CN111178069A - Data processing method and device, computer equipment and storage medium - Google Patents
Data processing method and device, computer equipment and storage medium Download PDFInfo
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- CN111178069A CN111178069A CN201911359223.6A CN201911359223A CN111178069A CN 111178069 A CN111178069 A CN 111178069A CN 201911359223 A CN201911359223 A CN 201911359223A CN 111178069 A CN111178069 A CN 111178069A
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- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
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- G06F16/23—Updating
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Abstract
The invention discloses a data processing method, a data processing device, computer equipment and a storage medium. The method comprises the following steps: inquiring the item to be matched according to the identity information in the user information; extracting key information from the ill characteristic information of the user information; when the matching information of the item to be matched is successfully matched with the key information, hospital information matched with the key information is determined; generating a display weight factor of a target hospital corresponding to each item of hospital information by using the lucene component, and determining the association degree between the user information, the matching information and the hospital information of the target hospital according to the display weight factor; and sequencing the target hospitals according to the relevance, and displaying hospital information and/or display weight factors corresponding to the sequenced target hospitals on an interactive interface. The target hospital displayed in the interactive interface of the invention is matched with the user information and the sick characteristic information, and the fitness of the hospital information and the user information of the target hospital is improved.
Description
Technical Field
The present invention relates to the field of data processing, and in particular, to a data processing method and apparatus, a computer device, and a storage medium.
Background
Medical resources are a very important resource in the health insurance industry. Whether a user can enjoy high-quality medical services after purchasing health insurance products becomes an important factor for the user to select insurance companies, and is a competitive focus of each insurance company. At present, an insurance company can automatically pay by using an application program on a computer paying system or a mobile terminal, but hospital information which can be paid and is generated on the computer paying system or the mobile terminal is not related to user types or disease types, and the like, so that the hospital information cannot have a definite guiding function for selecting a target hospital when a user treats diseases, and further, the user cannot accurately know the association relation among each insurance product, the hospital information and the user. Therefore, on one hand, the user can perform manual repeated consultation on treatment flows such as treatment and claims and the like and staff of the insurance company subsequently, inconvenience is brought to claim settlement work, the claim settlement efficiency of automatic claim settlement through a computer claim settlement system or a mobile terminal is reduced, human resources are wasted, and extremely poor user experience is brought to the user; on the other hand, the user may randomly select a hospital from the hospital information for treatment, and the randomly selected hospital may not have any pertinence to the disease of the user, and may delay the symptomatic treatment of the user, thereby causing the disease condition of the user to be aggravated, and at the same time, the payment limit of the insurance company may also be increased.
Therefore, the technical solution for analyzing the association among insurance products, hospital information and user information through big data and generating the most accurate and suitable hospital information of the target hospital for the user becomes a problem to be solved by those skilled in the art.
Disclosure of Invention
Therefore, it is necessary to provide a data processing method, an apparatus, a computer device, and a storage medium for analyzing user information, matching information, and hospital information through big data and then recommending a target hospital with high fitness and accuracy to a user, so that the user can select the target hospital and improve the experience of the user.
A method of data processing, comprising:
receiving a recommendation instruction containing user information, and inquiring an item to be matched from a database according to identity information in the user information;
extracting key information from the diseased characteristic information of the user information;
acquiring matching information of the item to be matched through a semantic model, traversing and inquiring a hospital information list associated with the database and the matching information when the matching information is successfully matched with the key information, determining the hospital information matched with the key information, and generating a matching list according to the hospital information matched with the key information; the hospital information list comprises at least one item of hospital information;
generating a display weight factor of a target hospital corresponding to each item of hospital information in the matching list by using a lucene component, and determining the association degree between the user information, the matching information and the hospital information of the target hospital according to the display weight factor;
and sequencing each target hospital according to the relevance, and displaying the hospital information and/or the display weight factor corresponding to each target hospital after sequencing according to a preset dimension on an interactive interface of a client.
A data processing apparatus comprising:
the receiving module is used for receiving a recommendation instruction containing user information and inquiring an item to be matched from a database according to identity information in the user information;
the extraction module is used for extracting key information from the diseased characteristic information of the user information;
the generation module is used for acquiring matching information of the item to be matched through a semantic model, traversing and inquiring a hospital information list associated with the database and the matching information when the matching information is successfully matched with the key information, determining hospital information matched with the key information, and generating a matching list according to the hospital information matched with the key information; the hospital information list comprises at least one item of hospital information;
the determining module is used for generating a display weight factor of a target hospital corresponding to each item of the hospital information in the matching list by using a lucene component, and determining the association degree among the user information, the matching information and the hospital information of the target hospital according to the display weight factor;
and the display module is used for sequencing the target hospitals according to the relevance and displaying the hospital information and/or the display weight factor corresponding to the target hospitals after sequencing according to a preset dimension on an interactive interface of a client.
