Resource recommendation method and device

Abstract

The present disclosure provides a resource recommendation method, which can be applied to the field of computer technology. The resource recommendation method includes: in response to an insurance product recommendation request for recommending insurance products to family members in a family, obtaining historical insurance product purchase information associated with at least one family member in the family, wherein the historical insurance product purchase information includes family member information in the family, and the family member information includes health risk information; generating a genetic map based on the historical insurance product purchase information; obtaining description information of the family, wherein the description information represents the purchasing power of the family for insurance products; and generating an insurance product recommendation result for recommending insurance products to family members in the family based on the genetic map and the description information. The present disclosure also provides a resource recommendation device, equipment, storage medium and program product.

Description

Technical Field

[0001] The present disclosure relates to the field of computer technology, and more particularly to a data processing method, apparatus, device, medium, and program product. Background Art

[0002] With the development of society and the improvement of people's living standards, users' demand for insurance products has gradually increased.

[0003] Insurance product recommendation technology in related technologies is usually individual-oriented. After users answer some questions online, insurance products are recommended to users based on factors such as their financial risks, travel risks, and health risks.

[0004] In the process of realizing the concept disclosed herein, the inventors discovered that since the insurance product recommendation technology in the related art relies on user data obtained from online questions and answers, there is a technical problem of inaccurate recommendation results, and the related art lacks a family-oriented insurance product recommendation technology. Summary of the Invention

[0005] In view of the above problems, the present disclosure provides a resource recommendation method, apparatus, device, medium and program product.

[0006] According to a first aspect of the present disclosure, a resource recommendation method is provided, comprising:

[0007] In response to an insurance product recommendation request for recommending an insurance product for a family member, obtaining historical insurance product purchase information associated with at least one family member of the family, wherein the historical insurance product purchase information includes family member information of the family, and the family member information includes health risk information;

[0008] Generate a genetic map based on the above historical insurance product purchase information;

[0009] Obtaining descriptive information of the household, wherein the descriptive information represents the household's purchasing power for insurance products; and

[0010] An insurance product recommendation result is generated based on the genetic map and the description information for recommending insurance products to family members in the family.

[0011] According to an embodiment of the present disclosure, the family member information includes family members in the family and the relationship between the family members;

[0012] The above-mentioned generation of a genetic map based on the above-mentioned historical insurance product purchase information includes:

[0013] Generating a kinship graph based on the family member information, wherein the kinship graph includes at least two nodes connected by an edge, the nodes representing family members in the family, and the edges representing relationships between the family members;

[0014] At least one genetic map is generated based on the kinship map and the health risk information, wherein the genetic map is associated with at least one genetic disease.

[0015] According to an embodiment of the present disclosure, the above-mentioned historical insurance product purchases also include historical insurance product information;

[0016] The above method further includes:

[0017] Generating a plurality of insurance categories based on the historical insurance product information, wherein each insurance category represents insurance information for at least one insurance product;

[0018] According to the preset rules, the minimum insurance standard and the optimal insurance standard are determined from each of the above insurance categories.

[0019] According to an embodiment of the present disclosure, the above method further includes:

[0020] Generate the basic premium for each family member in the above family based on the above description information;

[0021] Recommended insurance information for at least one insurance product for each family member is generated based on the basic premium of each family member and the genetic map.

[0022] According to an embodiment of the present disclosure, the above-mentioned description information includes the total income, expenditure ratio, loan amount and loan term of the above-mentioned family;

[0023] The basic premium for each family member in the above family generated based on the above description information includes:

[0024] Generate the basic insurance premium for the above-mentioned family based on the above-mentioned total income, the above-mentioned expenditure ratio, the above-mentioned loan amount and the above-mentioned loan term;

[0025] Based on the number and age of family members in the above family, generate the premium ratio corresponding to each family member;

[0026] The basic premium for each family member is generated based on each of the above premium proportions and the basic premium of the above family.

[0027] According to an embodiment of the present disclosure, generating recommended insurance information for at least one insurance product for each family member based on the basic premium of each family member and the pending information includes:

[0028] Determining the risk level of the family members for developing a genetic disease based on at least one of the genetic profiles;

[0029] Determine the set of insurance products to be insured based on the above risk levels;

[0030] Based on the above minimum insurance standard, the above optimal insurance standard, and the basic premium of the above family, recommended insurance information for at least one insurance product in the above set of insurance products to be insured is generated.

[0031] A second aspect of the present disclosure provides a resource recommendation device, comprising:

[0032] a first acquisition module configured to, in response to an insurance product recommendation request for recommending an insurance product for a family member, acquire historical insurance product purchase information associated with at least one family member of the family, wherein the historical insurance product purchase information includes family member information of the family, and the family member information includes health risk information;

[0033] A first generating module is configured to generate a genetic map based on the historical insurance product purchase information; and

[0034] A second acquisition module is configured to acquire descriptive information of the family, wherein the descriptive information represents the purchasing power of the family for insurance products;

[0035] The second generating module is used to generate an insurance product recommendation result for recommending insurance products to family members in the family according to the genetic map and the description information.

[0036] A third aspect of the present disclosure provides an electronic device, comprising: one or more processors; and a memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors execute the resource recommendation method.

[0037] A fourth aspect of the present disclosure further provides a computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, causes the processor to execute the above-mentioned resource recommendation method.

