CN112116969B - Information recommendation method and device, storage medium and computer equipment - Google Patents

Information recommendation method and device, storage medium and computer equipment Download PDF

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CN112116969B
CN112116969B CN202010766589.1A CN202010766589A CN112116969B CN 112116969 B CN112116969 B CN 112116969B CN 202010766589 A CN202010766589 A CN 202010766589A CN 112116969 B CN112116969 B CN 112116969B
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CN112116969A (en
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王岩
刘阳
李大宝
刘琦
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Beijing Shuidi Technology Group Co ltd
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    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
    • G16H10/60—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
    • G—PHYSICS
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    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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    • G06Q30/06—Buying, selling or leasing transactions
    • G06Q30/0601—Electronic shopping [e-shopping]
    • G06Q30/0631—Item recommendations
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment

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Abstract

The invention discloses an information recommendation method, an information recommendation device, a storage medium and computer equipment, relates to the technical field of information, and mainly aims to improve the matching precision of guarantee business categories for unhealthy people and rapidly and accurately match the guarantee business categories really fit for unhealthy people. The method comprises the following steps: determining target unhealthy people to which users to be recommended belong, and corresponding illness record information of each user in the target unhealthy people; scoring different diagnosis features in each illness record information respectively to obtain service scores corresponding to the different diagnosis features in each illness record information; according to the service scores corresponding to different treatment characteristics in each illness record information, respectively calculating the matching scores of the target unhealthy crowd and each guarantee service class; and generating service recommendation information corresponding to the user to be recommended according to the matching scores of the target unhealthy crowd and each guarantee service class.

Description

Information recommendation method and device, storage medium and computer equipment
Technical Field
The present invention relates to the field of information technologies, and in particular, to an information recommendation method, an information recommendation device, a storage medium, and a computer device.
Background
With the increasing of the service demands of users, the service parties release various kinds of guarantee service products so as to meet the demands of different users.
Currently, business parties usually only recommend the guaranteed business category for healthy people. However, the same business requirements are also met for the unhealthy crowd, the way of recommending information only for the healthy crowd cannot meet the business requirements of the unhealthy crowd, and in addition, even if the unhealthy crowd is recommended for guaranteeing the business class, the unhealthy crowd is recommended only by means of the working experience of the business personnel, and the unhealthy crowd is difficultly matched to the truly suitable guaranteeing business class due to the fact that the business experience difference of different business personnel is large, so that the matching precision of the guaranteeing the business class is low, and the business requirements of the unhealthy crowd cannot be truly met.
Disclosure of Invention
In view of the above, the present invention provides an information recommendation method, apparatus, storage medium and computer device, which are mainly aimed at improving the matching precision of the guarantee business class for the unhealthy crowd, and rapidly and accurately matching the real fit guarantee business class for the unhealthy crowd, so as to satisfy the demands of the unhealthy crowd.
According to one aspect of the present invention, there is provided an information recommendation method including:
determining target unhealthy people to which users to be recommended belong, and corresponding illness record information of each user in the target unhealthy people;
scoring different diagnosis features in each illness record information respectively to obtain service scores corresponding to the different diagnosis features in each illness record information;
according to the service scores corresponding to different treatment characteristics in each illness record information, respectively calculating the matching scores of the target unhealthy crowd and each guarantee service class;
and generating service recommendation information corresponding to the user to be recommended according to the matching scores of the target unhealthy crowd and each guarantee service class.
Optionally, the calculating the matching score of the target unhealthy crowd and each guaranteed service class according to the service scores corresponding to different treatment features in the disease record information includes:
respectively comparing the service scores corresponding to different treatment characteristics in each illness record information with preset score thresholds corresponding to different service characteristics of any one of the guarantee service categories to obtain comparison results corresponding to different treatment characteristics in each illness record information;
And calculating the matching scores of the target unhealthy crowd and any one of the security service categories according to the comparison results corresponding to different diagnosis features in the disease record information.
Optionally, the calculating the matching score of the target unhealthy crowd and the any one of the security service categories according to the comparison result corresponding to the different diagnosis features in the respective disease record information includes:
according to the comparison results corresponding to different diagnosis features in the illness record information, calculating the matching scores of the users and any one of the security service categories respectively;
and calculating the matching scores of the target unhealthy crowd and any one of the security service categories according to the matching scores of the users and any one of the security service categories.
Optionally, the calculating the matching score of the target unhealthy crowd and the any one of the security service categories according to the comparison result corresponding to the different diagnosis features in the respective disease record information includes:
determining weight values corresponding to different diagnosis features in each disease record information;
and calculating the matching scores of the target non-healthy crowd and any one of the protection business categories based on the determined weight values and the comparison results corresponding to different diagnosis features in the disease record information.
Optionally, the generating the service recommendation information corresponding to the user to be recommended according to the matching scores of the target unhealthy crowd and each guaranteed service class includes:
screening the highest matching score from the calculated matching scores, and determining the guarantee service class corresponding to the highest matching score;
and generating service recommendation information corresponding to the user to be recommended based on the guaranteed service class corresponding to the determined highest matching score.
Optionally, the diagnosis feature includes a main symptom feature, an inspection result feature and a diagnosis duration feature of the user, and the scoring the different diagnosis features in each piece of disease record information to obtain service scores corresponding to the different diagnosis features in each piece of disease record information includes:
and scoring the main symptom characteristic, the examination result characteristic and the diagnosis duration characteristic in each illness record information respectively to obtain service scores respectively corresponding to the main symptom characteristic, the examination result characteristic and the diagnosis duration characteristic in each illness record.
Optionally, the method further comprises:
respectively calculating the matching scores of the to-be-released guaranteed service class and each guaranteed service release platform;
And determining a target guarantee service delivery platform with the optimal delivery effect of the to-be-delivered guarantee service class according to the matching scores of the to-be-delivered guarantee service class and each guarantee service delivery platform.