A computer device comprising a memory, a processor and a computer program stored in said memory and executable on said processor, said processor implementing the above data processing method when executing said computer program.
A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the above-mentioned data processing method.
The data processing method, the data processing device, the computer equipment and the storage medium extract key information from the diseased characteristic information of the user information; acquiring matching information of the item to be matched through a semantic model, traversing and inquiring a hospital information list associated with the database and the matching information when the matching information is successfully matched with the key information, determining the hospital information matched with the key information, and generating a matching list according to the hospital information matched with the key information; the hospital information list comprises at least one item of hospital information; generating a display weight factor of a target hospital corresponding to each item of hospital information in the matching list by using a lucene component, and determining the association degree between the user information, the matching information and the hospital information of the target hospital according to the display weight factor; and sequencing each target hospital according to the relevance, and displaying the hospital information and/or the display weight factor corresponding to each target hospital after sequencing according to a preset dimension on an interactive interface of a client. At this time, the interactive interface at the client is displayed according to the preset dimension, that is, each page in the interactive interface displays the hospital information (such as the name of the hospital, the main treatment subject of the hospital, etc.) and/or the display weight factor (such as the geographic factor, the insurance claim factor, etc.) of the target hospital, and the hospital information of the target hospital of each page is sorted according to the degree of fitness (relevance) after analyzing the user information, the matching information and the hospital information. Therefore, the user can conveniently watch and sort in the interactive interface of the client and then select a target hospital which is most suitable for the item to be matched (insurance product) associated with the identity information of the user, so that the doubtful property of the user for selecting the target hospital can be reduced, and the condition of wasting human resources caused by subsequent repeated consultation is avoided; and the target hospital selected by the user is matched with the sick characteristic information contained in the identity information of the user, namely the selected target hospital has pertinence, so that the user can perform symptomatic treatment in the selected target hospital, on one hand, the sick characteristic information of the user can be treated best, the user experience effect is further improved, on the other hand, the user can obtain the payment related to the cost generated by treatment to the maximum extent by displaying the weight factor (insurance payment factor), and on the other hand, the payment amount of extra payment for delaying the illness state of an insurance company is indirectly reduced due to the pertinence of the selected target hospital.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments of the present invention will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without inventive labor.
FIG. 1 is a diagram illustrating an application environment of a data processing method according to an embodiment of the present invention;
FIG. 2 is a flow chart of a data processing method according to an embodiment of the present invention;
FIG. 3 is a flowchart illustrating step S40 of the data processing method according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a data processing apparatus according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of a computer device according to an embodiment of the invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The data processing method provided by the invention can be applied to the application environment shown in fig. 1, wherein a client communicates with a server through a network. Among other things, the client may be, but is not limited to, various personal computers, laptops, smartphones, tablets, and portable wearable devices. The server may be implemented as a stand-alone server or as a server cluster consisting of a plurality of servers.
In an embodiment, as shown in fig. 2, a data processing method is provided, which is described by taking the server in fig. 1 as an example, and includes the following steps S10-S50:
s10, receiving a recommendation instruction containing user information, and inquiring an item to be matched from a database according to identity information in the user information;
understandably, after a user triggers a recommendation instruction of a hospital through a button, a server receives the recommendation instruction, simultaneously obtains user information matched with the user from a preset storage database, and can query at least one item to be matched from the database associated with each cooperation company according to identity information (including name, identification card number, home address and the like) in the user information, wherein the item to be matched is a product item having an association relation with each hospital, for example, the product item is an insurance product of each cooperation insurance company and comprises an insurance product of health insurance.
S20, extracting key information from the diseased characteristic information of the user information;
understandably, the diseased characteristic information is medical record information acquired from databases associated with the hospital systems, and is stored in a preset storage database in association with user information, at this time, key information in the diseased characteristic information can be directly extracted from a fixed module position in the preset storage database according to rules for identifying the fixed module, for example, the diseased characteristic information is medical record information of a user in a hospital, and at this time, a specific academic name (cold, fever, etc.) of a disease suffered by the user can be directly extracted from a diseased module position (the above-mentioned fixed template position, information or an identifier associated with the fixed template position can be identified, such as a diseased name, a star identifier, etc.) in the medical record information.
S30, acquiring matching information of the item to be matched through a semantic model, traversing and inquiring a hospital information list associated with the database and the matching information when the matching information is successfully matched with the key information, determining hospital information matched with the key information, and generating a matching list according to the hospital information matched with the key information; the hospital information list comprises at least one item of hospital information;
understandably, the matching information refers to the product information of the above mentioned product items (when the item to be matched is an insurance product, the matching information is the clause information of the insurance product, and the clause information can be the responsibility clause related to the disease, etc.), wherein, each product item has a product contract or product specification (existing in an electronic form), so that the product information corresponding to the product contract or product specification can be directly obtained through the product contract or product specification; a plurality of kinds of hospital information associated with the items to be matched exist in the hospital information list; the hospital information is hospital data after cleaning and labeling, and therefore the hospital information is finally hospital data presented in a label form, for example, the hospital information of a certain hospital is hospital data presented in a label form of one, third-level special hospitals or third-level class-A hospitals or third-level class-B hospitals or third-level class-C hospitals or second-level class-B hospitals or second-level class-C hospitals in public hospitals or private hospitals, or an unrated hospital, a limited social security fixed-point hospital, an overseas hospital, and the like.