[0038] A fifth aspect of the present disclosure further provides a computer program product, including a computer program, which implements the above-mentioned resource recommendation method when executed by a processor. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] The above contents and other objects, features and advantages of the present disclosure will become more apparent through the following description of the embodiments of the present disclosure with reference to the accompanying drawings, in which:

[0040] Figure 1A diagram schematically illustrates an application scenario of the resource recommendation method, apparatus, device, medium, and program product according to an embodiment of the present disclosure;

[0041] Figure 2 The following schematically shows a flow chart of a resource recommendation method according to an embodiment of the present disclosure;

[0042] Figure 3 Schematically illustrates a flow chart for generating a genetic map based on historical insurance product purchase information according to an embodiment of the present disclosure;

[0043] Figure 4 Schematically shows a schematic diagram of a genetic map according to an embodiment of the present disclosure;

[0044] Figure 5 Schematically shows a flow chart of a resource recommendation method according to another embodiment of the present disclosure;

[0045] Figure 6 Schematically shows a flow chart of a resource recommendation method according to another embodiment of the present disclosure;

[0046] Figure 7 Schematically illustrates a flow chart for generating a basic premium for each family member in a family based on description information according to an embodiment of the present disclosure;

[0047] Figure 8 Schematically illustrates a flow chart for generating a basic premium for each family member in a family based on description information according to an embodiment of the present disclosure;

[0048] Figure 9 Schematically shows a structural block diagram of a resource recommendation device according to an embodiment of the present disclosure; and

[0049] Figure 10 The block diagram schematically shows an electronic device suitable for implementing the resource recommendation method according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0050] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are merely exemplary and are not intended to limit the scope of the present disclosure. In the detailed description below, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of the embodiments of the present disclosure. However, it is apparent that one or more embodiments may also be implemented without these specific details. In addition, in the following description, descriptions of well-known structures and technologies are omitted to avoid unnecessary confusion of the concepts of the present disclosure.

[0051] The terms used herein are only for describing specific embodiments and are not intended to limit the present disclosure. The terms "comprise," "include," etc. used herein indicate the presence of the features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0052] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification and should not be interpreted in an idealized or overly rigid manner.

[0053] When expressions such as "at least one of A, B and C, etc." are used, they should generally be interpreted in accordance with the meaning of the expression commonly understood by those skilled in the art (for example, "a system having at least one of A, B and C" should include but is not limited to a system having A alone, B alone, C alone, A and B, A and C, B and C, and / or A, B, C, etc.).

[0054] In the technical solution disclosed herein, the acquisition, storage and application of user personal information involved comply with the provisions of relevant laws and regulations, take necessary confidentiality measures, and do not violate public order and good morals.

[0055] The present disclosure provides a resource recommendation method applicable to the field of computer technology. The resource recommendation method includes: in response to an insurance product recommendation request for recommending an insurance product to a family member, obtaining historical insurance product purchase information associated with at least one family member, wherein the historical insurance product purchase information includes family member information, and the family member information includes health risk information; generating a genetic profile based on the historical insurance product purchase information; obtaining descriptive information about the family, wherein the descriptive information represents the family's purchasing power for insurance products; and generating an insurance product recommendation result based on the genetic profile and the descriptive information for recommending an insurance product to the family member. The present disclosure also provides a resource recommendation apparatus, device, storage medium, and program product.

[0056] Figure 1 The application scenario diagram of the resource recommendation method, apparatus, device, medium and program product according to the embodiments of the present disclosure is schematically shown.

[0057] like Figure 1As shown, the application scenario 100 according to this embodiment may include terminal devices 101, 102, 103, a network 104, and a server 105. The network 104 is used as a medium for providing a communication link between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired or wireless communication links or optical fiber cables.

[0058] Users can use terminal devices 101, 102, and 103 to interact with server 105 via network 104 to receive or send messages, etc. Various communication client applications can be installed on terminal devices 101, 102, and 103, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social platform software, etc. (only as examples).

[0059] The terminal devices 101 , 102 , and 103 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop computers, and desktop computers.

[0060] The server 105 may be a server that provides various services, such as a background management server (for example only) that supports websites browsed by users using the terminal devices 101, 102, and 103. The background management server may analyze and process received data such as user requests, and feed back processing results (such as web pages, information, or data obtained or generated according to user requests) to the terminal device.

[0061] It should be noted that the resource recommendation method provided in the embodiment of the present disclosure can generally be executed by the server 105. Accordingly, the resource recommendation device provided in the embodiment of the present disclosure can generally be set in the server 105. The resource recommendation method provided in the embodiment of the present disclosure can also be executed by a server or server cluster that is different from the server 105 and can communicate with the terminal devices 101, 102, 103 and / or the server 105. Accordingly, the resource recommendation device provided in the embodiment of the present disclosure can also be set in a server or server cluster that is different from the server 105 and can communicate with the terminal devices 101, 102, 103 and / or the server 105.

[0062] It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is merely illustrative. Any number of terminal devices, networks and servers may be provided as required.

[0063] The following will be based on Figure 1 The scene described by Figures 2 to 7 The resource recommendation method of the disclosed embodiment is described in detail.

[0064] Figure 2 The flowchart of the resource recommendation method according to an embodiment of the present disclosure is schematically shown.

[0065] like Figure 2 As shown, the resource recommendation method of this embodiment includes operations S201 to S204.

[0066] In operation S201, in response to an insurance product recommendation request for recommending insurance products to family members in a family, historical insurance product purchase information associated with at least one family member in the family is obtained, wherein the historical insurance product purchase information includes family member information in the family, and the family member information includes health risk information.

[0067] In operation S202 , a genetic map is generated based on historical insurance product purchase information.

[0068] According to an embodiment of the present disclosure, the historical insurance product purchase information may include insurance information.