Optionally, the calculating the matching scores of the to-be-released guaranteed service class and each guaranteed service release platform includes:
comparing different service characteristics of the to-be-released guaranteed service class with different release characteristics of any one of the guaranteed service release platforms to obtain a comparison result corresponding to the different service characteristics of the to-be-released guaranteed service class;
and calculating the matching scores of the objective to-be-released guaranteed service class and any one of the guaranteed service release platforms according to the comparison results corresponding to the different service characteristics of the to-be-released guaranteed service class.
According to a second aspect of the present invention, there is provided an information recommendation apparatus comprising:
the determining unit is used for determining target unhealthy crowd to which the user to be recommended belongs and disease record information corresponding to each user in the target unhealthy crowd;
the scoring unit is used for scoring different diagnosis features in each illness record information respectively to obtain business scores corresponding to the different diagnosis features in each illness record information;
The calculating unit is used for calculating the matching scores of the target unhealthy crowd and each guarantee business class according to the business scores corresponding to different treatment characteristics in each illness record information;
and the generating unit is used for generating the service recommendation information corresponding to the user to be recommended according to the matching scores of the target unhealthy crowd and each guarantee service class.
Optionally, the computing unit includes: the comparison module and the calculation module are used for comparing the data of the data,
the comparison module is used for respectively comparing the service scores corresponding to the different treatment characteristics in each illness record information with preset score thresholds corresponding to the different service characteristics of any one of the guarantee service categories to obtain comparison results corresponding to the different treatment characteristics in each illness record information;
and the calculating module is used for calculating the matching scores of the target unhealthy crowd and any one of the security service categories according to the comparison results corresponding to different diagnosis features in the illness record information.
Optionally, the computing module comprises a first computing sub-module and a second computing sub-module,
the first calculation sub-module is used for calculating the matching scores of the users and any one of the security service categories according to the comparison results corresponding to different diagnosis features in the illness record information;
And the second calculation submodule is used for calculating the matching scores of the target unhealthy crowd and any one of the security service classes according to the matching scores of the users and the any one of the security service classes.
Optionally, the computing module further comprises a determining sub-module,
the determining submodule is used for determining weight values corresponding to different diagnosis features in each piece of disease record information;
the first calculation sub-module is further configured to calculate a matching score of the target unhealthy crowd and the any one of the security service categories based on the determined weight value and a comparison result corresponding to different diagnosis features in the respective disease record information.
Optionally, the generating unit comprises a determining module and a generating module,
the determining module is used for screening out the highest matching score from the calculated matching scores and determining the guarantee service class corresponding to the highest matching score;
and the generating module is used for generating the service recommendation information corresponding to the user to be recommended based on the guaranteed service class corresponding to the determined highest matching score.
Optionally, the diagnosis feature includes a main symptom feature, an inspection result feature and a diagnosis duration feature of the user, and the scoring unit is specifically configured to score the main symptom feature, the inspection result feature and the diagnosis duration feature in each disease record information respectively, so as to obtain service scores corresponding to the main symptom feature, the inspection result feature and the diagnosis duration feature in each disease record respectively.
Optionally, the calculating unit is further configured to calculate matching scores of the to-be-released guaranteed service class and each guaranteed service release platform respectively;
the determining unit is further configured to determine a target guarantee service delivery platform with an optimal delivery effect of the to-be-delivered guaranteed service class according to the matching scores of the to-be-delivered guaranteed service class and each of the guaranteed service delivery platforms.
Optionally, the computing unit is specifically configured to compare different service features of the to-be-released guaranteed service class with different release features of any one of the guaranteed service release platforms, so as to obtain a comparison result corresponding to the different service features of the to-be-released guaranteed service class; and calculating the matching scores of the to-be-released guaranteed service class and any one of the guaranteed service release platforms according to the comparison results corresponding to the different service characteristics of the to-be-released guaranteed service class.
According to a third aspect of the present invention, there is provided a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of:
determining target unhealthy people to which users to be recommended belong, and corresponding illness record information of each user in the target unhealthy people;
Scoring different diagnosis features in each illness record information respectively to obtain service scores corresponding to the different diagnosis features in each illness record information;
according to the service scores corresponding to different treatment characteristics in each illness record information, respectively calculating the matching scores of the target unhealthy crowd and each guarantee service class;
and generating service recommendation information corresponding to the user to be recommended according to the matching scores of the target unhealthy crowd and each guarantee service class.
According to a fourth aspect of the present invention there is provided a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of:
determining target unhealthy people to which users to be recommended belong, and corresponding illness record information of each user in the target unhealthy people;
scoring different diagnosis features in each illness record information respectively to obtain service scores corresponding to the different diagnosis features in each illness record information;
according to the service scores corresponding to different treatment characteristics in each illness record information, respectively calculating the matching scores of the target unhealthy crowd and each guarantee service class;
And generating service recommendation information corresponding to the user to be recommended according to the matching scores of the target unhealthy crowd and each guarantee service class.
Compared with the current recommending mode of guaranteeing service categories only for healthy people, the information recommending method, device, storage medium and computer equipment provided by the invention has the advantages that the target unhealthy people to which the user to be recommended belongs and the illness record information corresponding to each user in the target unhealthy people are determined; scoring different diagnosis features in each illness record information respectively to obtain service scores corresponding to the different diagnosis features in each illness record information; meanwhile, according to the service scores corresponding to different treatment characteristics in each illness record information, respectively calculating the matching scores of the target unhealthy crowd and each guarantee service class; and finally, generating service recommendation information corresponding to the user to be recommended according to the matching scores of the target unhealthy crowd and each guarantee service class, so that service information recommendation aiming at unhealthy crowd can be realized, meanwhile, the matching precision of the guarantee service class aiming at unhealthy crowd is improved, the real suitable guarantee service class can be quickly and accurately matched for unhealthy crowd, and the demands of unhealthy crowd are met.
The technical scheme of the invention is further described in detail through the drawings and the embodiments.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description, serve to explain the principles of the invention.
