CN109726390B - Document processing method, device, electronic equipment and storage medium - Google Patents
Document processing method, device, electronic equipment and storage medium Download PDFInfo
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Abstract
The disclosure discloses a document processing method, a document processing device, electronic equipment and a storage medium. The method comprises the following steps: acquiring a first document issued by a user, and determining the type of the first document; selecting a second document of the same type as the first document from the database; acquiring quality evaluation information obtained by a first document in preset time, and acquiring quality evaluation information obtained by a second document in preset time; performing quality evaluation on the first document and the second document according to the quality evaluation information of the first document and the second document; and generating recommendation information according to the quality evaluation result, and providing the recommendation information for readers. The method can score the quality by finding the documents of the same type from the database, can help readers to quickly find the high-quality documents in the related fields while improving the creation quality of the documents, meets the requirements of users, and improves the use experience of the users, thereby improving the viscosity between the users and the products.
Description
Technical Field
The present disclosure relates to the field of computer technologies, and in particular, to a document processing method, a document processing device, an electronic device, and a computer readable storage medium.
Background
At present, the creation is more and more popular, the culture exchange is more and more frequent, and the information acquisition modes of people are also rich and various. The text creation platform is also used for generating various sounds and borboriding. But the quality level of the creation is uneven while the content and the platform are rich, so that the document recommended to the reader by the document recommendation system may be poor in quality, the requirements of users cannot be met, the user experience is poor, and the viscosity between the users and the products is reduced.
Disclosure of Invention
The disclosure provides a document processing method, a device, electronic equipment and a storage medium, which can solve the technical problem that in the prior art, due to uneven creation quality level, a document recommended to a reader by a document recommendation system is likely to be poor in quality and cannot meet the requirements of users, so that the viscosity between the users and products is reduced.
An embodiment of a first aspect of the present disclosure provides a document processing method, including: acquiring a first document issued by a user, and determining the type of the first document; selecting a second document of the same type as the first document from a database; acquiring quality evaluation information of the first document in a preset time, and acquiring quality evaluation information of the second document in the preset time; performing quality evaluation on the first document and the second document according to the quality evaluation information of the first document and the second document; and generating recommendation information according to the quality evaluation result, and providing the recommendation information for readers.
According to the document processing method, a first document issued by a user can be obtained, the type of the first document is determined, a second document which is the same as the first document is selected from a database, then quality evaluation information of the first document and quality evaluation information of the second document which are obtained in preset time are obtained, then quality evaluation is carried out on the first document and the second document according to the quality evaluation information of the first document and the quality evaluation information of the second document, recommendation information is generated according to the quality evaluation result, and the recommendation information is provided for readers, so that the readers can read the document with higher creation level, an auxiliary system screens high-quality documents for recommendation, and the readers can be helped to quickly find related field high-quality documents while the creation quality of the document is improved, the use experience of the users is improved, and therefore the viscosity between the users and the products is improved.
In one embodiment of the present disclosure, before the selecting the second document of the same type as the first document from the database, the method further includes: determining a user level of the user; judging whether the user grade meets a preset grade or not; if yes, executing the step of selecting a second document which is the same as the first document from the database.
In one embodiment of the present disclosure, the performing quality evaluation on the first document and the second document according to quality evaluation information of the first document and the second document includes: calculating a quality score of the first document according to the quality rating information of the first document; calculating a quality score of the second document according to the quality rating information of the second document; and performing quality evaluation on the first document and the second document according to the quality scores of the first document and the second document.
In one embodiment of the present disclosure, the quality rating information includes a praise number, a comment number, a focus number, and a reading amount; wherein, the liquid crystal display device comprises a liquid crystal display device,
in an embodiment of the disclosure, the calculating the quality score of the first document according to the quality rating information of the first document includes: calculating the praise score of the first document according to the praise number of the first document and the scoring rule corresponding to the praise dimension; calculating comment scores of the first document according to the comment quantity of the first document and a scoring rule corresponding to comment dimensions; calculating the attention score of the first document according to the attention quantity of the first document and the scoring rule corresponding to the attention dimension; according to the reading quantity of the first document and the scoring rule corresponding to the reading dimension, calculating the reading score of the first document; calculating a quality score of the first document according to the praise score, the comment score, the attention score and the reading score of the first document;
The calculating the quality score of the second document according to the quality rating information of the second document comprises the following steps: calculating the praise score of the second document according to the praise number of the second document and the scoring rule corresponding to the praise dimension; calculating comment scores of the second document according to the comment quantity of the second document and a scoring rule corresponding to comment dimensions; calculating the attention score of the second document according to the attention quantity of the second document and the scoring rule corresponding to the attention dimension; according to the reading quantity of the second document and the scoring rule corresponding to the reading dimension, calculating the reading score of the second document; and calculating the quality score of the second document according to the praise score, the comment score, the attention score and the reading score of the second document.