[0069] According to an embodiment of the present disclosure, the insurance information may be each insurance record of a family member in the family, including: insurance company, insurance product, policyholder information, insured person information, beneficiary information, premium, insured amount, etc.

[0070] According to the embodiments of the present disclosure, the insurance information usually includes information on the policyholder, the insured and the beneficiary. Generally, the insured and the beneficiary are the immediate family members of the policyholder, that is, the insured is generally himself, his spouse, children, and parents; the beneficiaries are generally the legal heirs, that is, his spouse, children, parents, siblings, grandparents, and grandparents.

[0071] According to an embodiment of the present disclosure, since the insurance information of any family member may include information of other family members, when an insurance product recommendation request is received, only the historical insurance product purchase information of at least one family member may be obtained.

[0072] According to an embodiment of the present disclosure, when purchasing an insurance product, health risk information is usually filled in the insurance information. The health risk information may include, for example, common diseases, medical history, genetic disease descriptions, etc.

[0073] According to an embodiment of the present disclosure, a genetic map may be generated by reading the insurance information in the historical insurance product purchase information, obtaining the information of the policyholder, the insured, and the beneficiary, as well as the health status information related to the insured.

[0074] According to an embodiment of the present disclosure, the genetic map may be a map that reflects the genetic relationship of a disease among family members of a family.

[0075] According to embodiments of the present disclosure, historical insurance product purchase information may also include insurance company information and insurance product information. Insurance company information may include: name, address, etc. Insurance product information includes: coverage, applicable population, age, etc.; insurance liability, coverage of the insurance type; insurance term, insurance validity period; insurance amount and claim amount; and premium payment method.

[0076] In operation S203 , descriptive information of the household is obtained, wherein the descriptive information represents the purchasing power of the household for insurance products.

[0077] According to an embodiment of the present disclosure, the descriptive information of a family may be obtained by extracting the content of a questionnaire filled out by a user.

[0078] According to an embodiment of the present disclosure, the description information includes but is not limited to: six elements (document type, document number, contact number, name, gender, age), address, occupation, annual income, disease information, etc.

[0079] In operation S204, an insurance product recommendation result for recommending insurance products to family members in the family is generated based on the genetic map and the description information.

[0080] In an embodiment of the present disclosure, when recommending insurance products to family members in a family, not only is descriptive information obtained through a questionnaire, but also historical insurance product purchase information associated with at least one family member in the family is obtained, a genetic map is generated based on the historical insurance product purchase information, and insurance products are recommended to family members in the family based on the genetic map and the descriptive information, thereby improving the accuracy of insurance product recommendations and making the insurance products included in the insurance product recommendation results more suitable for the family members in the family.

[0081] Figure 3 A flowchart for generating a genetic map based on historical insurance product purchase information according to an embodiment of the present disclosure is schematically shown.

[0082] According to an embodiment of the present disclosure, family member information includes family members in a family and relationships between family members.

[0083] like Figure 3 As shown, the method of this embodiment includes operations S301 to S302.

[0084] In operation S301, a kinship graph is generated based on family member information, wherein the kinship graph includes at least two nodes connected by an edge, the nodes represent family members in a family, and the edges represent relationships between family members.

[0085] According to embodiments of the present disclosure, a natural language recognition algorithm can be used to extract family member information from historical insurance product purchase information and identify all person entities. Specifically, the insured, policyholder, and beneficiary information can be first extracted from the insurance application information. Each of these person entities can then be added as a node to the kinship knowledge graph.

[0086] According to embodiments of the present disclosure, after determining the nodes in the kinship knowledge graph, the edges (i.e., relationships) between any two nodes in the kinship knowledge graph can be determined. Specifically, entity linking can be used to extract two entities, i.e., the relationship between two family members, from the insurance information.

[0087] According to an embodiment of the present disclosure, nodes in the kinship knowledge graph can be identified using basic information such as ID number, mobile phone number, name, gender, and age. For example, at least one of the information among ID number, mobile phone number, name, gender, and age can be converted into a vector matrix, and the vector matrix can be used to configure label information for the node.

[0088] In operation S302 , at least one genetic map is generated based on the kinship map and the health risk information, wherein the genetic map is associated with at least one genetic disease.

[0089] According to the embodiments of the present disclosure, genetic disease information of at least one family member in the family can be extracted based on health risk information, and then the immediate family relationships of the family member can be determined from the relative knowledge graph, and the prevalence of the genetic disease in their immediate family relationships can be determined from the insurance information, where the prevalence of the disease can include historical illness but recovery, not currently ill, and moderate illness.

[0090] According to an embodiment of the present disclosure, a genetic map corresponding to a genetic disease can be generated based on the prevalence of genetic diseases among the family members, the immediate family members, and the immediate family members, and the genetic map indicates the probability of each family member suffering from the genetic disease.

[0091] According to an embodiment of the present disclosure, in the case where a family member may suffer from multiple genetic diseases, a genetic map may be generated for each genetic disease according to the above method.

[0092] Figure 4 A schematic diagram of a genetic map according to an embodiment of the present disclosure is schematically shown.

[0093] exist Figure 4 In the figure, individuals marked with 6, 7, 13 and 14 are family members of the family to be recommended the insurance product, and I represents the previous generation of direct relatives of the family.

[0094] from Figure 4It can be seen that family members 6, 7 and 14 are all carriers of genetic disease genes, that is, family members 6, 7 and 14 may have genetic diseases, or are not currently ill but may become ill in the future.

[0095] Since there are multiple family members in this family who carry genes for genetic diseases, when recommending insurance products to family members who carry genes for genetic diseases, priority can be given to recommending critical illness insurance products to them.

