CN111178069B - Data processing method, device, computer equipment and storage medium - Google Patents
Data processing method, device, computer equipment and storage medium Download PDFInfo
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- CN111178069B CN111178069B CN201911359223.6A CN201911359223A CN111178069B CN 111178069 B CN111178069 B CN 111178069B CN 201911359223 A CN201911359223 A CN 201911359223A CN 111178069 B CN111178069 B CN 111178069B
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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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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 illness characteristic information of the user information; when the matching information of the item to be matched is successfully matched with the key information, determining hospital information matched with the key information; generating display weight factors of target hospitals corresponding to each item of hospital information by using a lucene component, and determining the association degree among user information, matching information and hospital information of the target hospitals according to the display weight factors; and sorting all target hospitals according to the association degree, and displaying hospital information and/or display weight factors corresponding to all target hospitals after sorting on the interactive interface. The target hospital displayed in the interactive interface is matched with the user information and the illness characteristic information, so that the suitability 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, apparatus, computer device, and storage medium.
Background
Medical resources are a very important resource in the health insurance industry. Whether a user can enjoy a good medical service after purchasing a health insurance product becomes an important factor for selecting insurance companies by the user, and is also a competitive focus of each insurance company. At present, insurance companies can pay automatically through a computer pay system or an application program on a mobile terminal, but pay-able hospital information generated on the computer pay system or the mobile terminal is not associated with a user type or a disease type, so that the hospital information cannot have a definite guiding function on selecting a target hospital when a user treats the disease, and further, the user cannot accurately know the association relationship among each insurance product, the hospital information and the user. On the one hand, the user can carry out repeated manual consultation with staff of an insurance company on the follow-up treatment and payment and other processing flows, thereby bringing inconvenience to the claim settlement work, reducing the claim settlement efficiency of automatic claim settlement through a computer claim payment system or a mobile terminal, wasting human resources and bringing extremely bad user experience to the user; on the other hand, the user may randomly select a hospital to treat in the hospital information, and the randomly selected hospital may not have pertinence to the user disease, may delay the symptomatic treatment of the user, further result in aggravation of the user disease, and may increase the payoff amount of the insurance company.
Therefore, finding a technical solution that can analyze the association relationship among insurance products, hospital information and user information through big data and generate the most accurate and most suitable hospital information of the target hospital of the user is a urgent need for those skilled in the art.
Disclosure of Invention
Based on the foregoing, it is necessary to provide a data processing method, apparatus, computer device and storage medium for recommending a target hospital with high fitness and accuracy to a user after analyzing user information, matching information and hospital information by big data, so that the user can select the target hospital and then improve the experience effect of the user.
A data processing method, comprising:
receiving a recommendation instruction containing user information, and inquiring a to-be-matched item from a database according to identity information in the user information;
extracting key information from the illness 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 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 display weight factors of target hospitals corresponding to each item of hospital information in the matching list by using a lucene component, and determining the degree of association among the user information, the matching information and the hospital information of the target hospitals according to the display weight factors;
and sorting all the target hospitals according to the association degree, and displaying the hospital information and/or the display weight factors corresponding to the sorted target hospitals according to the preset dimension on an interactive interface of the client.
A data processing apparatus comprising:
the receiving module is used for receiving a recommendation instruction containing user information and inquiring items to be matched from the database according to the identity information in the user information;
the extraction module is used for extracting key information from the illness characteristic information of the user information;
the generation module is used for acquiring the 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;
The determining module is used for generating display weight factors of the target hospitals corresponding to each item of 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 hospitals according to the display weight factors;
and the display module is used for sorting all the target hospitals according to the association degree, and displaying the hospital information and/or the display weight factors corresponding to the sorted target hospitals according to a preset dimension on an interactive interface of the client.
A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the data processing method described above when executing the computer program.
A computer readable storage medium storing a computer program which, when executed by a processor, implements the data processing method described above.
