comprises:

7. The method according to any one of claims 1-3, wherein said determining a target insurance based on said target object characteristics and said associated object characteristics comprises:

acquiring a second insurance purchased by the associated object;

8. An information pushing apparatus, comprising:

9. An information pushing apparatus comprising a processor, a memory, a communication interface, and one or at least one program, wherein the one or at least one program is stored in the memory and configured to be executed by the processor, the program comprising instructions for performing the steps in the method of any one of claims 1-7.

10. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program, the computer program causing a computer to execute to implement the method of any one of claims 1-7.