The invention may be more clearly understood from the following detailed description taken in conjunction with the accompanying drawings, in which:
fig. 1 shows a flowchart of an information recommendation method provided by an embodiment of the present invention;
FIG. 2 is a flowchart of another information recommendation method according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of an information recommendation device according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of another information recommendation device according to an embodiment of the present invention;
fig. 5 shows a schematic physical structure of a computer device according to an embodiment of the present invention.
Detailed Description
Various exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be noted that: the relative arrangement of the components and steps, numerical expressions and numerical values set forth in these embodiments do not limit the scope of the present invention unless it is specifically stated otherwise.
Meanwhile, it should be understood that the sizes of the respective parts shown in the drawings are not drawn in actual scale for convenience of description.
The following description of at least one exemplary embodiment is merely exemplary in nature and is in no way intended to limit the invention, its application, or uses.
Techniques, methods, and apparatus known to one of ordinary skill in the relevant art may not be discussed in detail, but are intended to be part of the specification where appropriate.
It should be noted that: like reference numerals and letters denote like items in the following figures, and thus once an item is defined in one figure, no further discussion thereof is necessary in subsequent figures.
Embodiments of the invention are operational with numerous other general purpose or special purpose computing system environments or configurations. Examples of well known computing systems, environments, and/or configurations that may be suitable for use with the computer system/server include, but are not limited to: personal computer systems, server computer systems, thin clients, thick clients, hand-held or laptop devices, microprocessor-based systems, set-top boxes, programmable consumer electronics, network personal computers, minicomputer systems, mainframe computer systems, and distributed cloud computing technology environments that include any of the above systems, and the like.
A computer system/server may be described in the general context of computer-system-executable instructions, such as program modules, being executed by a computer system. Generally, program modules may include routines, programs, objects, components, logic, data structures, etc., that perform particular tasks or implement particular abstract data types. The computer system/server may be implemented in a distributed cloud computing environment in which tasks are performed by remote processing devices that are linked through a communications network. In a distributed cloud computing environment, program modules may be located in both local and remote computing system storage media including memory storage devices.
The embodiment of the invention provides an information recommendation method, as shown in fig. 1, which comprises the following steps:
101. and determining target unhealthy people to which the users to be recommended belong and disease record information corresponding to each user in the target unhealthy people.
The method and the device are mainly suitable for recommending service information for the unhealthy crowd, an execution subject of the embodiment of the invention is a device or equipment capable of recommending the service information for the unhealthy crowd, and in order to meet the service requirements of the unhealthy crowd, the unhealthy crowd is matched and recommended for the guaranteeing service class suitable for the unhealthy crowd, a large amount of personal information and diseased record information of the unhealthy user are required to be collected in advance, and particularly, when the unhealthy user handles corresponding service on a service platform, the personal information of the user is filled in, wherein the diseased record information corresponding to each user comprises the information of the hospitalization hospital, a main symptom, an assay and an examination result, whether the hospitalization duration, the operation and the like: the information of the region, sex, age, education degree, occupation and the like is uploaded, and meanwhile, the illness record information of the user is uploaded, for example, when the user makes a claim on a claim settlement platform, personal information of the user is filled in, and corresponding illness record information is uploaded, so that the personal information and illness record information of a large number of unhealthy users can be obtained from the service platform.
Further, according to the attribute characteristics corresponding to each unhealthy user, classifying and counting a large number of unhealthy users to form unhealthy people with different attribute characteristics, for example, unhealthy users who are in the Shanghai, 30-40 years old and have gender above the school of the family, and are engaged in non-physical labor are classified into one unhealthy people, meanwhile, unhealthy users who are in the Beijing, 30-40 years old and have gender below the school of the family, and are engaged in physical labor are classified into another unhealthy people, so that different unhealthy users can be classified into different unhealthy people according to the attribute characteristics of the unhealthy users, and the illness record information corresponding to each user under different unhealthy people is determined, so that service information is recommended for the unhealthy people with different attribute characteristics according to the illness record information corresponding to each user.
For the embodiment of the invention, when a user to be recommended has corresponding service requirements and needs to conduct service information recommendation, personal information corresponding to the user to be recommended is firstly obtained, the personal information corresponding to the user to be recommended comprises information of an area, gender, age, education degree, occupation and the like where the user to be recommended is located, further, the personal information corresponding to the user to be recommended is matched with attribute characteristics corresponding to different unhealthy people, according to a matching result, the target unhealthy people to which the user to be recommended belongs are determined, for example, the personal information corresponding to the user to be recommended is Shanghai, age 35, gender is higher than the academic, occupation is a teacher and the like, and the attribute characteristics corresponding to the unhealthy people A are between Shanghai, age 30-40, gender is higher than the academic and the like, and the unhealthy labor is engaged, so that the target unhealthy people to which the user to be recommended belongs to are unhealthy people A can be determined according to the diseased record information corresponding to each user in the target unhealthy people, and the service class suitable for the group is generated to the service requirements of the unhealthy people to be recommended, so as to meet the service requirements of the unhealthy people.
102. And scoring different diagnosis features in each illness record information respectively to obtain service scores corresponding to the different diagnosis features in each illness record information.
The diagnosis feature includes a main symptom feature of the user, an inspection result feature and a diagnosis duration feature, the main symptom feature is a disease symptom of the unhealthy user, the inspection result feature is a diagnosis and test result of the unhealthy user, the diagnosis duration feature is a length of a hospitalization time of the unhealthy user, besides, the diagnosis feature includes a diagnosis hospital name of the unhealthy user, whether the unhealthy user performs an operation, an operation name, and the like, for the embodiment of the present invention, in order to determine a matching degree between a target unhealthy crowd and different service guarantee categories, scoring processing needs to be performed on disease record information corresponding to each user in the target unhealthy crowd in advance, and step 102 specifically includes: and scoring the main symptom characteristic, the examination result characteristic and the diagnosis duration characteristic in each illness record information respectively to obtain service scores respectively corresponding to the main symptom characteristic, the examination result characteristic and the diagnosis duration characteristic in each illness record. Specifically, scoring is performed according to the severity degree corresponding to different diagnosis features, the main symptom features and the examination result features can be scored according to the severity degree corresponding to the main symptom features and the examination result features of the user during scoring, and meanwhile, the diagnosis duration features are scored according to the time length corresponding to the diagnosis duration features, so that the illness record information of each user can be accurately scored according to the severity degree and the hospitalization time of the illness of the user.