In one embodiment of the present disclosure, the performing quality rating on the first document and the second document according to the quality scores of the first document and the second document includes: comparing the quality score of the first document to the quality score of the second document; if the quality score of the first document is greater than or equal to the quality score of the second document, determining that the quality of the first document is higher than the quality of the second document; and if the quality score of the first document is smaller than the quality score of the second document, judging that the quality of the second document is higher than that of the first document.
In one embodiment of the disclosure, the generating recommendation information according to the quality rating result includes: when the quality of the first document is higher than that of the second document, obtaining user information of the user, and generating recommendation information according to the user information, the first document and quality rating information of the first document; and when the quality of the second document is higher than that of the first document, acquiring the user information of the issuing user of the second document, and generating the recommendation information according to the user information of the issuing user, the second document and the quality rating information of the second document.
An embodiment of a second aspect of the present disclosure proposes a document processing apparatus including: the document acquisition module is used for acquiring a first document issued by a user; a type determining module for determining a type of the first document; the document selection module is used for selecting a second document which is the same as the first document from the database; the information acquisition module is used for acquiring quality evaluation information of the first document in a preset time and acquiring quality evaluation information of the second document in the preset time; the quality evaluation module is used for performing quality evaluation on the first document and the second document according to the quality evaluation information of the first document and the second document; and the recommending module is used for generating recommending information according to the quality comparison result and providing the recommending information for readers.
According to the document processing device, a first document issued by a user can be acquired through the document acquisition module, the type determination module determines the type of the first document, the document selection module selects a second document of the same type as the first document from the database, the information acquisition module acquires quality evaluation information obtained by the first document in preset time and acquires quality evaluation information obtained by the second document in preset time, the quality evaluation module performs quality evaluation on the first document and the second document according to the quality evaluation information of the first document and the second document, the recommendation module generates recommendation information according to the quality evaluation result and provides the recommendation information to a reader, so that the reader can read the document with higher creation level, the auxiliary system screens the high-quality document for recommendation, and the reader can be helped to quickly find the high-quality document in the relevant field while meeting the user requirement and improving the use experience of the user by finding the documents of the same type in the database for quality grading.
In one embodiment of the present disclosure, the apparatus further comprises: a user grade determining module, configured to determine a user grade of the user before selecting a second document of the same type as the first document from a database; the judging module is used for judging whether the user grade meets a preset grade or not; the document selection module is specifically configured to: and when the user grade is judged to meet the preset grade, selecting a second document which is the same as the first document from a database.
In one embodiment of the disclosure, the quality assessment module is specifically configured to: calculating a quality score of the first document according to the quality rating information of the first document; calculating a quality score of the second document according to the quality rating information of the second document; and performing quality evaluation on the first document and the second document according to the quality scores of the first document and the second document.
In one embodiment of the present disclosure, the quality rating information includes a praise number, a comment number, a focus number, and a reading amount; the quality evaluation module is specifically used for:
calculating the praise score of the first document according to the praise number of the first document and the scoring rule corresponding to the praise dimension; calculating comment scores of the first document according to the comment quantity of the first document and a scoring rule corresponding to comment dimensions; calculating the attention score of the first document according to the attention quantity of the first document and the scoring rule corresponding to the attention dimension; according to the reading quantity of the first document and the scoring rule corresponding to the reading dimension, calculating the reading score of the first document; calculating a quality score of the first document according to the praise score, the comment score, the attention score and the reading score of the first document;
Calculating the praise score of the second document according to the praise number of the second document and the scoring rule corresponding to the praise dimension; calculating comment scores of the second document according to the comment quantity of the second document and a scoring rule corresponding to comment dimensions; calculating the attention score of the second document according to the attention quantity of the second document and the scoring rule corresponding to the attention dimension; according to the reading quantity of the second document and the scoring rule corresponding to the reading dimension, calculating the reading score of the second document; and calculating the quality score of the second document according to the praise score, the comment score, the attention score and the reading score of the second document.
In one embodiment of the disclosure, the quality assessment module is specifically configured to:
comparing the quality score of the first document to the quality score of the second document; if the quality score of the first document is greater than or equal to the quality score of the second document, determining that the quality of the first document is higher than the quality of the second document; and if the quality score of the first document is smaller than the quality score of the second document, judging that the quality of the second document is higher than that of the first document.