The data processing method, the data processing device, the computer equipment and the storage medium extract key information from the illness 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 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 display weight factors of target hospitals corresponding to each item of hospital information in the matching list by using a lucene component, and determining the degree of association among the user information, the matching information and the hospital information of the target hospitals according to the display weight factors; and sorting all the target hospitals according to the association degree, and displaying the hospital information and/or the display weight factors corresponding to the sorted target hospitals according to the preset dimension on an interactive interface of the client. At this time, the interactive interface at the client is displayed according to a preset dimension, that is, each page in the interactive interface displays the hospital information (such as the name of the hospital, the main treatment subjects of the hospital, etc.) and/or the display weight factors (such as the geographic factors, the pay factors of insurance, etc.), and the hospital information of the target hospital in each page is sorted according to the suitability (association degree) after analyzing the user information, the matching information and the hospital information. Therefore, a user can conveniently watch and sort the target hospitals which are most suitable for the items to be matched (insurance products) associated with the identity information of the user in the interactive interface of the client, so that the confusion of the user in selecting the target hospitals can be reduced, and the situation of wasting human resources caused by subsequent repeated consultation is avoided; and the target hospital selected by the user is matched with the disease characteristic information contained in the self identity information, namely the selected target hospital has pertinence, so that the user can treat symptoms in the selected target hospital, on one hand, the disease 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 of the cost about treatment to the maximum degree through displaying the weight factor (the payment factor of insurance), and on the other hand, the payment amount of the insurance company for additional expenditure for illness delay 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 that are needed in the description of the embodiments of the present invention will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of 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 a data processing method step S40 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 in accordance with an embodiment of the invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The data processing method provided by the invention can be applied to an application environment as shown in fig. 1, wherein a client communicates with a server through a network. The clients may be, but are not limited to, various personal computers, notebook computers, smart phones, tablet computers, and portable wearable devices. The server may be implemented as a stand-alone server or as a server cluster composed of a plurality of servers.
In one embodiment, as shown in fig. 2, a data processing method is provided, and the method is applied to the server in fig. 1, and includes the following steps S10-S50:
s10, receiving a recommendation instruction containing user information, and inquiring a to-be-matched item from a database according to identity information in the user information;
after the user triggers the recommendation command of the hospital through the button, the server receives the recommendation command, and simultaneously obtains user information matched with the user from a preset storage database, and queries at least one item to be matched in the database associated with each cooperation company according to the identity information (including name, identification card number, home address, etc.) in the user information, wherein the item to be matched is a product item associated with each hospital, for example, the product item is an insurance product of each cooperation insurance company, including an insurance product of health insurance.
S20, extracting key information from the illness characteristic information of the user information;
it is understood that the disease feature information is medical record information obtained from databases associated with various hospital systems, and is associated with user information and stored in a preset storage database, at this time, key information in the disease feature information can be directly extracted from the preset storage database according to rules for identifying a fixed module, for example, the disease feature information is medical record information of a user in a hospital, at this time, a specific academic name (common cold, fever, etc.) of a disease suffered by the user can be directly extracted when the disease module position (the above-mentioned fixed template position, information or identifier associated with the fixed template position, such as a name of the disease suffered by the user, a star identifier, etc.) in the medical record information is identified.
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;
As can be appreciated, 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 item information of the insurance product, the item information may be responsibility item related to disease, etc.), where each product item is associated with a product contract or a product specification (in electronic form), so that the product information corresponding to the product contract or the product specification can be directly obtained through the product contract or the product specification; a plurality of various hospital information associated with the items to be matched exist in the hospital information list; the hospital information is hospital data after washing and labeling, and thus 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 of public hospitals or private hospitals, three-level special hospitals, three-level first hospitals, three-level second hospitals, three-level third hospitals, two-level first hospitals, two-level second hospitals, two-level third hospitals, etc., a non-rated hospital, a limited social security point hospital, overseas hospitals, etc.