For example, the disease types of the users in the characteristics of the examination results are scored, the disease types of the users are classified into 5 grades according to the severity of the disease of the users, the corresponding scores are respectively 0-5 grades, the higher the score is, the more serious the disease of the unhealthy users is represented, meanwhile, if the same user suffers from multiple diseases, the score corresponding to the disease type with the highest severity is determined, the service score corresponding to the disease type of the users is determined, if the disease type of the user suffers from more than one disease type with the highest severity, the score of the users is further processed by adding 1 on the basis of the highest score, and the scores corresponding to the different grades are classified into different grades according to the main symptoms of the users and the severity of the test results, further, the corresponding score is set according to whether the users are hospitalized or not, and the corresponding score is determined to be 0 if the users are not hospitalized; if the user is subjected to hospitalization diagnosis, determining that the corresponding score is 1, adding the corresponding score according to the hospitalization time length of the user on the basis, wherein the longer the hospitalization time of the user is, the more serious the disease of the user is represented, so that different treatment characteristics in disease record information of each user can be scored, service scores corresponding to the different treatment characteristics are obtained, the matching degree of a target healthy crowd and different service guarantee categories is calculated according to the service scores corresponding to the different treatment characteristics in the disease record information of each user, and therefore the service information is automatically recommended to non-healthy crowd without depending on service experience of service personnel, and the matching degree of the service guarantee categories for the non-healthy crowd is improved.
103. And respectively calculating the matching scores of the target unhealthy crowd and each guarantee business class according to the business scores corresponding to different treatment characteristics in each illness record information.
For the embodiment of the invention, in order to match the target unhealthy population with each guaranteed service class, preset scoring thresholds corresponding to different service features in each guaranteed service class are required to be preset according to the service features corresponding to each guaranteed service class, wherein the different service features corresponding to the guaranteed service class can be disease types, symptom features, inspection results, treatment duration and the like for the guaranteed service class, for example, the preset scoring threshold corresponding to the disease types in the guaranteed service class A is less than 3, the preset scoring threshold corresponding to the inspection results is less than 2, the treatment duration is less than 4 and the like, so that the target unhealthy population can be matched with each guaranteed service class.
For the embodiment of the invention, in order to determine the matching degree between the target unhealthy crowd and different guarantee service classes, service scores corresponding to different diagnosis features in each illness record information are respectively compared with preset score thresholds corresponding to different service features of any one of the guarantee service classes, so as to obtain comparison results corresponding to the different diagnosis features in each illness record information, and further, the matching scores corresponding to each user and any one of the guarantee service classes are calculated according to the comparison results corresponding to the different diagnosis features.
For example, the service score corresponding to the main symptom feature in the illness record information of the non-healthy user a is 2, the service score corresponding to the inspection result feature is 1, the service score corresponding to the diagnosis time length feature is 3, the preset score threshold corresponding to the main symptom feature in the guaranteed service class 1 is less than 3, the preset score threshold corresponding to the inspection result is less than 2, the preset score threshold corresponding to the diagnosis time length is less than 2, then the service scores corresponding to different diagnoses in the illness record information are compared with the preset score threshold corresponding to different service features in the guaranteed service class 1, according to the comparison result, it is known that the service scores corresponding to the main symptom feature and the inspection result feature in the illness record information of the non-healthy user a are both within the preset score threshold of the corresponding service feature in the service class 1, therefore, the matching score corresponding to the main symptom feature and the inspection result feature in the illness record information of the non-healthy user a is determined to be 1, the service score corresponding to the non-healthy user is further determined to be more than 1, and the score = 1 is more matched with the service score corresponding to the non-healthy user 1 when the score is more than 1. The matching scores between each unhealthy user and different guarantee business categories can be calculated, and further, the matching scores between the target unhealthy crowd and different business categories are calculated according to the matching scores between each unhealthy user and different guarantee business categories.
Further, in order to improve the accuracy of calculating the matching score between the target unhealthy crowd and the different service classes, step 103 specifically includes: determining weight values corresponding to different diagnosis features in each disease record information; and calculating the matching scores of the target non-healthy crowd and any one of the protection business categories based on the determined weight values and the comparison results corresponding to different diagnosis features in the disease record information. The weight value corresponding to different diagnosis features in the illness record information can be set according to service requirements, for example, the weight corresponding to the main symptom feature is set to be 0.5, the weight value corresponding to the checking result feature is set to be 0.3, the weight value corresponding to the diagnosis time length feature is set to be 0.2, specifically, the matching scores of each user and any one of the security service classes are calculated according to the comparison results corresponding to different diagnosis features in each illness record information and the weight values corresponding to different diagnosis features, and the matching scores between the target non-healthy crowd and different service classes are calculated based on the calculated matching scores of each user and any one of the security service classes.
104. And generating service recommendation information corresponding to the user to be recommended according to the matching scores of the target unhealthy crowd and each guarantee service class.
For the embodiment of the present invention, in order to generate the service recommendation information corresponding to the user to be recommended, step 104 specifically includes: screening the highest matching score from the calculated matching scores, and determining the guarantee service class corresponding to the highest matching score; and generating service recommendation information corresponding to the user to be recommended based on the guaranteed service class corresponding to the determined highest matching score.
Specifically, after the matching scores between the target unhealthy crowd and different guarantee service classes are determined, the highest matching score is screened out from the matching scores, the guarantee service class corresponding to the highest matching score is determined and is determined as the target guarantee service class, further, service recommendation information corresponding to the user to be recommended is generated based on the determined target guarantee service class, namely, the matching degree between the target guarantee service class and the user to be recommended is higher, the requirements of the user to be recommended can be met, and therefore the target guarantee service class with the highest matching degree can be recommended for the unhealthy user quickly and accurately.