In one embodiment of the disclosure, the recommendation module is specifically configured to:
when the quality of the first document is higher than that of the second document, obtaining user information of the user, and generating recommendation information according to the user information, the first document and quality rating information of the first document; and when the quality of the second document is higher than that of the first document, acquiring the user information of the issuing user of the second document, and generating the recommendation information according to the user information of the issuing user, the second document and the quality rating information of the second document.
An embodiment of a third aspect of the present disclosure provides an electronic device, including: the document processing system comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor realizes the document processing method according to the embodiment of the first aspect of the disclosure when executing the computer program.
An embodiment of a fourth aspect of the present disclosure proposes a computer-readable storage medium, on which a computer program is stored, which when executed by a processor implements a document processing method according to an embodiment of the first aspect of the present disclosure.
Additional aspects and advantages of the disclosure will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the disclosure.
Drawings
The foregoing and/or additional aspects and advantages of the present disclosure will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings, in which:
FIG. 1 is a flow chart of a document processing method provided by an embodiment of the present disclosure;
FIG. 2 is a schematic diagram of a document processing apparatus according to an embodiment of the present disclosure;
fig. 3 is a schematic structural diagram of an electronic device for executing a document processing method according to an embodiment of the present disclosure.
Detailed Description
Embodiments of the present disclosure are described in detail below, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to like or similar elements or elements having like or similar functions throughout. The embodiments described below by referring to the drawings are exemplary and intended for the purpose of explaining the present disclosure and are not to be construed as limiting the present disclosure.
Document processing methods, apparatuses, electronic devices, and computer-readable storage media of embodiments of the present disclosure are described below with reference to the accompanying drawings.
FIG. 1 is a flow chart of a document processing method provided by an embodiment of the present disclosure. Note that the document processing method of the embodiment of the present disclosure may be applied to the document processing apparatus of the embodiment of the present disclosure, which may be configured on an electronic device. For example, the electronic device may be a device capable of implementing a document processing function, such as a server.
As shown in fig. 1, the document processing method may include:
step 101, a first document issued by a user is acquired, and the type of the first document is determined.
Optionally, when the confirmation of the release by the user is monitored, the document released by the user can be obtained, and the label of the document is determined according to the content of the document, wherein the label is the type of the document, such as software-back-end-java, food-canteen, automobile-car-praise-germane, and the like, that is, the type can be understood as the minimum category divided in the field.
Step 102, selecting a second document of the same type as the first document from the database.
Specifically, according to the type of the first document, the database may be searched to find the document with the same type, and the document with the same type as the first document may be used as the second document. It should be noted that, in one embodiment of the present disclosure, when searching from the database to find out that the documents identical to the type are plural according to the type of the first document, one may be randomly selected from the plural documents as the second document, or the document located at the first position among the plural documents may be selected as the second document.
In order to ensure the quality level of the document and reduce the computing resource of the system, the grade of the user can be set, and the document issued by the user is allowed to be compared with other documents in the database when the grade of the user reaches the preset grade. Optionally, in an embodiment of the present disclosure, before selecting the second document of the same type as the first document from the database, a user level of the user may be determined, and whether the user level meets a preset level may be determined, and if yes, the step of selecting the second document of the same type as the first document from the database is performed.
That is, when a user edits and issues a document, a document of a same type may be found from the database for quality evaluation, and before a document of a same type is found from the database, it may be determined whether the user's level reaches a preset level, for example, 50 levels, if the preset level is not reached, it indicates that the quality of the document edited by the user is poor, it is not necessary to perform quality evaluation on the document, and it is not necessary to provide the document as recommendation information to readers, thereby reducing the computing resources of the system while guaranteeing the quality level of the document. If the user grade is judged to reach the preset grade, the quality of the document authored by the user can be considered to be higher, and the quality of the document issued by the user and the same type of document in the database can be subjected to quality evaluation, so that recommendation information is determined according to the quality evaluation result, and the quality level of the document is ensured.
In embodiments of the present disclosure, user ratings may be upgraded based on empirical values. For example, a class full level of 100, a 0 to 1 level requires 10 points of experience, a 1 to 2 level requires 20 points of experience, and so on. The empirical value can be obtained by: issuing a document with more than 1000 words, and acquiring 100-point experience; the published document obtains a praise to obtain 10 experiences; check in to get 10 experiences a day, get 20 experiences a day 2, and so on, get 100 experiences a day at most. Thus, the user's level may be upgraded by obtaining an empirical value.