Specifically, keywords in all matching information corresponding to the items to be matched can be identified through a semantic model, and only the matching information of the module where the keywords are located can be extracted (for example, related keywords when a user suffers from various diseases in the items to be matched can be identified, the matching information of the module where the keywords are located can be directly extracted at the moment, all the matching information in the items to be matched is divided by a plurality of modules; matching the matching information with the key information (namely matching the disease type recorded in the matching information with the specific academic name of the disease suffered by the user), and when the matching is successful (in another embodiment, when the matching is failed, determining that the matching information of the item to be matched does not have the function of guaranteeing the characteristic information of the disease), inquiring a hospital information list associated with the matching information from the database (the association relationship between each item of hospital information in the hospital information list and the matching information of the item to be matched is successfully bound), namely determining at least one item of hospital information associated with the item to be matched; and finally, further determining the hospital information matched with the key information according to the matching relationship between the matching information and the key information and the incidence relationship between the matching information and the hospital information in the hospital information list.
In this embodiment, by matching the matching information with the key information, and when the matching is successful, each item of hospital information in the hospital information list associated with the matching information of the item to be matched can be determined first, and then the hospital information matched with the key information can be determined, so that the process that the key information is directly matched with all the hospital information which is not determined to be associated with the matching information can be avoided, the time for determining the hospital information matched with the key information by the server can be reduced, and the workload of the server can also be reduced.
Further, the obtaining of the matching information of the item to be matched through the semantic model, when the matching information is successfully matched with the key information, traversing and querying a hospital information list associated with the database and the matching information, and determining the hospital information matched with the key information includes:
determining the quantity of the matching information acquired from the item to be matched through the semantic model; one item to be matched corresponds to one matching information;
when the number of the matching information is one and the matching information is successfully matched with the key information, traversing and inquiring the hospital information list associated with the matching information and the database, and determining the hospital information matched with the key information; in another embodiment, when the number of the matching information is one and the matching between the matching information and the key information fails, the key information is prompted not to be associated with the item to be matched.
When the number of the matching information is more than two and the matching information is successfully matched with the key information, traversing and inquiring the hospital information list associated with the database and all the matching information, acquiring each group of matching data formed by the hospital information matched with each matching information, acquiring the hospital information superposed in each group of matching data, and determining the superposed hospital information as the hospital information matched with the key information. In another embodiment, when the number of the matching information is two or more and the matching information is successfully matched with the key information, each set of matching data consisting of the hospital information matched with each matching information is acquired from the hospital information list associated with the matching information in the database, and when the hospital information superposed in each set of matching data is not acquired, the hospital information with the highest matching degree is selected from the matching data and determined as the hospital information matched with the key information; the matching degree is that hospital information which is most suitable for the key information is determined from each group of matching data, the grading of the outpatient service ranking, the hospital grade ranking, the expert grade and other conditions of the treatment key information in the hospital information is determined, and finally the matching degree of each hospital information and the key information is calculated through grading.
In this embodiment, since one item to be matched corresponds to one matching information, and the identity information in the user information is associated with at least one item to be matched, when the identity information in the user information is associated with more than two items to be matched, it is possible to determine that the number of matching information acquired from the item to be matched is one; when the identity information in the user information is associated with more than two items to be matched, the number of the matching information acquired from the items to be matched can be determined to be more than two. At this time, the matching information can be matched with the key information, and when the matching is successful, the key information can be associated with the item to be matched, and the hospital information matched with the key information can also be determined. The embodiment can determine the hospital information matched with the key information by determining the number of the matching information acquired from the item to be matched, so that the determined hospital information is more consistent with the key information, and can also play a role in integrating and recommending for the user (when more than two items to be matched are associated with the identity information in the user information, namely when the number of the matching information of the items to be matched is more than two, a piece of hospital information most suitable for the key information of the user is determined).
Further, before the traversing queries the hospital information list associated with the matching information in the database and determines the hospital information matching the key information, the traversing further includes:
collecting hospital data of all hospitals in a preset data acquisition mode, performing data check on all the hospital data, and performing data cleaning to obtain the cleaned hospital data;
labeling the cleaned hospital data, and recording each labeled hospital data of each hospital as the hospital information of the hospital.