Compared with the current recommendation mode of guaranteeing service categories only for healthy people, the information recommendation method provided by the embodiment of the invention has the advantages that the target unhealthy people to which the users to be recommended belong and the illness record information corresponding to each user in the target unhealthy people are determined; scoring different diagnosis features in each illness record information respectively to obtain service scores corresponding to the different diagnosis features in each illness record information; meanwhile, according to the service scores corresponding to different treatment characteristics in each illness record information, respectively calculating the matching scores of the target unhealthy crowd and each guarantee service class; and finally, generating service recommendation information corresponding to the user to be recommended according to the matching scores of the target unhealthy crowd and each guarantee service class, so that service information recommendation aiming at unhealthy crowd can be realized, meanwhile, the matching precision of the guarantee service class aiming at unhealthy crowd is improved, the real suitable guarantee service class can be quickly and accurately matched for unhealthy crowd, and the demands of unhealthy crowd are met.
Further, in order to better illustrate the service information recommendation process for the unhealthy crowd, as a refinement and extension of the foregoing embodiment, another information recommendation method is provided in the embodiment of the present invention, as shown in fig. 2, where the method includes:
201. and determining target unhealthy people to which the users to be recommended belong and disease record information corresponding to each user in the target unhealthy people.
Wherein, to the embodiment of the invention, in order to generate the service recommendation information corresponding to the user to be recommended, the target unhealthy crowd to which the user to be recommended belongs needs to be determined in advance, and the guaranteed service class which is most matched with the target unhealthy crowd is determined according to the illness record information corresponding to each user in the target unhealthy crowd, and the service recommendation information corresponding to the user to be recommended is generated, specifically, when different unhealthy users transact services on a service platform, corresponding personal information is filled in, and meanwhile illness record information of the user is uploaded, so that a large amount of personal information and illness record information corresponding to the unhealthy user can be obtained, further, according to the attribute characteristics corresponding to each unhealthy user, a large amount of unhealthy users are statistically classified to the unhealthy crowd with different attribute characteristics, for example, the unhealthy crowd between 30 and 40 years old, the unhealthy user with gender being more than the family school, the unhealthy user who engages in non-physical labor is used as one unhealthy crowd, the unhealthy crowd is simultaneously, the corresponding to the health information is difficult to be recommended, the information of the user is compared with the corresponding to the user to the illness record information, and the information is compared with the information of the target unhealthy crowd to be recommended, and the information is further, and the information is required to be read by the target unhealthy crowd, and the user is compared with the information is determined to be read, and generating service recommendation information corresponding to the user to be recommended according to the disease record information corresponding to each user in the target unhealthy crowd.
202. And scoring different diagnosis features in each illness record information respectively to obtain service scores corresponding to the different diagnosis features in each illness record information.
For the embodiment of the invention, before scoring different diagnosis features in each disease record information, the main symptom feature and the examination result feature are divided into a plurality of grades according to the severity degree corresponding to the main symptom feature and the examination result feature, the higher the grade corresponding score is, the more serious the disease of the user is represented, for example, the main symptom feature is divided into 5 grades according to the severity degree, the corresponding score is 0-5, the highest grade corresponding score is 5, the same is true of the diagnosis time, the examination result and other features are also divided into a plurality of grades, and further, in specific scoring, the service score corresponding to the different diagnosis features in each disease record information is determined according to the grade of the different diagnosis features in each disease record information.
203. And respectively comparing the service scores corresponding to the different treatment characteristics in each disease record information with preset score thresholds corresponding to the different service characteristics of any one of the guarantee service categories to obtain comparison results corresponding to the different treatment characteristics in each disease record information.
The different service characteristics corresponding to the guarantee service classes can be disease types, symptom characteristics, inspection results, treatment duration and the like aimed at by the guarantee service classes, in order to match target unhealthy people with each guarantee service class, preset scoring thresholds corresponding to the different service characteristics in each guarantee service class need to be set in advance according to the service characteristics corresponding to each guarantee service class, and when information recommendation is carried out on users to be recommended, service scores corresponding to the different treatment characteristics in each illness record information are compared with preset scoring thresholds corresponding to the different treatment characteristics of any one guarantee service class in each illness record information, so that comparison results corresponding to the different treatment characteristics in each illness record information are obtained.
204. And calculating the matching scores of the target unhealthy crowd and any one of the security service categories according to the comparison results corresponding to different diagnosis features in the disease record information.
For the embodiment of the present invention, in order to calculate the matching score of the target unhealthy crowd and any of the security service categories, step 204 specifically includes: according to the comparison results corresponding to different diagnosis features in the illness record information, calculating the matching scores of the users and any one of the security service categories respectively; and calculating the matching scores of the target unhealthy crowd and any one of the security service categories according to the matching scores of the users and any one of the security service categories. Specifically, according to the comparison results corresponding to different diagnosis features in each illness record information, determining the matching scores corresponding to the different diagnosis features in each illness record information, adding the matching scores corresponding to the different diagnosis features in each illness record information to obtain the matching scores of each user and any one of the security service categories, and further, calculating the average value of the matching scores of each user and any one of the security service categories to obtain the matching scores of the target unhealthy population and any one of the security service categories.
205. And generating service recommendation information corresponding to the user to be recommended according to the matching scores of the target unhealthy crowd and each guarantee service class.
For the embodiment of the invention, after the matching scores of the target unhealthy crowd and each guarantee service class are calculated, the target guarantee service class corresponding to the highest matching score is determined, namely, the matching degree of the target unhealthy crowd and the target guarantee service class is highest, and then the service recommendation information corresponding to the user to be recommended is generated according to the determined target guarantee service class, so that the guarantee service class suitable for the unhealthy crowd can be rapidly and accurately recommended, and the service requirements of the unhealthy crowd are met.