And step 103, obtaining quality evaluation information of the first document obtained in a preset time, and obtaining quality evaluation information of the second document obtained in the preset time.
Optionally, counting the quality rating information obtained by the first document in a preset time, and counting the quality rating information obtained by the second document in the preset time. For example, taking a preset time of 7 days as an example, quality rating information accumulated in 7 days of the first document and quality rating information accumulated in 7 days of the second document may be acquired.
And 104, performing quality evaluation on the first document and the second document according to the quality evaluation information of the first document and the second document.
Optionally, the quality score of the first document is calculated according to the quality rating information of the first document, the quality score of the second document is calculated according to the quality rating information of the second document, and the quality ratings of the first document and the second document are compared according to the quality scores of the first document and the second document.
As one example, the quality rating information may include, but is not limited to, number of praise, number of comments, number of attention, and amount of reading. In this example, the specific implementation process of calculating the quality score of the first document according to the quality rating information of the first document may be as follows: the method comprises the steps of calculating the praise score of a first document according to the praise number of the first document and the scoring rule corresponding to the praise dimension, calculating the comment score of the first document according to the comment number of the first document and the scoring rule corresponding to the comment dimension, calculating the attention score of the first document according to the attention number of the first document and the scoring rule corresponding to the attention dimension, calculating the reading score of the first document according to the reading quantity of the first document and the scoring rule corresponding to the reading dimension, and finally calculating the quality score of the first document according to the praise score, the comment score, the attention score and the reading score of the first document.
That is, the score in each dimension may be calculated according to the number of praise, the number of comments, the number of attention and the reading amount of the first document and the scoring rule corresponding to the four dimensions, and finally, the scores in each dimension may be summed to obtain the quality score of the first document. For example, assume that the scoring rules for each dimension are as follows: the praise 10 score, the comment 20 score, the attention 20 score and the reading quantity 3 score are obtained on the assumption that the first document obtains 'praise 10, comment 5, attention 5 and reading quantity 100' in a preset time (such as 7 days), and according to the praise quantity, the comment quantity, the attention quantity and the reading quantity of the first document and the scoring rules corresponding to the four dimensions, the quality score of the first document can be calculated, namely 10×10+5×20+5×20+100×3=600.
In this example, according to the quality rating information of the second document, a specific implementation procedure of calculating the quality rating of the second document may be as follows: calculating the praise score of the second document according to the praise number of the second document and the scoring rule corresponding to the praise dimension, calculating the comment score of the second document according to the comment number of the second document and the scoring rule corresponding to the comment dimension, calculating the attention score of the second document according to the attention number of the second document and the scoring rule corresponding to the attention dimension, calculating the reading score of the second document according to the reading quantity of the second document and the scoring rule corresponding to the reading dimension, and calculating the quality score of the second document according to the praise score, the comment score, the attention score and the reading score of the second document.
That is, the score in each dimension may be calculated according to the number of praise, the number of comments, the number of attention and the reading amount of the second document and the scoring rule corresponding to the four dimensions, and finally, the scores in each dimension may be summed to obtain the quality score of the second document. For example, assume that the scoring rules for each dimension are as follows: the praise 10 score, the comment 20 score, the attention 20 score and the reading quantity 3 score, and the second document is assumed to obtain 'praise 5, comment 3, attention 10 and reading quantity 150' in a preset time (such as 7 days), and the quality score of the second document can be calculated according to the praise number, the comment number, the attention number and the reading quantity of the second document and the scoring rules corresponding to the four dimensions, namely, 5×10+3×20+10×10+150×3=700.
In this step, when the quality scores of the first document and the second document are obtained, the quality scores of the first document and the second document may be compared with each other. As one example, the quality score of the first document may be compared to the quality score of the second document by size, and if the quality score of the first document is greater than or equal to the quality score of the second document, the quality of the first document is determined to be higher than the quality score of the second document; if the quality score of the first document is less than the quality score of the second document, it is determined that the quality of the second document is higher than the first document.
And 105, generating recommendation information according to the quality evaluation result, and providing the recommendation information to readers.
Specifically, a document with better quality can be selected from the first document and the second document according to the quality evaluation result, and corresponding recommendation information is generated according to the document and related information thereof, so that the recommendation information is provided for a reader, the reader can read the document with higher creation level, and the auxiliary system screens the high-quality document for recommendation.