Specifically, firstly, 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 a module where the keywords are located can be extracted (for example, the matching information of the module where the keywords are located can be directly extracted when the user suffers from various diseases in the items to be matched can be identified, and all the matching information in the items to be matched is divided by a plurality of modules; then matching the matching information with the key information (namely, matching the disease type recorded in the matching information and the specific academic name of the disease suffered by the user), and when the matching is successful (in another embodiment, when the matching fails, the matching information of the item to be matched is determined not to have the function of guaranteeing the disease characteristic information), inquiring a hospital information list associated with the matching information from a 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; finally, the hospital information matched with the key information can be further determined through the association 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 is determined, so that a 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 the server to determine the hospital information matched with the key information can be reduced, and the workload of the server can be reduced.
Further, the obtaining, by the semantic model, the matching information of the item to be matched, and when the matching information is successfully matched with the key information, traversing and querying a hospital information list associated with the matching information and the database, 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 of the items to be matched corresponds to one of the matching information;
when the number of the matching information is one and the matching information is successfully matched with the key information, traversing and querying the hospital information list related to the database and the matching information, 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 information fails to match with the key information, 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 related to the database and all the matching information, acquiring each group of matching data formed by the hospital information matched by each matching information, acquiring the overlapped hospital information in each group of matching data, and determining the overlapped hospital information as the hospital information matched with the key information. In another embodiment, 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 composed of the hospital information matched by each matching information from the hospital information list associated with the matching information by the database, and selecting the hospital information with the highest matching degree from the matching data and determining the hospital information as the hospital information matched with the key information when the hospital information overlapped in each group of matching data is not acquired; the matching degree is hospital information which is most suitable for the key information is determined from each group of matching data, and comprises the steps of determining scores of the conditions of clinic ranking, hospital ranking, expert ranking and the like of treatment key information in the hospital information, and finally calculating the matching degree of each hospital information and the key information through the scores.
In this embodiment, since one item to be matched corresponds to one piece of 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 two or more items to be matched, the number of pieces of matching information acquired from the items to be matched can be determined to be 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 and the key information can be matched, and when the matching is successful, the key information can be related to the item to be matched, and hospital information matched with the key information can be determined. In this embodiment, the number of pieces of matching information acquired from the items to be matched can be determined to determine the hospital information matching the key information, so that the determined hospital information will be more consistent with the key information, and an integrated recommendation effect can be also provided to the user (when there are more than two items to be matched associated with the identity information in the user information, that is, when the number of pieces of matching information of the items to be matched is more than two, one hospital information most suitable for the key information of the user is determined).
Further, the traversing querying the hospital information list associated with the matching information by the database, and before determining the hospital information matching the key information, further includes:
collecting hospital data of all hospitals in a preset data acquisition mode, performing data check on all the hospital data, and then performing data cleaning to obtain cleaned hospital data;
and labeling the cleaned hospital data, and recording each hospital data labeled by each hospital as the hospital information of the hospital.
Understandably, the preset data acquisition mode includes a web crawler or a manual collection mode; the data cleaning process is used for carrying out re-examination and verification on all hospital data, and aims to delete repeated information, correct existing errors and ensure consistency of the hospital data, and a specific implementation mode can be realized by setting cleaning rules or manual integration processing, wherein the cleaning rules can comprise duplicate removal processing and the like; labeling specifically can screen or summarize representative keywords from hospital data after washing.
In this embodiment, all collected hospital data of 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 convenience is brought to users in checking.