Meanwhile, in order to improve the delivery precision of the guaranteed service class, and enable the delivered guaranteed service class to truly meet the requirements of unhealthy people, before delivering the target guaranteed service class, the matching degree between the target guaranteed service class and different service delivery platforms needs to be calculated so as to select the service delivery platform with the highest matching degree with the target guaranteed service class for delivery, and based on this, the method further comprises: respectively calculating the matching scores of the to-be-released guaranteed service class and each guaranteed service release platform; and determining a target guarantee service delivery platform with the optimal delivery effect of the to-be-delivered guarantee service class according to the matching scores of the to-be-delivered guarantee service class and each guarantee service delivery platform. Further, comparing different service characteristics of the to-be-released guaranteed service class with different release characteristics of any one of the guaranteed service release platforms to obtain a comparison result corresponding to the different service characteristics of the to-be-released guaranteed service class; and calculating the matching scores of the to-be-released guaranteed service class and any one of the guaranteed service release platforms according to the comparison results corresponding to the different service characteristics of the to-be-released guaranteed service class. The service class to be put in and guaranteed can be any service class with a guaranteed service in a service class library.
For example, the service characteristics of the to-be-released guaranteed service class are mainly for users who engage in non-physical labor in first-line cities with ages of 30-40 and above, the release characteristics of the guaranteed service release platform A are two-line cities with ages of 30-40 and below, the users who engage in physical labor are compared with the different release characteristics of the guaranteed service release platform A, the comparison results corresponding to the different service characteristics of the to-be-released guaranteed service class are obtained, the matching scores corresponding to the different service characteristics of the to-be-released guaranteed service class are determined according to the comparison results, the matching scores corresponding to the different service characteristics of the to-be-released guaranteed service class are 1 score because only age groups are matched, the matching scores of the other service characteristics are 0 score, and the matching scores corresponding to the various service characteristics of the to-be-released guaranteed service class are added to obtain the matching scores of the to-be-released service class and the guaranteed service release platform A, so that the matching scores between the to-be-released service class and the different guaranteed service release platform A can be determined, the matching scores corresponding to the to be the optimal guaranteed service platform can be determined, and the to be-released service effect of the to be the optimal guaranteed platform.
In order to illustrate the implementation process of the above embodiment, taking the claim product recommendation of the unhealthy crowd as an example, the following application scenario is given, but not limited thereto:
in a specific application scene, when a user performs claim settlement on a claim settlement platform, personal information is filled in, corresponding ill record information is uploaded, and therefore, the personal information and the ill record information of unhealthy users who settle the claim in a period of time can be obtained, the users are divided into different unhealthy groups according to the attribute characteristics corresponding to the unhealthy users, the ill record information corresponding to each user under different unhealthy groups is determined, when the unhealthy users have business requirements, the personal information corresponding to the user can be obtained when the claim settlement products suitable for the user are required to be purchased, the target unhealthy groups to which the unhealthy users belong are determined according to the personal information corresponding to the user, and further, business recommendation information of the user is generated according to the ill record information corresponding to each user under the target unhealthy groups, so that the requirements of the unhealthy groups on the claim settlement products can be met, meanwhile, a proper throwing platform can be selected for the claim settlement products so as to ensure throwing effects of the claim settlement products, and sales of the claim settlement products for the unhealthy groups can be opened.
Compared with the current recommendation mode of guaranteeing service categories only for healthy people, the information recommendation method provided by the embodiment of the invention has the advantages that the target unhealthy people to which the users to be recommended belong and the illness record information corresponding to each user in the target unhealthy people are determined; scoring different diagnosis features in each illness record information respectively to obtain service scores corresponding to the different diagnosis features in each illness record information; meanwhile, according to the service scores corresponding to different treatment characteristics in each illness record information, respectively calculating the matching scores of the target unhealthy crowd and each guarantee service class; and finally, generating service recommendation information corresponding to the user to be recommended according to the matching scores of the target unhealthy crowd and each guarantee service class, so that service information recommendation aiming at unhealthy crowd can be realized, meanwhile, the matching precision of the guarantee service class aiming at unhealthy crowd is improved, the real suitable guarantee service class can be quickly and accurately matched for unhealthy crowd, and the demands of unhealthy crowd are met.
Further, as an implementation of the method shown in fig. 1, an embodiment of the present invention provides an information recommendation apparatus, as shown in fig. 3, including: a determination unit 31, a scoring unit 32, a calculation unit 33, and a generation unit 34.
The determining unit 31 may be configured to determine a target unhealthy crowd to which the user to be recommended belongs, and disease record information corresponding to each user in the target unhealthy crowd. The determining unit 31 is a main functional module in the present apparatus for determining a target unhealthy crowd to which the user to be recommended belongs, and disease record information corresponding to each user in the target unhealthy crowd.
The scoring unit 32 may be configured to score different diagnosis features in each of the disease record information, so as to obtain service scores corresponding to the different diagnosis features in each of the disease record information. The scoring unit 32 is a main functional module for scoring different diagnosis features in each disease record information in the device to obtain service scores corresponding to the different diagnosis features in each disease record information, and is also a core module.
The calculating unit 33 may be configured to calculate, according to the service scores corresponding to the different diagnosis features in the disease record information, matching scores of the target unhealthy crowd and each of the guaranteed service categories. The calculating unit 33 is a main functional module, and is also a core module, for calculating the matching scores of the target unhealthy crowd and each guaranteed service class according to the service scores corresponding to different diagnosis features in the disease record information.
The generating unit 34 may be configured to generate the service recommendation information corresponding to the user to be recommended according to the matching scores of the target unhealthy crowd and each guaranteed service class. The generating unit 34 is a main functional module, and also a core module, for generating service recommendation information corresponding to the user to be recommended according to the matching scores of the target unhealthy crowd and each guaranteed service class in the device.
Further, as shown in fig. 4, the computing unit 33 includes: a comparison module 331 and a calculation module 332.