[0096] Figure 5 The following schematically shows a flow chart of a resource recommendation method according to another embodiment of the present disclosure.

[0097] According to an embodiment of the present disclosure, historical insurance product purchases also include historical insured product information.

[0098] like Figure 5 As shown, the method of this embodiment includes operations S501 to S502.

[0099] In operation S501 , a plurality of insurance categories are generated based on historical insurance product information, wherein each insurance category represents insurance information for at least one insurance product.

[0100] In operation S502, according to preset rules, the minimum insurance standard and the optimal insurance standard are determined from each insurance category.

[0101] According to an embodiment of the present disclosure, historical insurance product information may first be divided into multiple product groups according to the insurance product categories, and each product group corresponds to at least one insurance product.

[0102] According to an embodiment of the present disclosure, the insured product categories may include medical insurance, accident insurance, life insurance, financial insurance, etc.

[0103] According to an embodiment of the present disclosure, after generating multiple product groups, insurance products that are currently unavailable for recommendation can be filtered out from each product group. Insurance products that are unavailable for recommendation may include, for example, time-sensitive insurance products or discontinued insurance products.

[0104] According to an embodiment of the present disclosure, the preset rule may be to determine the insurance product with the lowest premium as the minimum insurance standard; and to determine the insurance product with the highest ratio of the insured amount to the premium as the optimal insurance standard.

[0105] According to an embodiment of the present disclosure, for multiple insurance products in each group, the insured amount and premium of each product may be obtained, and then the insured amount may be divided by the premium to generate a first ratio.

[0106] According to an embodiment of the present disclosure, the insurance product corresponding to the maximum first ratio in each group can be determined respectively, and the insurance product can be used as the optimal insurance standard in each product group.

[0107] According to an embodiment of the present disclosure, after obtaining the premium of each product in each product group, the insurance product corresponding to the lowest premium in each product group can be used as the minimum insurance standard in the product group.

[0108] According to an embodiment of the present disclosure, multiple insurance products in each group can also be divided into multiple batches based on the insured's annual income level, the insured's age, the insured's gender, the insured's social security payment status, etc., and the optimal insurance standard and the minimum insurance standard for the insurance products in each batch can be determined.

[0109] Table (1) is a schematic diagram showing the classification of each group of insurance products according to the insured's annual income level, age, gender, and social security payment status.

[0110] Table (1)

[0111]

[0112] As shown in Table (1), in the accident insurance group, all accident insurance products can be divided into three levels according to the annual income level. For each insurance product in each level, the optimal insurance standard can be determined based on the ratio of premium to insured amount. For example, in the 100,000-300,000 yuan level, premium / insured amount = 132 / 30 = 4.4; in the 300,000-500,000 yuan level, premium / insured amount = 222 / 50 = 4.44; in the 500,000-1,000,000 yuan level, premium / insured amount = 432 / 100 = 4.32. Therefore, in the accident insurance product group, the premium of 222 yuan / year and the insured amount of 500,000 yuan per year are the optimal insurance standards. Moreover, since the premium of 132 / year is the lowest premium insurance product in the accident insurance product group, the premium of 132 / year is the lowest insurance standard in the accident insurance product group.

[0113] The resource recommendation method provided by the embodiment of the present disclosure can also determine a benchmark insured person from multiple family members, and then recommend insurance products to other family members based on the insurance information of the benchmark insured person.

[0114] According to an embodiment of the present disclosure, for example, the family member whose income accounts for the largest proportion of the family income can be used as the benchmark insured person.

[0115] According to an embodiment of the present disclosure, after determining the benchmark insured, historical insurance product purchase information can be read to extract the first insurance product purchase record in which the insured is the benchmark insured, as well as all insurance information records in the historical insurance product purchase information. Then, based on the first insurance product purchase record and all insurance information records in the historical insurance product purchase information, the premium allocation ratio MR1 for the benchmark insured in the current insurance product recommendation can be calculated. The specific calculation formula is shown in Formula (1).

[0116]

[0117] Among them, the i variable represents the first insurance product purchase record, and there are n such insurance records in total; the t variable represents the record of all insurance information in the historical insurance product purchase information, and there are m such insurance records in total, where m is greater than or equal to n.

[0118] Figure 6 The following schematically shows a flow chart of a resource recommendation method according to another embodiment of the present disclosure.

[0119] like Figure 6 As shown, the method of this embodiment includes operations S601 to S602.

[0120] In operation S601 , a basic premium for each family member in the family is generated according to the description information.

[0121] According to embodiments of the present disclosure, since the description information can represent the purchasing power of a household for insurance products, the base premium for each family member can be determined based on the description information. Once the base premium is determined, personalized insurance product recommendations can be made for each family member based on the base premium and other information such as health risks.

[0122] In operation S602 , recommended insurance information for at least one insurance product for each family member is generated based on the basic premium and genetic profile of each family member.

[0123] Figure 7 The flowchart of generating the basic insurance premium for each family member in a family according to the description information according to an embodiment of the present disclosure is schematically shown.

[0124] According to an embodiment of the present disclosure, the description information includes the family's total income, expenditure ratio, loan amount, and loan term.

[0125] like Figure 7 As shown, the method of this embodiment includes operations S701 to S703.

[0126] In operation S701 , a basic insurance premium for a family is generated based on total income, expenditure ratio, loan amount, and loan term.

[0127] According to an embodiment of the present disclosure, the family basic premium FY can be calculated using the following formula (2).