S40, generating display weight factors of target hospitals corresponding to each item of hospital information in the matching list by using a lucene component, and determining the degree of association among the user information, the matching information and the hospital information of the target hospitals according to the display weight factors;
as can be appreciated, displaying the weighting factor refers to setting the order component to generate and present important hospital information about the target hospital and the importance level of the portion of the important hospital information using the correspondence between the user information, the matching information, and the respective hospital information in the matching list, such as twenty percent importance level of the target hospital (one hundred percent importance level of the target hospital ranked in the third order, eighty percent importance level of the target hospital ranked in the second order, etc.), twenty percent importance level of the clinic ranking of the treatment key information of the target hospital (one hundred percent importance level of the target hospital ranked in the first order, etc.), twenty percent importance level of the evaluation information of the target hospital (one hundred percent importance level of the evaluation information in the good order, etc.), the association of the target hospital with the item to be matched (i.e. the user pays a good insurance product at the target hospital, the method can also be used as an insurance claim factor, wherein the insurance claim factor comprises full claim, partial claim and the like, the importance degree is twenty percent, the importance degree of the distance between a target hospital and a user (namely the geographical factor mentioned below) is ten percent, the other importance degrees are ten percent and the like, and the importance degree can be set according to requirements; the association degree refers to calculating the weight value (the importance degree occupied by all important hospital information in the weight factors is calculated through addition operation) of the user information, the matching information and the target hospital (the user information, the matching information and the hospital information of the target hospital have a corresponding relationship, namely, one user information corresponds to at least one matching information, and one matching relationship corresponds to at least one hospital information of the target hospital, so that once the important hospital information of one target hospital is determined through the preset weight factor, the association degree between the important hospital information of the target hospital can be determined through the preset weight factor, the above mentioned association relationship is established through the data map component), the weight value is suitable for sorting the target hospitals, and the association degree can reflect the suitability of the target hospitals and users 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 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, which are established through a data map component, by utilizing the lucene component, and carrying out documenting processing on each group of the user information, the matching information and the hospital information of the target hospital by utilizing 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 to obtain a first target word element after word segmentation;
s403, inputting the first target word into a preset language processing component in the lucene component for filtering and summarizing to obtain a second target word;
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 word element;
S405, after the key information is input to the lucene component, matching the key information with the index key information in the index file, and when matching is successful, acquiring the display weight factor output by a first data interface associated with the lucene component and related to the target hospital.
Understandably, the lucene component is a tool with a full text search function, and can add an index to a system program of the server, and then search target information through the index; a data graph component is a logic that is established by a continuous relationship between data and can output all data information associated with a data, i.e., the data graph component has written a data relationship. The first data interface is for transmitting out data of the display weighting factors of the target hospital in the lucene component.
In this embodiment, the correspondence established by the data map component can intuitively and accurately correlate the user information, the matching information and the hospital information in the target hospital, and once one of the data is determined, other data corresponding to the data correlation can be quickly queried, so that the operation efficiency of the server can be increased; after the key information is input to the lucene component, the hospital information of the target hospital can be queried according to the corresponding relation between the user information, the matching information and the hospital information in the matching list, but because the lucene component sets important hospital information, the first data interface associated with the lucene component outputs all hospital information corresponding to the target hospital, but the important hospital information corresponding to the target hospital (namely, the weight factors are displayed). Therefore, the embodiment can present important information for the user to watch, and is also convenient for setting the weight relation (namely the above-mentioned association degree) 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 a memory index, and placing the deleted index file to be updated into a memory document deleting 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 the 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 with the new index file into the hard disk index, and confirming that the updating of the index file is completed.
It will be appreciated that, since each index file is stored in the database and the update identifier (such as the number) has already been associated with all index files in the database, the index file can be determined by querying the update identifier, for example, the index file associated with the number 1 is the index file to be updated. At this time, the index file to be updated can be queried from the database through the number 1; after deleting the index file to be updated corresponding to the update identification in the database, a new index file corresponding to the update identification (after determining the update identification of the index file to be updated, the update identification can be associated with the new index file in advance) can be added into the database
In this embodiment, the index file in the database may be updated in time, so that an invalid index file to be updated may be removed, and thus in the process of matching the key information with the index key information in the index file, the lucene component may be utilized to generate a targeted display weight factor.