As an example, when the quality of the first document is higher than that of the second document, user information of the user may be acquired, and recommendation information may be generated according to the user information, the first document, and the quality rating information of the first document; when the quality of the second document is higher than that of the first document, the user information of the issuing user of the second document can be acquired, and recommendation information is generated according to the user information of the issuing user, the second document and the quality rating information of the second document.
That is, when the quality of the first document is higher than that of the second document as a result of the quality evaluation, user information such as a user name or nickname of the user who issued the first document may be acquired, and the user information, the first document, and the quality evaluation information of the first document (such as the number of praise, the number of comments, the number of attention, the reading amount, and the like) may be provided as recommendation information to the reader. When the quality of the second document is higher than that of the first document as a result of the quality evaluation, user information, such as a user name or a nickname, of the user who issued the second document may be acquired, and the user information who issued the second document, and the quality evaluation information (such as the number of praise, the number of comments, the number of attention, the reading amount, and the like) of the second document may be provided as recommendation information to the reader. Therefore, the documents with better quality in the first document and the second document and the related information thereof are recommended to the reader through the quality evaluation result, and the reader can be helped to quickly find the related-field high-quality documents.
According to the document processing method, a first document issued by a user can be obtained, the type of the first document is determined, a second document which is the same as the first document is selected from a database, then quality evaluation information of the first document and quality evaluation information of the second document which are obtained in preset time are obtained, then quality evaluation is carried out on the first document and the second document according to the quality evaluation information of the first document and the quality evaluation information of the second document, recommendation information is generated according to the quality evaluation result, and the recommendation information is provided for readers, so that the readers can read the document with higher creation level, an auxiliary system screens high-quality documents for recommendation, and the readers can be helped to quickly find related field high-quality documents while the creation quality of the document is improved, the use experience of the users is improved, and therefore the viscosity between the users and the products is improved.
In order to stimulate the authors to create high quality documents, the two documents may be scored according to the quality rating results of the documents, and the documents may be ranked according to the scores of the documents, thereby stimulating the authors to create the desire according to the ranking of the documents, and stimulating the authors to create high quality documents. Specifically, in embodiments of the present disclosure, after comparing the quality score of a first document with the quality score of a second document in size, if the quality score of the first document is greater than or equal to the quality score of the second document, the quality of the first document may be considered higher than the quality score of the second document, at which time the first document may be added with a quality score, a quality score failure score may be deducted from the second document, e.g., a 10 score may be added to the first document, and a 10 score may be deducted from the second document. If the quality score of a first document is less than the quality score of a second document, the quality of the second document may be considered higher than the first document, at which time a quality score may be added to the second document, a quality score failure score may be subtracted from the first document, e.g., a score of 10 may be added to the second document, and a score of 10 may be subtracted from the first document. Thus, the scores of the documents can be obtained through the quality evaluation, and then the documents can be ranked through the scores of each document, so that the author is stimulated to create the desire according to the ranks of the documents, and the author is stimulated to create the high-quality documents.
In correspondence with the document processing methods provided in the above-described several embodiments, an embodiment of the present disclosure also provides a document processing apparatus, and since the document processing apparatus provided in the embodiment of the present disclosure corresponds to the document processing method provided in the above-described several embodiments, implementation of the foregoing document processing method is also applicable to the document processing apparatus provided in the embodiment, and will not be described in detail in the embodiment. Fig. 2 is a schematic diagram of a document processing apparatus according to an embodiment of the present disclosure. As shown in fig. 2, the document processing apparatus 200 may include: a document acquisition module 210, a type determination module 220, a document selection module 230, an information acquisition module 240, a quality review module 250, and a recommendation module 260.
Specifically, the document acquisition module 210 is configured to acquire a first document published by a user.
The type determination module 220 is used to determine the type of the first document.
The document selection module 230 is configured to select a second document of the same type as the first document from the database.
The information obtaining module 240 is configured to obtain quality rating information obtained by the first document in a preset time, and obtain quality rating information obtained by the second document in the preset time.
The quality evaluation module 250 is configured to perform quality evaluation on the first document and the second document according to quality evaluation information of the first document and the second document. For example, quality score module 250 may calculate a quality score for the first document based on the quality score information for the first document; calculating a quality score of the second document according to the quality rating information of the second document; and performing quality evaluation on the first document and the second document according to the quality scores of the first document and the second document.
