CN111143516A - Article search result display method and related device - Google Patents
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Abstract
The application provides an article search result display method and a related device, and relates to the technical field of data display. The method comprises the steps of firstly obtaining first keywords to be searched, then preprocessing the first keywords to be searched to generate one or more target words, then determining multiple pieces of target articles from a database according to the target words, scoring each piece of target articles according to the target words to obtain a first score of each piece of target articles, then determining a second score of each piece of target articles according to historical access records, and finally summing the first score and the second score of each piece of target articles to obtain a total score of each piece of target articles, and displaying the multiple pieces of target articles according to the magnitude order of the total scores. The article search result display method and the related device have the advantages that the final display sequence is more suitable for the use requirements of the user, and the experience of the user is higher.
Description
Technical Field
The present application relates to the field of data display technologies, and in particular, to a method and a related apparatus for displaying article search results.
Background
At present, for internet enterprises, it is very important to make timely and accurate response to a search request made by a user, and the experience of the user can be influenced.
Generally, after a user proposes a keyword to be searched, the system automatically searches a responsive article and pushes the article to the user. However, at present, the analysis results are generally sorted directly according to the matching scores, the sorting is relatively fixed, and the experience of the user is poor.
In summary, at present, the ranking of the article search results is relatively fixed, so that the experience of the user is relatively poor.
Disclosure of Invention
The application aims to provide an article search result display method and a related device, and the method and the related device are used for solving the problems that in the prior art, the sequence of the article search results is relatively fixed, and the experience of a user is relatively poor.
In order to achieve the above purpose, the embodiments of the present application employ the following technical solutions:
in a first aspect, an embodiment of the present application provides a method for displaying article search results, where the method includes:
acquiring a first keyword to be searched;
preprocessing the first keywords to be searched to generate one or more target words;
determining a plurality of pieces of target articles from a database according to the target words, and scoring each piece of target article according to the target words to obtain a first score of each piece of target article;
determining a second score of each piece of the target article according to a historical access record, wherein the historical access record comprises the accessed times and/or the accessed time length of each piece of the target article;
and summing the first score and the second score of each target article to obtain a total score of each target article, and displaying the multiple target articles according to the magnitude order of the total scores.
Further, the step of determining multiple pieces of target articles from the database according to the target word, and scoring each piece of target article according to the target word to obtain a first score of each piece of target article includes:
acquiring title scores and content scores of each piece of target articles according to the target words;
and summing the title score and the content score to obtain the first score.
Further, before the step of determining multiple pieces of target articles from the database according to the target word and scoring each piece of target article according to the target word to obtain a first score of each piece of target article, the method further includes:
preprocessing each article to obtain a plurality of second keywords of each article;
calculating the weight of each second keyword according to a TextRank algorithm;
the step of determining a plurality of target articles from the database according to the target words comprises the following steps:
determining an article corresponding to the second keyword and the target word as a target article;
the step of scoring each piece of the target articles according to the target words to obtain a first score of each piece of the target articles comprises:
obtaining title scores according to the number of second keywords corresponding to the target words contained in the titles of each piece of target article;
and acquiring content scores according to the weight of the second keyword corresponding to the target word contained in the content of each piece of target article.
Further, the step of preprocessing the first keyword to be searched to generate one or more target words includes:
performing word segmentation processing on the first keyword to obtain at least one word to be analyzed;
performing filtering word parking processing on the at least one word to be analyzed;
and carrying out synonym transformation on the processed words to be analyzed so as to determine one or more target words.
In a second aspect, an embodiment of the present application further provides an article search result display apparatus, where the apparatus includes:
the data acquisition module is used for acquiring a first keyword to be searched;
the data processing module is used for preprocessing the first keyword to be searched to generate one or more target words;
the data processing module is further used for determining multiple pieces of target articles from a database according to the target words and scoring each piece of target article according to the target words to obtain a first score of each piece of target article;
the data processing module is further used for determining a second score of each piece of the target article according to a historical access record, wherein the historical access record comprises the accessed times and the accessed duration of each piece of the target article;
and the data processing module is further used for summing the first score and the second score of each target article to obtain a total score of each target article, and displaying the multiple target articles according to the size sequence of the total scores.
Further, the data processing module is further configured to obtain a title score and a content score of each target article according to the target word, and sum the title score and the content score to obtain the first score.
Further, the data processing module is further used for preprocessing each article to obtain a plurality of second keywords of each article; calculating the weight of each second keyword according to a TextRank algorithm;
the data processing module is further used for determining that the article corresponding to the second keyword and the target word is a target article;
the data processing module is further used for obtaining title scores according to the number of second keywords corresponding to the target words contained in the titles of each piece of target articles; and acquiring content scores according to the weight of the second keyword corresponding to the target words contained in the content of each piece of target article.