Further, the user information comprises a first geographic position of the user; the display weight factor includes a geographic factor; in the step S40, the generating, by using a lucene component, a display weight factor of the target hospital corresponding to each piece of hospital information in the matching list includes:
and acquiring a second geographic position of each target hospital in hospital information of the target hospital, calculating a third geographic position of a phase 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 user information can trigger the recommendation instruction of the hospital by the user and then acquire the first geographical position of the user information by the positioning function of the client; the second geographic position of each target hospital can be acquired through online crawling in advance, and data of the second geographic position are stored in hospital information. The third geographic location is an actual distance between the first geographic location and the second geographic location determined by various traffic means (including but not limited to walking, driving, buses and subways), that is, the above-mentioned geographic factors may be displayed as the actual distance between the first geographic location and the second geographic location in various traffic means, or may be displayed as the actual distance between the first geographic location and the second geographic location in a common traffic means.
The geographic factor in this embodiment is used as one of the pre-weighting factors, and is displayed on the interactive interface of the client for the user to check the distance between the target hospital and the user.
S50, sorting all the target hospitals according to the association degree, and displaying the hospital information and/or the display weight factors corresponding to the sorted target hospitals according to the preset dimension on an interactive interface of the client.
It can be understood that the determined association degree is also a ranked weight value, and the target hospitals can be ranked on the interactive interface of the client by the size of the weight value (wherein, the higher the size of the weight value, the earlier the ranking order, the higher the suitability of the target hospitals and the user information is indicated by the earlier ranking, so 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 a preset dimension, that is, each page in the interactive interface displays the hospital information (such as the name of the hospital, the main treatment subjects of the hospital, etc.) and/or the display weight factors (such as the geographic factors, the pay factors of insurance, etc.), and the hospital information of the target hospital in each page is sorted according to the suitability (association degree) after analyzing the user information, the matching information and the hospital information. Therefore, the user can conveniently select a target hospital which is most suitable for the item to be matched and is associated with the self identity information after watching the sorting, so that the user experience can be increased, on one hand, the doubt of the user for selecting the target hospital can be reduced, and on the other hand, the user can obtain the payment of the cost generated by treatment to the maximum degree through displaying the weight factor (the insurance payment factor), and on the other hand, the payment amount of the insurance company for additional expenditure for illness delay is indirectly reduced due to the pertinence of the selected target hospital.
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 the target hospital has diagnosis information matched with the identity information of the user or not through a second data interface associated with the target hospital;
when the doctor information matched with the identity information of the user exists, the evaluation information is sent to a preset person for verification, and after verification is correct, the association degree corresponding to the target hospital is adjusted according to the evaluation information.
Understandably, the evaluation information is that after the user triggers a preset time period of a recommendation instruction of the hospital, the server automatically generates a piece of corresponding information for prompting to rate and feeds the information back to the client associated with the user. The second data interface is a clinic system associated with the target hospital.
In this embodiment, the evaluation information fed back by the user for one target hospital is acquired first, and then whether the target hospital has the diagnosis information matched with the identity information of the user is queried, so that the situation that the user performs malicious evaluation without visiting the target hospital can be avoided, and therefore the fairness of the sorting (the above-mentioned association degree) of each target hospital can be ensured. When the doctor information matched with the identity information of the user exists, the doctor information is verified by a preset person, and the situation that the user performs malicious evaluation can be further avoided.
Further, in the step S50, after displaying the hospital information and/or the display weight factor corresponding to each target hospital after the sorting according to the preset dimension on the interactive interface of the client, the method further includes:
and after acquiring a display instruction triggered by the user in the interactive interface aiming at one target hospital, enabling the interactive interface to display all the cleaned hospital data associated with the target hospital.
Understandably, the main page of the interactive interface of the client has hospital information and/or display weight factors corresponding to a target hospital with a plurality of preset dimensions, alternatively, one preset dimension may correspond to one hospital information and/or display weight factor, and one sub-dimension exists in one preset dimension, and all the cleaned hospital data associated with the target hospital exists in each sub-dimension.