In one embodiment of the present disclosure, the quality rating information includes a praise number, a comment number, a focus number, and a reading amount. Wherein, in the embodiment of the present disclosure, the quality evaluation module 250 is specifically configured to:
calculating the praise score of the first document according to the praise number of the first document and the scoring rule corresponding to the praise dimension; calculating comment scores of the first document according to the comment quantity of the first document and a scoring rule corresponding to comment dimensions; calculating the attention score of the first document according to the attention quantity of the first document and the scoring rule corresponding to the attention dimension; according to the reading quantity of the first document and the scoring rule corresponding to the reading dimension, calculating the reading score of the first document; and calculating the quality score of the first document according to the praise score, the comment score, the attention score and the reading score of the first document.
In an embodiment of the present disclosure, the quality assessment module 250 is specifically configured to: calculating the praise score of the second document according to the praise number of the second document and the scoring rule corresponding to the praise dimension; calculating comment scores of the second document according to the comment quantity of the second document and a scoring rule corresponding to comment dimensions; calculating the attention score of the second document according to the attention quantity of the second document and the scoring rule corresponding to the attention dimension; according to the reading quantity of the second document and the scoring rule corresponding to the reading dimension, calculating the reading score of the second document; and calculating the quality score of the second document according to the praise score, the comment score, the attention score and the reading score of the second document.
In one embodiment of the present disclosure, the quality assessment module 250 is specifically configured to: comparing the quality score of the first document to the quality score of the second document; if the quality score of the first document is greater than or equal to the quality score of the second document, determining that the quality of the first document is higher than the quality of the second document; and if the quality score of the first document is smaller than the quality score of the second document, judging that the quality of the second document is higher than that of the first document.
The recommendation module 260 is used for generating recommendation information according to the quality evaluation result and providing the recommendation information to the reader. As an example, recommendation module 260 is specifically configured to: when the quality of the first document is higher than that of the second document, obtaining user information of the user, and generating recommendation information according to the user information, the first document and quality rating information of the first document; and when the quality of the second document is higher than that of the first document, acquiring the user information of the issuing user of the second document, and generating the recommendation information according to the user information of the issuing user, the second document and the quality rating information of the second document.
In one embodiment of the present disclosure, the document processing apparatus may further include: the user grade determining module and the judging module. The user grade determining module is used for determining the user grade of the user before selecting a second document which is the same as the first document from the database; the judging module is used for judging whether the user grade meets a preset grade. In an embodiment of the disclosure, the document selection module is specifically configured to: and when the user grade is judged to meet the preset grade, selecting a second document which is the same as the first document from a database.
According to the document processing device disclosed by the embodiment of the disclosure, the first document issued by the user can be acquired through the document acquisition module, the type determination module determines the type of the first document, the document selection module selects the second document of the same type as the first document from the database, the information acquisition module acquires the quality evaluation information of the first document obtained in the preset time and acquires the quality evaluation information of the second document obtained in the preset time, the quality evaluation module performs quality evaluation on the first document and the second document according to the quality evaluation information of the first document and the second document, the recommendation module generates recommendation information according to the quality evaluation result and provides the recommendation information to readers, so that the readers can read the document with higher creation level, the auxiliary system screens the high-quality document for recommendation, and the readers can be helped to quickly find related high-quality documents in the field while the creation quality of the document is improved, the user requirements are met, and the use experience of the user is improved, and therefore the viscosity between the user and the product is improved.
In order to achieve the above embodiments, an embodiment of the present disclosure further provides an electronic device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, when executing the computer program, for:
Acquiring a first document issued by a user, and determining the type of the first document; selecting a second document of the same type as the first document from the database; acquiring quality evaluation information obtained by a first document in preset time, and acquiring quality evaluation information obtained by a second document in preset time; performing quality evaluation on the first document and the second document according to the quality evaluation information of the first document and the second document; and generating recommendation information according to the quality evaluation result, and providing the recommendation information for readers.
To achieve the above embodiments, the present disclosure further proposes a non-transitory computer-readable storage medium having stored thereon a computer program to be executed by a processor for:
acquiring a first document issued by a user, and determining the type of the first document; selecting a second document of the same type as the first document from the database; acquiring quality evaluation information obtained by a first document in preset time, and acquiring quality evaluation information obtained by a second document in preset time; performing quality evaluation on the first document and the second document according to the quality evaluation information of the first document and the second document; and generating recommendation information according to the quality evaluation result, and providing the recommendation information for readers.
Referring now to fig. 3, a schematic diagram of an electronic device (e.g., a terminal device or server in fig. 1) 300 suitable for use in implementing embodiments of the present disclosure is shown. The terminal devices in the embodiments of the present disclosure may include, but are not limited to, mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and the like, and stationary terminals such as digital TVs, desktop computers, and the like. The electronic device shown in fig. 3 is merely an example and should not be construed to limit the functionality and scope of use of the disclosed embodiments.