[0128] FY=(household income*(1-expenditure ratio)-loan amount / loan term)*10%; (2)

[0129] In operation S602, a premium ratio corresponding to each family member is generated according to the number and age of the family members.

[0130] According to an embodiment of the present disclosure, a first number of first family members whose age is younger than a first preset threshold among all family members may be determined, and then a fixed first premium ratio may be allocated to the first family members. For example, the first premium ratio may be 10%, but is not limited thereto, and may also be 12%, 15%, or 20%.

[0131] According to the embodiments of the present disclosure, the first preset threshold can be flexibly set by those skilled in the art, and the embodiments of the present disclosure do not specifically limit the value of the first preset threshold. For example, the first preset threshold can be 22 years old.

[0132] According to an embodiment of the present disclosure, before calculating the premium share of each family member, it is possible to first determine whether the premium allocation ratio of the basic insured exceeds the second preset threshold. If the premium allocation ratio of the basic insured exceeds the second preset threshold, the premium allocation ratio calculated according to formula (1) can be used as the premium allocation ratio of the basic insured. If the premium allocation ratio of the basic insured does not exceed the preset threshold, the premium allocation ratio MR2 of the basic insured can be recalculated according to the following formula (3).

[0133] MR2 = MR1 + (1-MR1-first premium ratio*first quantity) / (total number of family members-first quantity); (3)

[0134] According to the embodiment of the present disclosure, the second preset threshold can be flexibly set by those skilled in the art, and the embodiment of the present disclosure does not specifically limit the value of the second preset threshold. For example, the second preset threshold can be 50%.

[0135] According to an embodiment of the present disclosure, a second family member whose age is greater than the first preset threshold among all family members may be determined, and then a second premium ratio CR for the second family member may be configured. The second premium ratio CR of the second family member may be calculated using the following formula (4).

[0136] CR = (1-MR2-first premium ratio*first amount) / (number of family members other than the basic insured-first amount); (4)

[0137] According to an embodiment of the present disclosure, the third premium ratio SR of the spouse of the basic insured can be calculated using the following formula (5).

[0138] SR = (1-MR2-first premium ratio*first amount) / (number of family members other than the basic insured-first amount); (5)

[0139] In operation S703 , a basic premium for each family member is generated according to each premium proportion and the basic premium of the family.

[0140] According to an embodiment of the present disclosure, the basic premium of each family member can be calculated by multiplying the family basic premium by the premium proportion of each family member.

[0141] Figure 8 The flowchart of generating the basic insurance premium for each family member in a family according to the description information according to an embodiment of the present disclosure is schematically shown.

[0142] like Figure 8 As shown, the method of this embodiment includes operations S801 to S803.

[0143] In operation S801 , a risk level of a family member suffering from a genetic disease is determined based on at least one genetic profile.

[0144] According to an embodiment of the present disclosure, since the probability of each family member suffering from a genetic disease is indicated in the genetic map, the risk level of the family member suffering from a genetic disease can be determined based on the probability of each family member suffering from the genetic disease.

[0145] According to an embodiment of the present disclosure, when there are multiple genetic maps, the probability of suffering from a genetic disease indicated in each genetic map can be accumulated to generate a risk level for the genetic disease.

[0146] In operation S802, a set of insurance products to be insured is determined according to the risk level.

[0147] According to an embodiment of the present disclosure, when the insured person's risk level for a genetic disease is greater than a third preset threshold, a first insurance product set can be generated, wherein the insurance products in the first insurance product set have respective priorities. For example, the first insurance product set includes {critical illness insurance, accident insurance, medical insurance, life insurance}, and the critical illness insurance that ranks high in the first insurance product set can occupy the highest proportion of the insurance amount allocated.

[0148] When the insured's risk level for genetic diseases is less than a third preset threshold, a second insurance product set can be generated, wherein the insurance products in the second insurance product set have respective priorities. For example, the second insurance product set includes {accident insurance, medical insurance, critical illness insurance, life insurance}, and the accident insurance that ranks high in the second insurance product set can occupy the highest proportion of the insurance amount allocated.

[0149] According to the embodiments of the present disclosure, the third preset threshold can be flexibly set by those skilled in the art, and the embodiments of the present disclosure do not specifically limit the value of the third preset threshold.

[0150] In operation S803, recommended insurance information for at least one insurance product in the set of insurance products to be insured is generated based on the minimum insurance standard, the optimal insurance standard, and the basic insurance premium of the family.

[0151] After determining the set of insurance products to be insured, the insurance amount and premium can be configured for each insurance product according to the order of the products in the set of insurance products to be insured.

[0152] According to an embodiment of the present disclosure, the insurance standards corresponding to the family may be determined first based on the description information of the family. The insurance standards may include a minimum insurance standard and an optimal insurance standard.

[0153] According to an embodiment of the present disclosure, for example, based on the descriptive information of the family, it is determined that the insurance standard of the family is the optimal insurance standard. Then, the optimal insurance standard can be summed with the insurance amount and premium configured for each insurance product according to the product order in the set of insurance products to be insured to obtain the total premium of the first temporary family member.

[0154] After obtaining the first temporary total family member premium, it can be determined whether the first temporary total family member premium exceeds a fourth preset threshold, which can be, for example, 1.2 times the basic family premium.

[0155] When the total premium of the first temporary family members does not exceed the fourth preset threshold, the insured amount of each insurance product of the family members can be set to the insured amount corresponding to the optimal insurance standard, and the premium of each insurance product of the family members can be set to the premium corresponding to the optimal insurance standard.