In this embodiment, after the user triggers the display instruction for one target hospital in the interactive interface, the user can clearly view all the cleaned hospital data associated with the target hospital, so that the user's knowledge of the target hospital can be enhanced, and a reference for further judgment is provided for the user.
In summary, the above provides a data processing method, which extracts key information from the disease 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 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 display weight factors of target hospitals corresponding to each item of hospital information in the matching list by using a lucene component, and determining the degree of association among the user information, the matching information and the hospital information of the target hospitals according to the display weight factors; and sorting all the target hospitals according to the association degree, and displaying the hospital information and/or the display weight factors corresponding to the sorted target hospitals according to the preset dimension on an interactive interface of the client. At this time, the interactive interface at the client is displayed according to a preset dimension, that is, each page in the interactive interface displays the hospital information (such as the name of the hospital, the main treatment subjects of the hospital, etc.) and/or the display weight factors (such as the geographic factors, the pay factors of insurance, etc.), and the hospital information of the target hospital in each page is sorted according to the suitability (association degree) after analyzing the user information, the matching information and the hospital information. Therefore, a user can conveniently watch and sort the target hospitals which are most suitable for the items to be matched (insurance products) associated with the identity information of the user in the interactive interface of the client, so that the confusion of the user in selecting the target hospitals can be reduced, and the situation of wasting human resources caused by subsequent repeated consultation is avoided; and the target hospital selected by the user is matched with the disease characteristic information contained in the self identity information, namely the selected target hospital has pertinence, so that the user can treat symptoms in the selected target hospital, on one hand, the disease 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 of the cost about treatment to the maximum degree through displaying the weight factor (the payment factor of insurance), and on the other hand, the payment amount of the insurance company for additional expenditure for illness delay is indirectly reduced due to the pertinence of the selected target hospital.
It should be understood that the sequence number of each step in the foregoing embodiment does not mean that the execution sequence of each process should be determined by the function and the internal logic, and should not limit the implementation process of the embodiment of the present invention.
In one embodiment, a data processing apparatus is provided, where the data processing apparatus corresponds to the data processing method in the above embodiment one by 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 displaying module 15. The functional modules are described in detail as follows:
the receiving module 11 is used for receiving a recommendation instruction containing user information, and inquiring items to be matched from a database according to identity information in the user information;
an extracting module 12, configured to extract key information from the disease 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, and when the matching information is successfully matched with the key information, traverse and query a hospital information list associated with the matching information of the database, 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 hospital information in the matching list, and determine a degree of association 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 15 is configured to sort the target hospitals according to the association degree, and display, on an interactive interface of the client, the hospital information and/or the display weight factor corresponding to the sorted target hospitals according to a preset dimension.
Further, the generating module includes:
a first determining submodule, configured to determine the number of matching information acquired from the item to be matched through the semantic model; one of the items to be matched corresponds to one of the matching information;
the second determining submodule is used for traversing and inquiring the hospital information list related to the database and the matching information when the number of the matching information is one and the matching information and the key information are successfully matched, and determining the hospital information matched with the key information;
and the third determining submodule is used for traversing and inquiring the hospital information list related to 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 by each matching information, acquiring the overlapped hospital information in each group of matching data, and determining the overlapped 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 in a preset data acquisition mode, performing data cleaning after data checking on all the hospital data, and obtaining the cleaned hospital data;
and the recording module is used for labeling the cleaned hospital data and recording each hospital data labeled by 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 are established through the data map component, by utilizing the lucene component, and obtaining a target document after the user information, the matching information and the hospital information of the target hospital, which are in each group, are subjected to documenting processing by utilizing the lucene component;
the second processing sub-module is used for inputting the target document into a preset word segmentation component in the lucene component to perform word segmentation processing to obtain a first target word element after word segmentation processing;
The third processing sub-module is used for inputting the first target word element into a preset language processing component in the lucene component to carry out filtering and summarization processing to obtain a second target word element;
an input sub-module, configured to input the second target word element to 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 word element;
and the matching sub-module is used for matching the key information with the index key information in the index file after inputting the key information into the lucene component, and acquiring the display weight factor which is output by a first data interface associated with the lucene component and related to the target hospital 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 a memory index, and storing the deleted index file to be updated in a memory document deleting list;
The adding module is used for obtaining a new index file according to the update 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 confirmation module is used for merging the memory index added with the new index file into the hard disk index and confirming that the updating of the index file is completed.