Understandably, the preset data acquisition mode comprises a web crawler or manual collection mode; the data cleaning carries out the process of reexamination and verification on all hospital data, aims to delete repeated information, correct existing errors and ensure the consistency of the hospital data, and the specific implementation mode can be realized by setting cleaning rules or manual integration treatment, wherein the cleaning rules can comprise deduplication treatment and the like; the labeling can specifically screen or summarize representative keywords from the washed hospital data.
In the embodiment, the collected hospital data of all hospitals can be cleaned through data cleaning, so that invalid or repeated hospital data can be filtered, and the cleaned hospital data is labeled, so that the cleaned hospital data can be converted into a simplified form, and the data can be conveniently checked by a user.
S40, generating a display weight factor of a target hospital corresponding to each item of hospital information in the matching list by using a lucene component, and determining the association degree between the user information, the matching information and the hospital information of the target hospital according to the display weight factor;
understandably, the display weight factor means that the lucene component is set by using the corresponding relationship between the user information, the matching information and each hospital information in the matching list to generate and present important hospital information about the target hospital and the importance degree of the important hospital information, such as twenty percent of the level ranking of the target hospital (the importance degree of the target hospital with the level ranking of thirteen is one hundred percent below twenty percent, the importance degree of the target hospital with the level ranking of two is eighty percent below twenty percent, etc.), twenty percent of the clinic ranking of the treatment key information of the target hospital (the importance degree of the target hospital with the clinic ranking of the first name is one hundred percent below twenty percent, etc.), and twenty percent of the evaluation information of the target hospital (the importance degree of the target hospital with the good evaluation information is below twenty percent, etc.) One hundred percent, etc. The evaluation information can be specifically determined by preset personnel, the degree of importance of the association between the target hospital and the item to be matched (that is, the condition of the insurance product after the user visits the target hospital, and also can be referred to as an insurance claim factor, the insurance claim factor includes full claim, partial claim and the like) is twenty percent, the degree of importance of the distance between the target hospital and the user (that is, the geographic factor mentioned below) is ten percent, the other degrees of importance are ten percent and the like, and the degree of importance mentioned above can be set by the user according to the requirements; the association degree is a weighted value (the importance degree of all the important hospital information in the weight factors is calculated by adding operation) of the weighted value of the user information, the matching information and the target hospital corresponding to the hospital information of the target hospital (the user information, the matching information and the hospital information of the target hospital have a corresponding relation, namely, one user information corresponds to at least one matching information, and one matching relation corresponds to at least one hospital information of the target hospital, therefore, once the important hospital information of one target hospital is determined by the preset weight factors, the association degree between the important hospital information of the target hospital can be determined by the preset weight factors, the mentioned association relation is established by the data map component), and the weighted value is suitable for sequencing the target hospitals, and the relevance can reflect the fitness of the target hospital and the user through the weight value.
Further, as shown in fig. 3, the generating, by using a lucene component, a display weight factor of a target hospital corresponding to each piece of the hospital information in the matching list includes:
s401, acquiring the corresponding relation between the user information, the matching information and the hospital information in the target hospital established by the data map component by using the lucene component, and performing documentation processing on each group of the user information, the matching information and the hospital information in the target hospital with the corresponding relation by using the lucene component to obtain a target document;
s402, inputting the target document into a preset word segmentation component in the lucene component for word segmentation processing to obtain a first target word element after word segmentation processing;
s403, inputting the first target lemma into a preset language processing component in the lucene component for filtering and summarizing to obtain a second target lemma;
s404, inputting the second target lemma into a preset index component in the lucene component to obtain an index file generated by the preset index component; the index file comprises index key information corresponding to the second target lemma;
s405, after the key information is input into the lucene component, matching the key information with the index key information in the index file, and when the matching is successful, acquiring the display weight factor which is output by a first data interface associated with the lucene component and is related to the target hospital.
Understandably, the lucene component is a tool with a full-text searching function, and can be used for searching target information through indexes after indexes are added to a system program of the server; the data pattern component is a logic which is established through a continuous relation between data and can output all data information related to the data, namely the data pattern component writes a data relation. The first data interface is used for transmitting data of the display weight factors of the target hospitals in the lucene component.
In the embodiment, the corresponding relation established by the data map component can intuitively and accurately correlate the user information and the matching information with the hospital information in the target hospital, and once one data is determined, other data corresponding to the data correlation can be rapidly inquired, so that the operating efficiency of the server can be increased; after the key information is input into the lucene component, the hospital information of the target hospital can be inquired through the corresponding relation between the user information, the matching information and the hospital information in the matching list, but because the lucene component sets the important hospital information, the first data interface output associated with the lucene component is not all the hospital information corresponding to the target hospital, but the important hospital information corresponding to the target hospital (namely, the weight factor is displayed). Therefore, the embodiment can present important information to the user for viewing, and is also convenient for setting the weight relationship (i.e. the above-mentioned association) displayed by the target hospital.