The comparison module 331 may be configured to compare service scores corresponding to different diagnosis features in the respective disease record information with preset score thresholds corresponding to different service features of any one of the respective security service categories, so as to obtain comparison results corresponding to different diagnosis features in the respective disease record information.
The calculating module 332 may be configured to calculate the matching score of the target unhealthy crowd and the any one of the security service categories according to the comparison results corresponding to the different diagnosis features in the respective disease record information.
Further, the computing module 332 includes a first computing sub-module and a second computing sub-module.
The first calculation sub-module may be configured to calculate, according to comparison results corresponding to different diagnosis features in the disease record information, a matching score of each user and any one of the security service categories.
The second calculation sub-module may be configured to calculate, according to the matching scores of the users and the any one of the security service classes, a matching score of the target unhealthy crowd and the any one of the security service classes.
Further, the computing module 332 further includes a determining sub-module.
The determining submodule can be used for determining weight values corresponding to different diagnosis features in each piece of disease record information.
The first calculation sub-module may be further configured to calculate a matching score of the target unhealthy crowd and the any one of the security service categories based on the determined weight value and a comparison result corresponding to different diagnosis features in the respective disease record information.
Further, the generating unit 34 includes a determining module 341 and a generating module 342.
The determining module 341 may be configured to screen a highest matching score from the calculated matching scores, and determine a guaranteed service class corresponding to the highest matching score.
The generating module 342 may be configured to generate the service recommendation information corresponding to the user to be recommended based on the guaranteed service class corresponding to the determined highest matching score.
Further, the diagnosis feature includes a main symptom feature, an inspection result feature, and a diagnosis duration feature of the user, and the scoring unit 32 may be specifically configured to score the main symptom feature, the inspection result feature, and the diagnosis duration feature in each disease record information, so as to obtain service scores corresponding to the main symptom feature, the inspection result feature, and the diagnosis duration feature in each disease record.
Further, the calculating unit 33 may be further configured to calculate matching scores of the to-be-released guaranteed service class and each guaranteed service release platform respectively.
The determining unit 31 may be further configured to determine, according to the matching scores of the to-be-released guaranteed service class and each guaranteed service release platform, a target guaranteed service release platform with an optimal release effect of the to-be-released guaranteed service class.
Further, the calculating unit 33 may be specifically configured to compare different service characteristics of the to-be-released guaranteed service class with different release characteristics of any one of the guaranteed service release platforms, so as to obtain a comparison result corresponding to the different service characteristics of the to-be-released guaranteed service class; and calculating the matching scores of the to-be-released guaranteed service class and any one of the guaranteed service release platforms according to the comparison results corresponding to the different service characteristics of the to-be-released guaranteed service class.
Based on the above-mentioned methods shown in fig. 1 and 2, correspondingly, the embodiment of the present invention further provides a computer readable storage medium, on which a computer program is stored, which when executed by a processor, implements the methods shown in fig. 1 to 2.
Based on the embodiment of the method shown in fig. 1 and the device shown in fig. 3, the embodiment of the invention further provides a physical structure diagram of a computer device, as shown in fig. 5, where the computer device includes: a processor 41, a memory 42, and a computer program stored on the memory 42 and executable on the processor, wherein the memory 42 and the processor 41 are both arranged on a bus 43, the processor 41 implementing the method as shown in fig. 1-2 when executing the program.
According to the technical scheme, the target unhealthy crowd to which the user to be recommended belongs and the illness record information corresponding to each user in the target unhealthy crowd can be determined; scoring different diagnosis features in each illness record information respectively to obtain service scores corresponding to the different diagnosis features in each illness record information; meanwhile, according to the service scores corresponding to different treatment characteristics in each illness record information, respectively calculating the matching scores of the target unhealthy crowd and each guarantee service class; and finally, generating service recommendation information corresponding to the user to be recommended according to the matching scores of the target unhealthy crowd and each guarantee service class, so that service information recommendation aiming at unhealthy crowd can be realized, meanwhile, the matching precision of the guarantee service class aiming at unhealthy crowd is improved, the real suitable guarantee service class can be quickly and accurately matched for unhealthy crowd, and the demands of unhealthy crowd are met.
In this specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different manner from other embodiments, so that the same or similar parts between the embodiments are mutually referred to. For system embodiments, the description is relatively simple as it essentially corresponds to method embodiments, and reference should be made to the description of method embodiments for relevant points.
The method and system of the present invention may be implemented in a number of ways. For example, the methods and systems of the present invention may be implemented by software, hardware, firmware, or any combination of software, hardware, firmware. The above-described sequence of steps for the method is for illustration only, and the steps of the method of the present invention are not limited to the sequence specifically described above unless specifically stated otherwise. Furthermore, in some embodiments, the present invention may also be embodied as programs recorded in a recording medium, the programs including machine-readable instructions for implementing the methods according to the present invention. Thus, the present invention also covers a recording medium storing a program for executing the method according to the present invention.
The description of the present invention has been presented for purposes of illustration and description, and is not intended to be exhaustive or limited to the invention in the form disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, and to enable others of ordinary skill in the art to understand the invention for various embodiments with various modifications as are suited to the particular use contemplated.

Claims (16)

1. An information recommendation device, characterized by comprising:
the determining unit is used for determining target unhealthy crowd to which the user to be recommended belongs and disease record information corresponding to each user in the target unhealthy crowd;
the scoring unit is used for scoring different diagnosis features in each illness record information respectively to obtain business scores corresponding to the different diagnosis features in each illness record information;
the calculating unit is used for respectively comparing the service scores corresponding to different diagnosis features in each illness record information with preset score thresholds corresponding to different service features of any one of the guarantee service categories to obtain comparison results corresponding to different diagnosis features in each illness record information, and respectively calculating the matching scores of the target unhealthy crowd and each guarantee service category according to the comparison results;
and the generating unit is used for generating the service recommendation information corresponding to the user to be recommended according to the matching scores of the target unhealthy crowd and each guarantee service class.