As shown in fig. 3, the electronic device 300 may include a processing means (e.g., a central processing unit, a graphics processor, etc.) 301 that may perform various suitable actions and processes in accordance with a program stored in a Read Only Memory (ROM) 302 or a program loaded from a storage means 308 into a Random Access Memory (RAM) 303. In the RAM 303, various programs and data required for the operation of the electronic apparatus 300 are also stored. The processing device 301, the ROM 302, and the RAM 303 are connected to each other via a bus 304. An input/output (I/O) interface 305 is also connected to bus 304.
In general, the following devices may be connected to the I/O interface 305: input devices 306 including, for example, a touch screen, touchpad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; an output device 307 including, for example, a Liquid Crystal Display (LCD), a speaker, a vibrator, and the like; storage 308 including, for example, magnetic tape, hard disk, etc.; and communication means 309. The communication means 309 may allow the electronic device 300 to communicate with other devices wirelessly or by wire to exchange data. While fig. 3 shows an electronic device 300 having various means, it is to be understood that not all of the illustrated means are required to be implemented or provided. More or fewer devices may be implemented or provided instead.
In particular, according to embodiments of the present disclosure, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method shown in the flowcharts. In such an embodiment, the computer program may be downloaded and installed from a network via a communication device 309, or installed from a storage device 308, or installed from a ROM 302. The above-described functions defined in the methods of the embodiments of the present disclosure are performed when the computer program is executed by the processing means 301.
It should be noted that the computer readable medium described in the present disclosure may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this disclosure, a computer-readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present disclosure, however, the computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, with the computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, fiber optic cables, RF (radio frequency), and the like, or any suitable combination of the foregoing.
The computer readable medium may be contained in the electronic device; or may exist alone without being incorporated into the electronic device.
The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to: acquiring a first document issued by a user, and determining the type of the first document; selecting a second document of the same type as the first document from a database; acquiring quality evaluation information of the first document in a preset time, and acquiring quality evaluation information of the second document in the preset time; performing quality evaluation on the first document and the second document according to the quality evaluation information of the first document and the second document; and generating recommendation information according to the quality evaluation result, and providing the recommendation information for readers.
Computer program code for carrying out operations of the present disclosure may be written in one or more programming languages, including an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units involved in the embodiments of the present disclosure may be implemented by means of software, or may be implemented by means of hardware. The name of the unit does not in any way constitute a limitation of the unit itself, for example the first acquisition unit may also be described as "unit acquiring at least two internet protocol addresses".
Claims (9)
1. A document processing method, comprising:
acquiring a first document issued by a user, and determining the type of the first document;
selecting a second document of the same type as the first document from a database; wherein the type is the minimum category divided in the field;
acquiring quality evaluation information of the first document in a preset time, and acquiring quality evaluation information of the second document in the preset time;
performing quality evaluation on the first document and the second document according to the quality evaluation information of the first document and the second document;
selecting a document with high quality score from the first document and the second document according to the quality evaluation result to generate recommendation information, and providing the recommendation information for readers;
wherein before the selecting the second document of the same type as the first document from the database, the method further comprises:
determining a user level of the user;
judging whether the user grade meets a preset grade or not;
if yes, executing the step of selecting a second document which is the same as the first document from the database.
2. The document processing method according to claim 1, wherein the performing quality evaluation on the first document and the second document based on quality evaluation information of the first document and the second document includes:
Calculating a quality score of the first document according to the quality rating information of the first document;
calculating a quality score of the second document according to the quality rating information of the second document;
and performing quality evaluation on the first document and the second document according to the quality scores of the first document and the second document.
3. The document processing method according to claim 2, wherein the quality rating information includes a praise number, a comment number, a focus number, and a reading amount;
the calculating the quality score of the first document according to the quality rating information of the first document comprises the following steps:
calculating the praise score of the first document according to the praise number of the first document and the scoring rule corresponding to the praise dimension;
calculating comment scores of the first document according to the comment quantity of the first document and a scoring rule corresponding to comment dimensions;
calculating the attention score of the first document according to the attention quantity of the first document and the scoring rule corresponding to the attention dimension;
according to the reading quantity of the first document and the scoring rule corresponding to the reading dimension, calculating the reading score of the first document;
Calculating a quality score of the first document according to the praise score, the comment score, the attention score and the reading score of the first document;
the calculating the quality score of the second document according to the quality rating information of the second document comprises the following steps:
calculating the praise score of the second document according to the praise number of the second document and the scoring rule corresponding to the praise dimension;
calculating comment scores of the second document according to the comment quantity of the second document and a scoring rule corresponding to comment dimensions;
calculating the attention score of the second document according to the attention quantity of the second document and the scoring rule corresponding to the attention dimension;
according to the reading quantity of the second document and the scoring rule corresponding to the reading dimension, calculating the reading score of the second document;
and calculating the quality score of the second document according to the praise score, the comment score, the attention score and the reading score of the second document.