Further, in step S404, after obtaining an index file generated by the preset index component, the method further includes:
acquiring an index file updating instruction containing an updating identifier, acquiring an index file to be updated corresponding to the updating identifier from a database, deleting the index file to be updated in an internal memory index, and putting the deleted index file to be updated into an internal memory document deletion list;
acquiring a new index file according to the update identification, and adding the new index file into the memory index;
after the memory document deletion list is applied to a hard disk index corresponding to the database, deleting the index file to be updated in the hard disk index;
and merging the memory index added into the new index file into the hard disk index, and confirming that the update of the index file is completed.
Understandably, because each index file is stored in the database, and update identifiers (such as numbers) are associated with all index files in the database, the index file can be determined by querying the update identifiers, for example, the index file associated with number 1 is the index file to be updated. At the moment, the index file to be updated can be inquired from the database through the number 1; after deleting the index file to be updated corresponding to the update identifier in the database, adding a new index file corresponding to the update identifier (after determining the update identifier of the index file to be updated, associating the update identifier with the new index file in advance) into the database
In this embodiment, the index file in the database can be updated in time, so that the invalid index file to be updated can be removed, and a targeted display weight factor can be generated by using the lucene component in the process of matching the key information with the index key information in the index file.
Further, the user information comprises a first geographical position of the user; the display weight factor comprises a geographic factor; in step S40, the generating, by using the lucene component, a display weight factor of a target hospital corresponding to each piece of the hospital information in the matching list includes:
and acquiring a second geographic position of each target hospital in the hospital information of the target hospital, calculating a third geographic position with a difference between the first geographic position and the second geographic position by using a lucene component, and recording the third geographic position as a geographic factor.
Understandably, the first geographical position of the user information user can be obtained through the positioning function of the client after the user triggers the recommendation instruction of the hospital; the second geographic position of each target hospital can be obtained by crawling on the internet in advance, and the data of the second geographic position is stored in the hospital information. The third geographic position is determined by various transportation modes (including but not limited to walking, driving, public transportation and subway), that is, the geographic factor mentioned above can display the actual distance between the first geographic position and the second geographic position in various transportation modes, and can also display the actual distance between the first geographic position and the second geographic position in a common transportation mode.
The geographic factor in this embodiment will be used as one of the pre-weighting factors, and will be displayed on the interactive interface of the client for the user to view the distance between the target hospital and the user.
S50, sorting the target hospitals according to the relevance, and displaying the hospital information and/or the display weight factors corresponding to the sorted target hospitals according to preset dimensions on an interactive interface of a client.
Understandably, the determined association degree is also a sorted weight value, and the target hospitals can be sorted on the interactive interface of the client according to the size of the weight value (wherein the larger the weight value is, the earlier the sorting order is, the higher the suitability of the target hospitals and the user information is, and therefore, the association degree can be understood as the suitability of the user information). At this time, the interactive interface at the client is displayed according to the preset dimension, that is, each page in the interactive interface displays the hospital information (such as the name of the hospital, the main treatment subject of the hospital, etc.) and/or the display weight factor (such as the geographic factor, the insurance claim factor, etc.) of the target hospital, and the hospital information of the target hospital of each page is sorted according to the degree of fitness (relevance) after analyzing the user information, the matching information and the hospital information. Therefore, the user can conveniently watch and select the most suitable target hospital for the item to be matched associated with the self identity information after sequencing, thereby increasing the user experience, reducing the doubtful property of selecting the target hospital by the user on one hand, and maximizing the user to obtain the payment related to the cost generated by treatment by displaying the weight factor (insurance payment factor) on the other hand, and indirectly reducing the payment amount paid by an insurance company for delaying the illness state due to the pertinence of the selected target hospital on the other hand.
Further, after the step S50, the method further includes:
sending a feedback request to a user in a preset mode, acquiring evaluation information fed back by the user for one target hospital according to the feedback request, and inquiring whether diagnosis information matched with the identity information of the user exists in the target hospital or not through a second data interface associated with the target hospital;
and when the diagnosis information matched with the identity information of the user exists, sending the evaluation information to preset personnel for verification, and adjusting the association degree corresponding to the target hospital according to the evaluation information after verification is correct.
Understandably, after the user triggers a preset time length of a recommendation instruction of the hospital, the server automatically generates a corresponding prompt for rating and feeds back the rating information to the client associated with the user. The second data interface is a hospitalization system associated with the target hospital.
In this embodiment, the evaluation information fed back by the user for one target hospital is obtained first, and then whether the target hospital has the visit information matched with the identity information of the user is inquired, so that the condition that the user does not visit the target hospital and performs malicious evaluation can be avoided, and the fairness of the ranking (the above-mentioned association degree) of each target hospital can be ensured. When the information of the doctor matched with the identity information of the user exists, the evaluation information is verified through preset personnel, and the condition that the user carries out malicious evaluation can be further avoided.