[0156] When the total premium of the first temporary family members exceeds the fourth preset threshold, the minimum insurance standard can be obtained, and then the minimum insurance standard is summed with the insurance amount and premium configured for each insurance product according to the product order in the set of insurance products to be insured to obtain the total premium of the second temporary family members.

[0157] After obtaining the second temporary family member total premium, it can be determined whether the second temporary family member total premium exceeds a fourth preset threshold, which can be, for example, 1.2 times the family basic premium.

[0158] When the total premium of the second temporary family members does not exceed the fourth preset threshold, the insured amount of each insurance product of the family members can be set to the insured amount corresponding to the minimum insurance standard, and the premium of each insurance product of the family members can be set to the premium corresponding to the minimum insurance standard.

[0159] In the case that the total premium of the second temporary family members exceeds the fourth preset threshold, this type of insurance product may not be recommended to the family members in the family temporarily.

[0160] Tables (2) to (3) schematically illustrate a schematic diagram of recommending insurance products to family members in a family with a total basic family premium of RMB 4,000 according to the resource recommendation method provided in an embodiment of the present disclosure.

[0161] Table (2) can show the proportion of premium paid by each family member in the household.

[0162] Table (2)

[0163] Family members Premium share Premium (yuan) First Family Member 10％ 400 Benchmark Insured 55％ 2200 Spouse of the base insured 17.50％ 700 Second family member 17.50％ 700 total 100％ 4000

[0164] Table (3)

[0165]

[0166] The above table (3) can represent the insurance product recommendation results for each family member in the family.

[0167] The calculation results for this family's protection plan are shown in the table above. The total family premium is 3,761 yuan, and the total insured amount is 20 million yuan. The calculation process is as follows: Family member 1 is under 22 years old and has no life insurance. All other products are configured according to the optimal standard. The base insured is over 55 years old and has no critical illness insurance. Life insurance is configured according to the minimum standard, and all other products are configured according to the optimal standard. The base insured's spouse has a genetic disease and a high risk level, so critical illness insurance is prioritized and configured according to the optimal standard. Other products cannot meet the minimum standard, so all other products are configured at zero. Family member 2 has all products configured according to the optimal standard.

[0168] Based on the above resource recommendation method, the present disclosure also provides a resource recommendation device. Figure 9 The device is described in detail.

[0169] Figure 9 The structural block diagram of the resource recommendation device according to an embodiment of the present disclosure is schematically shown.

[0170] like Figure 9 As shown, the resource recommendation device 900 of this embodiment includes a first acquisition module 901 , a first generation module 902 , a second acquisition module 903 and a second generation module 904 .

[0171] First acquisition module 901 is configured to, in response to an insurance product recommendation request for recommending an insurance product for a family member, obtain historical insurance product purchase information associated with at least one family member, wherein the historical insurance product purchase information includes family member information, and the family member information includes health risk information. In one embodiment, first acquisition module 901 may be configured to perform operation S201 described above, which will not be further described here.

[0172] The first generating module 902 is used to generate a genetic map based on historical insurance product purchase information. In one embodiment, the first generating module 902 can be used to perform the operation S202 described above, which will not be repeated here.

[0173] The second acquisition module 903 is used to obtain descriptive information of the family, wherein the descriptive information represents the purchasing power of the family for insurance products. In one embodiment, the second acquisition module 930 can be used to perform the operation S203 described above, which will not be repeated here.

[0174] The second generating module 904 is used to generate an insurance product recommendation result for recommending insurance products to family members in the family based on the genetic map and the description information. In one embodiment, the second generating module 904 can be used to perform the operation S203 described above, which will not be repeated here.

[0175] According to an embodiment of the present disclosure, family member information includes family members in a family and relationships between family members.

[0176] According to an embodiment of the present disclosure, the first generating module 902 includes a first generating submodule and a second generating submodule.

[0177] A first generating submodule is configured to generate a kinship graph based on the family member information, wherein the kinship graph includes at least two nodes connected by an edge, wherein the nodes represent family members in the family and the edges represent the relationships between the family members;

[0178] The second generating submodule is used to generate at least one genetic map based on the kinship map and the health risk information, wherein the genetic map is associated with at least one genetic disease.

[0179] According to an embodiment of the present disclosure, historical insurance product purchases also include historical insured product information.

[0180] According to an embodiment of the present disclosure, the first generating module 902 further includes a third generating submodule and a determining submodule.

[0181] The third generating submodule is configured to generate a plurality of insurance categories based on historical insurance product information, wherein each insurance category represents insurance information for at least one insurance product.

[0182] The determination submodule is used to determine the minimum insurance standard and the optimal insurance standard from each insurance category according to preset rules.

[0183] According to an embodiment of the present disclosure, the first generating module 902 further includes a fourth generating submodule and a fifth generating submodule.

[0184] The fourth generation submodule is used to generate the basic premium for each family member in the family according to the description information;

[0185] The fifth generation submodule is used to generate recommended insurance information for at least one insurance product for each family member based on the basic premium and genetic map of each family member.

[0186] According to an embodiment of the present disclosure, the description information includes the family's total income, expenditure ratio, loan amount, and loan term.

[0187] According to an embodiment of the present disclosure, the fourth generating submodule includes a first generating unit, a second generating unit, and a third generating unit.

[0188] The first generating unit is used to generate a basic insurance premium for a family according to the total income, expenditure ratio, loan amount and loan term.

[0189] The second generating unit is used to generate a premium ratio corresponding to each family member according to the number and age of family members in the family.

[0190] The third generating unit is used to generate the basic premium for each family member according to each premium proportion and the basic premium of the family.