Further, the determining module includes:
and the acquisition sub-module 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 of the phase 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 for one target hospital according to the feedback request, and querying whether the target hospital has the 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 a preset person for verification when the diagnosis information matched with the identity information of the user exists, and adjusting the association degree corresponding to the target hospital according to the evaluation information after verification is correct.
For specific limitations of the data processing apparatus, reference may be made to the above limitations of the data processing method, and no further description is given here. Each of the modules in the above-described data processing apparatus may be implemented in whole or in part by software, hardware, and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above 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 includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. 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 that includes a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the computer program to implement the steps of the data processing method in the above embodiment, such as steps S10 to S50 shown in fig. 2. Alternatively, the processor, when executing a computer program, implements the functions of the modules/units of the data processing apparatus in the above embodiments, such as the functions of the modules 11 to 15 shown in fig. 4. In order to avoid repetition, a description thereof is omitted.
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 embodiment, such as steps S10 to S50 shown in fig. 2. Alternatively, the computer program, when executed by a processor, 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. In order to avoid repetition, a description thereof is omitted.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile 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), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions.
The above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the 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 scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention, and are intended to be included in the scope of the present invention.
Claims (9)
1. A method of data processing, comprising:
receiving a recommendation instruction containing user information, and inquiring a to-be-matched item from a database according to identity information in the user information;
Extracting key information from the illness 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 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 step of obtaining the matching information of the item to be matched through the semantic model, and when the matching information is successfully matched with the key information, traversing and inquiring a hospital information list associated with the database and the matching information, and determining the hospital information matched with the key information comprises the following steps:
determining the quantity of the matching information acquired from the item to be matched through the semantic model; one of the items to be matched corresponds to one of the matching information;
when the number of the matching information is one and the matching information is successfully matched with the key information, traversing and querying 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 more than two and the matching information is successfully matched with the key information, traversing and inquiring the hospital information list related to the database and all the matching information, acquiring each group of matching data formed by the hospital information matched by each matching information, acquiring the overlapped hospital information in each group of matching data, and determining the overlapped hospital information as the hospital information matched with the key information;
generating display weight factors of target hospitals corresponding to each item of hospital information in the matching list by using a lucene component, and determining the degree of association among the user information, the matching information and the hospital information of the target hospitals according to the display weight factors;
and sorting all the target hospitals according to the association degree, and displaying the hospital information and/or the display weight factors corresponding to the sorted target hospitals according to the preset dimension on an interactive interface of the client.
2. The data processing method of claim 1, wherein the traversing queries the database for a list of hospital information associated with the matching information, prior to determining hospital information matching the key information, further comprising:
Collecting hospital data of all hospitals in a preset data acquisition mode, performing data check on all the hospital data, and then performing data cleaning to obtain cleaned hospital data;
and labeling the cleaned hospital data, and recording each hospital data labeled by each hospital as the hospital information of the hospital.
3. The data processing method according to claim 1, wherein the generating, with the lucene component, a display weight factor of a target hospital corresponding to each of the hospital information in the matching list includes:
acquiring the corresponding relation between the user information, the matching information and the hospital information in the target hospital, which are established through a data map component, by utilizing the lucene component, and carrying out documenting processing on each group of the user information, the matching information and the hospital information of the target hospital by utilizing the lucene component to obtain a target document;
inputting the target document to a preset word segmentation component in the lucene component for word segmentation to obtain a first target word element after word segmentation;
Inputting the first target word element into a preset language processing component in the lucene component for filtering and summarizing to obtain a second target word element;
inputting the second target word element 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 word element;
after the key information is input to the lucene component, the key information is matched with the index key information in the index file, and when the matching is successful, the display weight factor about the target hospital is obtained and output through a first data interface associated with the lucene component.