Further, in the step S50, after displaying, on the interactive interface of the client, the sorted hospital information and/or display weight factors corresponding to the target hospitals according to the preset dimensions, the method further includes:
and after a display instruction triggered by the user aiming at one target hospital in the interactive interface is obtained, the interactive interface is made to display all cleaned hospital data associated with the target hospital.
Understandably, a main page of an interactive interface of the client has hospital information and/or display weight factors corresponding to a plurality of preset dimensions of target hospitals, optionally, one preset dimension may correspond to one hospital information and/or display weight factor, one preset dimension has one sub-dimension, and all cleaned hospital data associated with the target hospitals exist in each sub-dimension.
In this embodiment, after the user has a display instruction triggered by a target hospital in the interactive interface, the user can clearly view all cleaned hospital data associated with the target hospital, so that the user can be aware of the target hospital and provide a reference for the user to further determine.
In summary, the foregoing provides a data processing method, which extracts key information from diseased feature information of the user information; acquiring matching information of the item to be matched through a semantic model, traversing and inquiring a hospital information list associated with the database and the matching information when the matching information is successfully matched with the key information, determining the hospital information matched with the key information, and generating a matching list according to the hospital information matched with the key information; the hospital information list comprises at least one item of hospital information; generating a display weight factor of a target hospital corresponding to each item of hospital information in the matching list by using a lucene component, and determining the association degree between the user information, the matching information and the hospital information of the target hospital according to the display weight factor; and sequencing each target hospital according to the relevance, and displaying the hospital information and/or the display weight factor corresponding to each target hospital after sequencing according to a preset dimension on an interactive interface of a client. At this time, the interactive interface at the client is displayed according to the preset dimension, that is, each page in the interactive interface displays the hospital information (such as the name of the hospital, the main treatment subject of the hospital, etc.) and/or the display weight factor (such as the geographic factor, the insurance claim factor, etc.) of the target hospital, and the hospital information of the target hospital of each page is sorted according to the degree of fitness (relevance) after analyzing the user information, the matching information and the hospital information. Therefore, the user can conveniently watch and sort in the interactive interface of the client and then select a target hospital which is most suitable for the item to be matched (insurance product) associated with the identity information of the user, so that the doubtful property of the user for selecting the target hospital can be reduced, and the condition of wasting human resources caused by subsequent repeated consultation is avoided; and the target hospital selected by the user is matched with the sick characteristic information contained in the identity information of the user, namely the selected target hospital has pertinence, so that the user can perform symptomatic treatment in the selected target hospital, on one hand, the sick characteristic information of the user can be treated best, the user experience effect is further improved, on the other hand, the user can obtain the payment related to the cost generated by treatment to the maximum extent by displaying the weight factor (insurance payment factor), and on the other hand, the payment amount of extra payment for delaying the illness state of an insurance company is indirectly reduced due to the pertinence of the selected target hospital.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.
In an embodiment, a data processing apparatus is provided, and the data processing apparatus corresponds to the data processing method in the above embodiment one to one. As shown in fig. 4, the data processing apparatus includes a receiving module 11, an extracting module 12, a generating module 13, a determining module 14, and a presenting module 15. The functional modules are explained in detail as follows:
the receiving module 11 is configured to receive a recommendation instruction including user information, and query an item to be matched from a database according to identity information in the user information;
an extraction module 12, configured to extract key information from the diseased feature information of the user information;
the generating module 13 is configured to obtain matching information of the item to be matched through a semantic model, traverse and query a hospital information list associated with the database and the matching information when the matching information is successfully matched with the key information, determine hospital information matched with the key information, and generate a matching list according to the hospital information matched with the key information; the hospital information list comprises at least one item of hospital information;
a determining module 14, configured to generate, by using a lucene component, a display weight factor of a target hospital corresponding to each item of the hospital information in the matching list, and determine, according to the display weight factor, a degree of association between the user information, the matching information, and the hospital information of the target hospital;
and the display module 15 is configured to sort each target hospital according to the relevance, and display the hospital information and/or the display weight factor corresponding to each target hospital after sorting according to a preset dimension on an interactive interface of the client.
Further, the generating module includes:
the first determining submodule is used for determining the quantity of the matching information acquired from the item to be matched through the semantic model; one item to be matched corresponds to one matching information;
the second determining submodule is used for traversing and inquiring the hospital information list related to the database and the matching information and determining the hospital information matched with the key information when the number of the matching information is one and the matching between the matching information and the key information is successful;
and the third determining submodule is used for traversing and inquiring the hospital information list associated with the database and all the matching information when the number of the matching information is more than two and the matching information is successfully matched with the key information, acquiring each group of matching data formed by the hospital information matched with each matching information, acquiring the hospital information superposed in each group of matching data, and determining the superposed hospital information as the hospital information matched with the key information.