4. A document processing method according to claim 2 or 3, wherein said performing a quality rating on said first document and said second document based on a quality rating of said first document and said second document comprises:
Comparing the quality score of the first document to the quality score of the second document;
if the quality score of the first document is greater than or equal to the quality score of the second document, determining that the quality of the first document is higher than the quality of the second document;
and if the quality score of the first document is smaller than the quality score of the second document, judging that the quality of the second document is higher than that of the first document.
5. The document processing method according to claim 1, wherein the selecting a document having a high quality score from the first document and the second document according to the quality rating result generates recommendation information, comprising:
when the quality of the first document is higher than that of the second document, obtaining user information of the user, and generating recommendation information according to the user information, the first document and quality rating information of the first document;
and when the quality of the second document is higher than that of the first document, acquiring the user information of the issuing user of the second document, and generating the recommendation information according to the user information of the issuing user, the second document and the quality rating information of the second document.
6. A document processing apparatus, comprising:
the document acquisition module is used for acquiring a first document issued by a user;
a type determining module for determining a type of the first document;
the document selection module is used for selecting a second document which is the same as the first document from the database; wherein the type is the minimum category divided in the field;
the information acquisition module is used for acquiring quality evaluation information of the first document in a preset time and acquiring quality evaluation information of the second document in the preset time;
the quality evaluation module is used for performing quality evaluation on the first document and the second document according to the quality evaluation information of the first document and the second document;
the recommendation module is used for selecting a document with high quality score from the first document and the second document according to the quality comparison result to generate recommendation information, and providing the recommendation information for readers;
wherein the apparatus further comprises:
the grade determining module is used for determining the user grade of the user;
the grade judging module is used for judging whether the user grade meets a preset grade or not;
And the document selection module is also used for executing the step of selecting the second document which is the same as the first document from the database if the first document is the same as the second document.
7. The document processing device of claim 6, wherein the recommendation module is specifically configured to:
when the quality of the first document is higher than that of the second document, obtaining user information of the user, and generating recommendation information according to the user information, the first document and quality rating information of the first document;
and when the quality of the second document is higher than that of the first document, acquiring the user information of the issuing user of the second document, and generating the recommendation information according to the user information of the issuing user, the second document and the quality rating information of the second document.
8. An electronic device, comprising: memory, a processor and a computer program stored on the memory and executable on the processor, which processor, when executing the computer program, implements the document processing method according to any one of claims 1 to 5.
9. A computer-readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the document processing method according to any one of claims 1 to 5.
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| CN111193795B (en) * | 2019-12-30 | 2021-07-02 | 腾讯科技（深圳）有限公司 | Information pushing method and device, electronic equipment and computer readable storage medium |
| CN111212300B (en) * | 2020-01-09 | 2022-10-04 | 北京字节跳动网络技术有限公司 | Online document processing method and device, electronic equipment and storage medium |
| CN112163399A (en) * | 2020-10-12 | 2021-01-01 | 北京字跳网络技术有限公司 | Online document pushing method and device, electronic equipment and computer readable medium |
| CN112561334A (en) * | 2020-12-16 | 2021-03-26 | 咪咕文化科技有限公司 | Grading method and device for reading object, electronic equipment and storage medium |
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| CN102521377B (en) * | 2011-12-19 | 2014-02-05 | 刘松涛 | Method and system for screening high-quality documents from document collection of document processing system |
| US9727652B2 (en) * | 2013-07-22 | 2017-08-08 | International Business Machines Corporation | Utilizing dependency among internet search results |
| CN105488151A (en) * | 2015-11-27 | 2016-04-13 | 小米科技有限责任公司 | Reference document recommendation method and apparatus |
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| CN107239537A (en) * | 2017-06-01 | 2017-10-10 | 福建中金在线信息科技有限公司 | A kind of method of document display, device, electronic equipment and readable storage medium storing program for executing |
| CN107463645A (en) * | 2017-07-21 | 2017-12-12 | 雷锤智能科技南京有限公司 | The personalized recommendation system and its recommendation method being oriented to based on user property scoring |
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