[0191] According to an embodiment of the present disclosure, the fifth generating submodule includes a first determining unit, a second determining unit and a fourth generating unit.

[0192] a first determining unit, configured to determine a risk level of a family member suffering from a genetic disease based on at least one genetic map;

[0193] A second determining unit is used to determine a set of insurance products to be insured according to the risk level;

[0194] The fourth generating unit is used to generate recommended insurance information for at least one insurance product in the set of insurance products to be insured based on the minimum insurance standard, the optimal insurance standard, and the basic insurance premium of the family.

[0195] According to an embodiment of the present disclosure, any multiple modules of the first acquisition module 901, the first generation module 902, the second acquisition module 903, and the second generation module 904 can be combined into one module for implementation, or any one of the modules can be split into multiple modules. Alternatively, at least part of the functions of one or more of these modules can be combined with at least part of the functions of other modules and implemented in one module. According to an embodiment of the present disclosure, at least one of the first acquisition module 901, the first generation module 902, the second acquisition module 903, and the second generation module 904 can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application specific integrated circuit (ASIC), or can be implemented by hardware or firmware such as any other reasonable way of integrating or packaging the circuit, or implemented in any one of the three implementation methods of software, hardware, and firmware, or in an appropriate combination of any of them. Alternatively, at least one of the first acquisition module 901 , the first generation module 902 , the second acquisition module 903 and the second generation module 904 may be at least partially implemented as a computer program module, which may perform corresponding functions when executed.

[0196] Figure 10 The block diagram schematically shows an electronic device suitable for implementing the resource recommendation method according to an embodiment of the present disclosure.

[0197] like Figure 10 As shown, the electronic device 1000 according to an embodiment of the present disclosure includes a processor 1001, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage part 1008 into a random access memory (RAM) 1003. The processor 1001 may, for example, include a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or a related chipset and / or a dedicated microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 1001 may also include an onboard memory for caching purposes. The processor 1001 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0198] Various programs and data required for the operation of the electronic device 1000 are stored in the RAM 1003. The processor 1001, the ROM 1002, and the RAM 1003 are connected to each other via a bus 1004. The processor 1001 performs various operations of the method flow according to the embodiment of the present disclosure by executing the programs in the ROM 1002 and / or the RAM 1003. It should be noted that the programs may also be stored in one or more memories other than the ROM 1002 and the RAM 1003. The processor 1001 may also perform various operations of the method flow according to the embodiment of the present disclosure by executing the programs stored in the one or more memories.

[0199] According to an embodiment of the present disclosure, electronic device 1000 may further include an input / output (I / O) interface 1005, which is also connected to bus 1004. Electronic device 1000 may further include one or more of the following components connected to I / O interface 1005: an input section 1006 including a keyboard, a mouse, etc.; an output section 1007 including devices such as a cathode ray tube (CRT), a liquid crystal display (LCD), and speakers; a storage section 1008 including a hard disk; and a communication section 1009 including a network interface card such as a LAN card or a modem. Communication section 1009 performs communication processing via a network such as the Internet. A drive 1010 is also connected to I / O interface 1005 as needed. Removable media 1011, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed in drive 1010 as needed, so that computer programs read therefrom can be installed into storage section 1008 as needed.

[0200] The present disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments, or may exist independently and not be incorporated into the device / apparatus / system. The computer-readable storage medium carries one or more programs, and when executed, implements the method according to the embodiments of the present disclosure.

[0201] According to an embodiment of the present disclosure, a computer-readable storage medium may be a non-volatile computer-readable storage medium, for example, it may include but is not limited to: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, apparatus, or device. For example, according to an embodiment of the present disclosure, a computer-readable storage medium may include the ROM 1002 and / or RAM 1003 described above and / or one or more memories other than ROM 1002 and RAM 1003.

[0202] The embodiments of the present disclosure also include a computer program product, which includes a computer program containing program code for executing the method shown in the flowchart. When the computer program product is run in a computer system, the program code is used to enable the computer system to implement the resource recommendation method provided by the embodiments of the present disclosure.

[0203] The computer program executes the above functions defined in the system / device of the embodiment of the present disclosure when the processor 1001 executes the computer program. According to the embodiment of the present disclosure, the system, device, module, unit, etc. described above can be implemented by a computer program module.

[0204] In one embodiment, the computer program may be stored on a tangible storage medium such as an optical storage device or a magnetic storage device. In another embodiment, the computer program may be transmitted and distributed in the form of a signal on a network medium, downloaded and installed via the communication portion 1009, and / or installed from the removable medium 1011. The program code contained in the computer program may be transmitted using any appropriate network medium, including but not limited to wireless, wired, or any suitable combination thereof.

[0205] In such an embodiment, the computer program can be downloaded and installed from a network via the communication section 1009, and / or installed from the removable medium 1011. When the computer program is executed by the processor 1001, the above-described functions defined in the system of the embodiment of the present disclosure are performed. According to the embodiment of the present disclosure, the systems, devices, means, modules, units, etc. described above can be implemented by computer program modules.

[0206] According to an embodiment of the present disclosure, the program code for executing the computer program provided by the embodiment of the present disclosure can be written in any combination of one or more programming languages. Specifically, these computer programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, languages ​​such as Java, C++, python, "C" or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (for example, using an Internet service provider to connect via the Internet).

[0207] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, program segment, or a part of code, and the above-mentioned module, program segment, or a part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0208] Those skilled in the art will appreciate that the features described in the various embodiments and / or claims of this disclosure may be combined and / or coupled in various ways, even if such combinations and / or couplings are not explicitly described in this disclosure. In particular, the features described in the various embodiments and / or claims of this disclosure may be combined and / or coupled in various ways without departing from the spirit and teachings of this disclosure. All such combinations and / or couplings are intended to fall within the scope of this disclosure.