Further, the data processing apparatus further includes:
the data cleaning module is used for collecting hospital data of all hospitals through a preset data acquisition mode, performing data checking on all the hospital data and then performing data cleaning to obtain the cleaned hospital data;
and the recording module is used for labeling the cleaned hospital data and recording each labeled hospital data of each hospital as the hospital information of the hospital.
Further, the determining module includes:
the first processing sub-module is used for acquiring the corresponding relation between the user information, the matching information and the hospital information in the target hospital, which is established by the data map component, by using the lucene component, and performing documentation processing on each group of the user information, the matching information and the hospital information in the target hospital, which have the corresponding relation, by using the lucene component to obtain a target document;
the second processing submodule is used for inputting the target document into a preset word segmentation component in the lucene component for word segmentation processing to obtain a first target lemma after word segmentation processing;
the third processing submodule is used for inputting the first target lemma into a preset language processing component in the lucene component for filtering and summarizing processing to obtain a second target lemma;
the input submodule is used for inputting the second target lemma into a preset index component in the lucene component to obtain an index file generated by the preset index component; the index file comprises index key information corresponding to the second target lemma;
and the matching sub-module is used for matching the key information with the index key information in the index file after the key information is input into the lucene component, and acquiring the display weight factor related to the target hospital output through a first data interface associated with the lucene component when the matching is successful.
Further, the data processing apparatus further includes:
the storage module is used for acquiring an index file updating instruction containing an updating identifier, acquiring an index file to be updated corresponding to the updating identifier from a database, deleting the index file to be updated in the memory index, and storing the deleted index file to be updated into a memory document deletion list;
the adding module is used for acquiring a new index file according to the updating identification and adding the new index file into the memory index;
the application module is used for deleting the index file to be updated in the hard disk index after the memory document deletion list is applied to the hard disk index corresponding to the database;
and the confirming module is used for merging the memory index added into the new index file into the hard disk index and confirming that the update of the index file is completed.
Further, the determining module includes:
and the acquisition submodule is used for acquiring a second geographic position of each target hospital in the hospital information of the target hospital, calculating a third geographic position with a difference between the first geographic position and the second geographic position by using the lucene component, and recording the third geographic position as a geographic factor.
Further, the data processing apparatus further includes:
the query module is used for sending a feedback request to a user in a preset mode, acquiring evaluation information fed back by the user aiming at one target hospital according to the feedback request, and querying whether the target hospital has diagnosis information matched with the identity information of the user through a second data interface associated with the target hospital;
and the verification module is used for sending the evaluation information to preset personnel for verification when the visit information matched with the identity information of the user exists, and adjusting the correlation degree corresponding to the target hospital according to the evaluation information after the verification is correct.
For specific limitations of the data processing apparatus, reference may be made to the above limitations of the data processing method, which are not described herein again. The various modules in the data processing apparatus described above may be implemented in whole or in part by software, hardware, and combinations thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 5. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer device is used for storing data involved in the data processing method. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a data processing method.
In one embodiment, a computer device is provided, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor executes the computer program to implement the steps of the data processing method in the above embodiments, such as steps S10 to S50 shown in fig. 2. Alternatively, the processor, when executing the computer program, implements the functions of the respective modules/units of the data processing apparatus in the above-described embodiments, such as the functions of the modules 11 to 15 shown in fig. 4. To avoid repetition, further description is omitted here.
In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, which when executed by a processor implements the steps of the data processing method in the above-described embodiments, such as steps S10 to S50 shown in fig. 2. Alternatively, the computer program realizes the functions of the respective modules/units of the data processing apparatus in the above-described embodiments, such as the functions of the modules 11 to 15 shown in fig. 4, when being executed by the processor. To avoid repetition, further description is omitted here.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, databases, or other media used in embodiments provided herein may include non-volatile and/or volatile memory. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present invention, and are intended to be included within the scope of the present invention.
Claims (10)
1. A data processing method, comprising:
receiving a recommendation instruction containing user information, and inquiring an item to be matched from a database according to identity information in the user information;
extracting key information from the diseased characteristic information of the user information;
acquiring matching information of the item to be matched through a semantic model, traversing and inquiring a hospital information list associated with the database and the matching information when the matching information is successfully matched with the key information, determining the hospital information matched with the key information, and generating a matching list according to the hospital information matched with the key information; the hospital information list comprises at least one item of hospital information;
generating a display weight factor of a target hospital corresponding to each item of hospital information in the matching list by using a lucene component, and determining the association degree between the user information, the matching information and the hospital information of the target hospital according to the display weight factor;
and sequencing each target hospital according to the relevance, and displaying the hospital information and/or the display weight factor corresponding to each target hospital after sequencing according to a preset dimension on an interactive interface of a client.