4. A data processing method according to claim 3, wherein after obtaining an index file generated by the preset 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 a memory index, and placing the deleted index file to be updated into a memory document deleting 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 the 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 with the new index file into the hard disk index, and confirming that the updating of the index file is completed.
5. The data processing method of claim 1, wherein the user information includes a first geographic location of a location of the user; the display weight factor includes a geographic factor; the generating, by the lucene component, a display weight factor of a target hospital corresponding to each of the hospital information in the matching list, including:
and acquiring a second geographic position of each target hospital in hospital information of the target hospital, calculating a third geographic position of a phase 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.
6. The data processing method according to claim 1, wherein after the sorting of the target hospitals according to the association degree and displaying the hospital information and/or the display weight factors corresponding to the sorted target hospitals according to a preset dimension on the interactive interface of the 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 the target hospital has diagnosis information matched with the identity information of the user or not through a second data interface associated with the target hospital;
when the doctor information matched with the identity information of the user exists, the evaluation information is sent to a preset person for verification, and after verification is correct, the association degree corresponding to the target hospital is adjusted according to the evaluation information.
7. A data processing apparatus, comprising:
the receiving module is used for receiving a recommendation instruction containing user information and inquiring items to be matched from the database according to the identity information in the user information;
the extraction module is used for extracting key information from the illness characteristic information of the user information;
the generation module is used for acquiring the 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;
The generating module is further configured to:
determining the quantity of the matching information acquired from the item to be matched through the semantic model; one of the items to be matched corresponds to one of the matching information;
when the number of the matching information is one and the matching information is successfully matched with the key information, traversing and querying 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 more than two and the matching information is successfully matched with the key information, traversing and inquiring the hospital information list related to the database and all the matching information, acquiring each group of matching data formed by the hospital information matched by each matching information, acquiring the overlapped hospital information in each group of matching data, and determining the overlapped hospital information as the hospital information matched with the key information;
the determining module is used for generating display weight factors of the target hospitals corresponding to each item of 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 hospitals according to the display weight factors;
And the display module is used for sorting all the target hospitals according to the association degree, and displaying the hospital information and/or the display weight factors corresponding to the sorted target hospitals according to a preset dimension on an interactive interface of the client.
8. 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 of claims 1 to 6 when executing the computer program.
9. A computer-readable storage medium storing a computer program, characterized in that the computer program, when executed by a processor, implements the data processing method according to any one of claims 1 to 6.
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| CN112559578A (en) * | 2020-12-18 | 2021-03-26 | 深圳赛安特技术服务有限公司 | Data processing method and device, electronic equipment and storage medium |
| CN112509685B (en) * | 2020-12-31 | 2021-09-03 | 曜立科技(北京)有限公司 | Standardized system for screening operation modes |
| CN112990669A (en) * | 2021-02-24 | 2021-06-18 | 平安健康保险股份有限公司 | Product data analysis method and device, computer equipment and storage medium |
| CN112989021B (en) * | 2021-03-05 | 2024-02-09 | 上海明略人工智能(集团)有限公司 | Method, device and equipment for advisor behavior violation determination |
| CN113553306B (en) * | 2021-07-27 | 2023-07-21 | 重庆紫光华山智安科技有限公司 | Data processing method and data storage management system |
| CN113657809A (en) * | 2021-08-31 | 2021-11-16 | 平安医疗健康管理股份有限公司 | Hospital portrait construction method, device, equipment and storage medium |
| CN113764089A (en) * | 2021-09-09 | 2021-12-07 | 平安科技（深圳）有限公司 | Binding method, device, equipment and storage medium for hospital for treatment |
| CN116091253B (en) * | 2023-04-07 | 2023-08-08 | 北京亚信数据有限公司 | Medical insurance wind control data acquisition method and device |
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