[0209] The embodiments of the present disclosure are described above. However, these embodiments are for illustrative purposes only and are not intended to limit the scope of the present disclosure. Although each embodiment has been described separately above, this does not mean that the measures in each embodiment cannot be used in combination to advantage. The scope of the present disclosure is defined by the appended claims and their equivalents. Without departing from the scope of the present disclosure, those skilled in the art may make various substitutions and modifications, which should all fall within the scope of the present disclosure.

Claims

1. A resource recommendation method, include: In response to an insurance product recommendation request for recommending an insurance product for a family member in a family, obtaining historical insurance product purchase information associated with at least one family member in the family, wherein the historical insurance product purchase information includes family member information in the family, the family member information includes health risk information, the family member information also includes family members in the family, and the relationship between the family members; the historical insurance product purchase also includes historical insured product information; Generating a genetic map according to the historical insurance product purchase information, including: generating a kinship map according to the family member information, wherein the kinship map includes at least two nodes connected by an edge, the nodes represent family members in the family, and the edges represent the relationship between the family members; generating at least one genetic map according to the kinship map and the health risk information, wherein the genetic map is associated with at least one genetic disease; Acquire description information of the family, wherein the description information represents the purchasing power of the family for insurance products, and the description information includes the total income, expenditure ratio, loan amount and loan term of the family; generating an insurance product recommendation result for recommending insurance products to family members in the family according to the genetic map and the description information; The method further comprises: Generate multiple insurance categories based on the historical insurance product information, wherein each insurance category represents insurance information for at least one insurance product; determine the minimum insurance standard and the optimal insurance standard from each insurance category according to preset rules; The method further comprises: Generate a basic premium for each family member in the family according to the description information; generate recommended insurance information for at least one insurance product for each family member according to the basic premium of each family member and the genetic map; The basic premium for each family member in the family is generated according to the description information, including: according to the total income, the expenditure ratio, the loan amount and the IB213076-Active Correction The basic insurance premium of the family is generated based on the loan term; the premium ratio corresponding to each family member is generated based on the number and age of the family members; the basic insurance premium of each family member is generated based on each premium ratio and the basic insurance premium of the family; Among them, generating recommended insurance information for at least one insurance product for the family members based on the basic premium of each family member and the genetic map includes: determining the risk level of the family member suffering from a genetic disease based on at least one genetic map; determining a set of insurance products to be insured based on the risk level; generating recommended insurance information for at least one insurance product in the set of insurance products to be insured based on the minimum insurance standard, the optimal insurance standard, and the basic premium of the family.

2. A resource recommendation device, include: A first acquisition module is configured to, in response to an insurance product recommendation request for recommending an insurance product to a family member in a family, acquire historical insurance product purchase information associated with at least one family member in the family, wherein the historical insurance product purchase information includes family member information in the family, the family member information includes health risk information, the family member information also includes family members in the family, and the relationship between the family members; the historical insurance product purchase also includes historical insured product information; A first generating module is used to generate a genetic map according to the historical insurance product purchase information; wherein the first generating module includes a first generating submodule and a second generating submodule; The first generating submodule is used to generate a kinship map based on family member information, wherein the kinship map includes at least two nodes connected by an edge, the node represents a family member in the family, and the edge represents the relationship between the family members; the second generating submodule is used to generate at least one genetic map based on the kinship map and health risk information, wherein the genetic map is associated with at least one genetic disease; A second acquisition module is used to acquire description information of the family, wherein the description information represents the purchasing power of the family for insurance products, and the description information includes the total income, expenditure ratio, loan amount and loan term of the family; A second generating module, configured to generate an insurance product recommendation result for recommending insurance products to family members in the family according to the genetic map and the description information; The first generation module also includes a third generation submodule and a determination submodule; the third generation submodule is used to generate multiple insurance categories according to historical insurance product information, wherein each insurance category The insurance category represents the insurance information for at least one insurance product; the determination submodule is used to determine the minimum insurance standard and the optimal insurance standard from each insurance category according to preset rules; The first generation module also includes a fourth generation submodule and a fifth generation submodule; the fourth generation submodule is used to generate a basic premium for each family member in the family according to the description information; the fifth generation submodule is used to generate recommended insurance information for at least one insurance product for each family member according to the basic premium and the genetic map of each family member; The fourth generation submodule includes a first generation unit, a second generation unit and a third generation unit; the first generation unit is used to generate a basic premium for a family according to the total income, the expenditure ratio, the loan amount and the loan term; the second generation unit is used to generate a premium ratio corresponding to each family member according to the number and age of family members in the family; the third generation unit is used to generate a basic premium for each family member according to each premium ratio and the basic premium of the family; The fifth generating submodule includes a first determining unit, a second determining unit and a fourth generating unit; the first determining unit is used to determine the risk level of family members suffering from genetic diseases based on at least one genetic map; the second determining unit is used to determine the set of insurance products to be insured based on the risk level; the fourth generating unit is used to generate recommended insurance information for at least one insurance product in the set of insurance products to be insured based on the minimum insurance standard, the optimal insurance standard, and the basic premium of the family.

3. An electronic device, include: one or more processors; a storage device for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors are caused to perform the method according to claim 1.

4. A computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, causes the processor to perform the method according to claim 1.

5. A computer program product, comprising a computer program, which implements the method according to claim 1 when executed by a processor.

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