2. The data processing method according to claim 1, wherein the obtaining of the matching information of the item to be matched through the semantic model, when the matching information is successfully matched with the key information, traversing and querying a hospital information list associated with the matching information in the database, and determining the hospital information matched with the key information comprises:
determining the quantity of the matching information acquired from the item to be matched through the semantic model; one item to be matched corresponds to one matching information;
when the number of the matching information is one and the matching information is successfully matched with the key information, traversing and inquiring the hospital information list associated with the matching information and the database, and determining the hospital information matched with the key information;
when the number of the matching information is more than two and the matching information is successfully matched with the key information, traversing and inquiring the hospital information list associated with the database and all the matching information, acquiring each group of matching data formed by the hospital information matched with each matching information, acquiring the hospital information superposed in each group of matching data, and determining the superposed hospital information as the hospital information matched with the key information.
3. The data processing method of claim 1, wherein the traversing queries the database for a list of hospital information associated with the matching information, and before determining the hospital information matching the key information, further comprises:
collecting hospital data of all hospitals in a preset data acquisition mode, performing data check on all the hospital data, and performing data cleaning to obtain the cleaned hospital data;
labeling the cleaned hospital data, and recording each labeled hospital data of each hospital as the hospital information of the hospital.
4. The data processing method of claim 1, wherein the generating, by a lucene component, a display weight factor for a target hospital corresponding to each of the hospital information in the matching list comprises:
acquiring the corresponding relation between the user information, the matching information and the hospital information in the target hospital established by a data map component by using the lucene component, and performing documentation processing on each group of the user information, the matching information and the hospital information in the target hospital by using the lucene component to obtain a target document;
inputting the target document into a preset word segmentation component in the lucene component for word segmentation processing to obtain a first target lemma after word segmentation processing;
inputting the first target lemma into a preset language processing component in the lucene component for filtering and summarizing to obtain a second target lemma;
inputting the second target lemma into a preset index component in the lucene component to obtain an index file generated by the preset index component; the index file comprises index key information corresponding to the second target lemma;
after the key information is input into the lucene component, matching the key information with the index key information in the index file, and when the matching is successful, acquiring the display weight factor which is output about the target hospital through a first data interface associated with the lucene component.
5. The data processing method of claim 4, wherein after obtaining an index file generated by the predetermined index component, the method further comprises:
acquiring an index file updating instruction containing an updating identifier, acquiring an index file to be updated corresponding to the updating identifier from a database, deleting the index file to be updated in an internal memory index, and putting the deleted index file to be updated into an internal memory document deletion list;
acquiring a new index file according to the update identification, and adding the new index file into the memory index;
after the memory document deletion list is applied to a hard disk index corresponding to the database, deleting the index file to be updated in the hard disk index;
and merging the memory index added into the new index file into the hard disk index, and confirming that the update of the index file is completed.
6. The data processing method of claim 1, wherein the user information comprises a first geographical location of a location of the user; the display weight factor comprises a geographic factor; the generating, by the lucene component, a display weight factor of a target hospital corresponding to each piece of the hospital information in the matching list includes:
and acquiring a second geographic position of each target hospital in the hospital information of the target hospital, calculating a third geographic position with a difference between the first geographic position and the second geographic position by using a lucene component, and recording the third geographic position as a geographic factor.
7. The data processing method according to claim 1, wherein after the sorting of the target hospitals according to the relevance and the displaying of the hospital information and/or the display weight factor corresponding to the sorted target hospitals according to a preset dimension on an interactive interface of a client, the method further comprises:
sending a feedback request to a user in a preset mode, acquiring evaluation information fed back by the user for one target hospital according to the feedback request, and inquiring whether diagnosis information matched with the identity information of the user exists in the target hospital or not through a second data interface associated with the target hospital;
and when the diagnosis information matched with the identity information of the user exists, sending the evaluation information to preset personnel for verification, and adjusting the association degree corresponding to the target hospital according to the evaluation information after verification is correct.
8. A data processing apparatus, comprising:
the receiving module is used for receiving a recommendation instruction containing user information and inquiring an item to be matched from a database according to identity information in the user information;
the extraction module is used for extracting key information from the diseased characteristic information of the user information;
the generation module is used for acquiring matching information of the item to be matched through a semantic model, traversing and inquiring a hospital information list associated with the database and the matching information when the matching information is successfully matched with the key information, determining hospital information matched with the key information, and generating a matching list according to the hospital information matched with the key information; the hospital information list comprises at least one item of hospital information;
the determining module is used for generating a display weight factor of a target hospital corresponding to each item of the hospital information in the matching list by using a lucene component, and determining the association degree among the user information, the matching information and the hospital information of the target hospital according to the display weight factor;
and the display module is used for sequencing the target hospitals according to the relevance and displaying the hospital information and/or the display weight factor corresponding to the target hospitals after sequencing according to a preset dimension on an interactive interface of a client.
9. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the data processing method according to any one of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the data processing method according to any one of claims 1 to 7.
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