2. The apparatus of claim 1, wherein the computing unit comprises: a first computing sub-module and a second computing sub-module,
The first calculation sub-module is used for calculating the matching scores of the users and any one of the security service categories according to the comparison results corresponding to different diagnosis features in the illness record information;
and the second calculation submodule is used for calculating the matching scores of the target unhealthy crowd and any one of the security service classes according to the matching scores of the users and the any one of the security service classes.
3. The apparatus of claim 2, wherein the computing unit further comprises a determination submodule,
the determining submodule is used for determining weight values corresponding to different diagnosis features in each piece of disease record information;
the first calculation sub-module is further configured to calculate a matching score of the target unhealthy crowd and the any one of the security service categories based on the determined weight value and a comparison result corresponding to different diagnosis features in the respective disease record information.
4. The apparatus of claim 1, wherein the generating unit comprises: the determining module and the generating module are used for determining the position of the object,
the determining module is used for screening out the highest matching score from the calculated matching scores and determining the guarantee service class corresponding to the highest matching score;
And the generating module is used for generating the service recommendation information corresponding to the user to be recommended based on the guaranteed service class corresponding to the determined highest matching score.
5. The device according to claim 1, wherein the diagnosis features include a main symptom feature, an inspection result feature, and a diagnosis duration feature of the user, and the scoring unit is specifically configured to score the main symptom feature, the inspection result feature, and the diagnosis duration feature in each disease record information, respectively, to obtain service scores corresponding to the main symptom feature, the inspection result feature, and the diagnosis duration feature in each disease record.
6. The apparatus of claim 1, wherein the device comprises a plurality of sensors,
the computing unit is also used for respectively computing the matching scores of the to-be-released guaranteed service class and each guaranteed service release platform;
the determining unit is further configured to determine a target guarantee service delivery platform with an optimal delivery effect of the to-be-delivered guaranteed service class according to the matching scores of the to-be-delivered guaranteed service class and each of the guaranteed service delivery platforms.
7. The apparatus of claim 6, wherein the device comprises a plurality of sensors,
the computing unit is specifically configured to compare different service characteristics of the to-be-released guaranteed service class with different release characteristics of any one of the guaranteed service release platforms, so as to obtain a comparison result corresponding to the different service characteristics of the to-be-released guaranteed service class; and calculating the matching scores of the to-be-released guaranteed service class and any one of the guaranteed service release platforms according to the comparison results corresponding to the different service characteristics of the to-be-released guaranteed service class.
8. An information recommendation method, comprising:
determining target unhealthy people to which users to be recommended belong, and corresponding illness record information of each user in the target unhealthy people;
scoring different diagnosis features in each illness record information respectively to obtain service scores corresponding to the different diagnosis features in each illness record information;
respectively comparing the service scores corresponding to different treatment characteristics in each illness record information with preset score thresholds corresponding to different service characteristics of any one of the guarantee service categories to obtain comparison results corresponding to different treatment characteristics in each illness record information, and respectively calculating the matching scores of the target unhealthy crowd and each guarantee service category according to the comparison results;
and generating service recommendation information corresponding to the user to be recommended according to the matching scores of the target unhealthy crowd and each guarantee service class.
9. The method according to claim 8, wherein calculating the matching score of the target unhealthy population with the any one of the protection service categories based on the comparison results corresponding to the different visit characteristics in the respective disease record information comprises:
According to the comparison results corresponding to different diagnosis features in the illness record information, calculating the matching scores of the users and any one of the security service categories respectively;
and calculating the matching scores of the target unhealthy crowd and any one of the security service categories according to the matching scores of the users and any one of the security service categories.
10. The method according to claim 9, wherein calculating the matching score of the target unhealthy population with the any one of the protection service categories based on the comparison results corresponding to the different visit characteristics in the respective disease record information comprises:
determining weight values corresponding to different diagnosis features in each disease record information;
and calculating the matching scores of the target non-healthy crowd and any one of the protection business categories based on the determined weight values and the comparison results corresponding to different diagnosis features in the disease record information.
11. The method of claim 8, wherein the generating the service recommendation information corresponding to the user to be recommended according to the matching scores of the target unhealthy crowd and the respective guaranteed service categories comprises:
Screening the highest matching score from the calculated matching scores, and determining the guarantee service class corresponding to the highest matching score;
and generating service recommendation information corresponding to the user to be recommended based on the guaranteed service class corresponding to the determined highest matching score.
12. The method according to claim 8, wherein the diagnosis features include a main symptom feature, an inspection result feature, and a diagnosis duration feature of the user, and the scoring the different diagnosis features in each disease record information to obtain service scores corresponding to the different diagnosis features in each disease record information includes:
and scoring the main symptom characteristic, the examination result characteristic and the diagnosis duration characteristic in each illness record information respectively to obtain service scores respectively corresponding to the main symptom characteristic, the examination result characteristic and the diagnosis duration characteristic in each illness record.
13. The method of claim 8, wherein the method further comprises:
respectively calculating the matching scores of the to-be-released guaranteed service class and each guaranteed service release platform;
and determining a target guarantee service delivery platform with the optimal delivery effect of the to-be-delivered guarantee service class according to the matching scores of the to-be-delivered guarantee service class and each guarantee service delivery platform.
14. The method according to claim 13, wherein the calculating the matching scores of the to-be-delivered guaranteed service class and each guaranteed service delivery platform respectively includes:
comparing different service characteristics of the to-be-released guaranteed service class with different release characteristics of any one of the guaranteed service release platforms to obtain a comparison result corresponding to the different service characteristics of the to-be-released guaranteed service class;
and calculating the matching scores of the to-be-released guaranteed service class and any one of the guaranteed service release platforms according to the comparison results corresponding to the different service characteristics of the to-be-released guaranteed service class.
15. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 8 to 14.
16. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the computer program when executed by the processor implements the steps of the method of any of claims 8 to 14.
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