Further, the data processing module is further configured to perform word segmentation processing on the first keyword to obtain at least one word to be analyzed, perform filtering word parking processing on the at least one word to be analyzed, and perform synonym conversion on the processed word to be analyzed to determine one or more target words.
In a third aspect, an embodiment of the present application further provides an electronic device, including: a memory for storing one or more programs; a processor; when executed by the processor, the one or more programs implement the methods as described above.
In a fourth aspect, the present application further provides a computer-readable storage medium, on which a computer program is stored, where the computer program is executed by a processor to implement the method described above.
Now to prior art, this application has following beneficial effect:
the application provides an article search result display method and a related device, wherein first keywords to be searched are obtained, then the first keywords to be searched are preprocessed to generate one or more target words, then multiple pieces of target articles are determined from a database according to the target words, each piece of target article is scored according to the target words to obtain a first score of each piece of target article, then a second score of each piece of target article is determined according to a historical access record, the historical access record comprises the accessed times and the accessed duration of each piece of target article, finally the first score and the second score of each piece of target article are summed to obtain a total score of each piece of target article, and the multiple pieces of target articles are displayed in sequence according to the magnitude of the total score. Due to the fact that the ranking can be achieved through the sum of the first score and the second score, and the second score is determined according to the historical access record, the display sequence of the target article can be corrected through the behavior data of the user, the final display sequence can better meet the use requirements of the user, and the experience of the user is higher.
In order to make the aforementioned objects, features and advantages of the present application more comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and it will be apparent to those skilled in the art that other related drawings can be obtained from the drawings without inventive effort.
Fig. 1 is an interaction diagram of an electronic device according to an embodiment of the present disclosure.
Fig. 2 is a schematic block diagram of an electronic device according to an embodiment of the present disclosure.
Fig. 3 is a flowchart illustrating an article search result displaying method according to an embodiment of the present application.
Fig. 4 is a flowchart illustrating a sub-step of S104 in fig. 3 according to an embodiment of the present disclosure.
Fig. 5 is a flowchart illustrating a sub-step of S106 in fig. 3 according to an embodiment of the present disclosure.
Fig. 6 is another schematic flow chart of an article search result displaying method according to an embodiment of the present application.
Fig. 7 is a schematic block diagram of an article search result display apparatus according to an embodiment of the present application.
In the figure: 100-an electronic device; 101-a memory; 102-a processor; 103-a communication interface; 300-article search result presentation means; 310-a data acquisition module; 320-data processing module.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures. Meanwhile, in the description of the present application, the terms "first", "second", and the like are used only for distinguishing the description, and are not to be construed as indicating or implying relative importance.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
In the description of the present application, it should be noted that the terms "upper", "lower", "inner", "outer", and the like indicate orientations or positional relationships based on orientations or positional relationships shown in the drawings or orientations or positional relationships conventionally found in use of products of the application, and are used only for convenience in describing the present application and for simplification of description, but do not indicate or imply that the referred devices or elements must have a specific orientation, be constructed in a specific orientation, and be operated, and thus should not be construed as limiting the present application.
In the description of the present application, it is also to be noted that, unless otherwise explicitly specified or limited, the terms "disposed" and "connected" are to be interpreted broadly, e.g., as being either fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meaning of the above terms in the present application can be understood in a specific case by those of ordinary skill in the art.
Some embodiments of the present application will be described in detail below with reference to the accompanying drawings. The embodiments described below and the features of the embodiments can be combined with each other without conflict.
As described in the background art, in the current search result display of articles, after a user proposes a keyword to be searched, the system automatically searches for a responsive article and pushes the article to the user. However, the analysis results are sorted directly according to the matching scores, the sorting is relatively fixed, and the experience of the user is poor.
In view of this, the application provides an article search result display method, which determines a second score by using a historical behavior of a user, so as to realize an effect of correcting a final sequencing result, and the method is more suitable for user requirements, thereby improving user experience.
It should be noted that the article search result display method provided in the embodiment of the present application is applied to an electronic device 100, for example, referring to fig. 1, the electronic device 100 may be a server, the server is in communication connection with a plurality of user terminals and a database, and a user can send related search information to the server through the user terminals, then the server processes data, finds a target article, and pushes the target article to the user terminal for display. The user terminal includes but is not limited to a computer, a mobile phone, a smart wearable device and the like, and can realize data interaction.
Also, referring to fig. 2, the electronic device 100 includes a memory 101, a processor 102 and a communication interface 103, wherein the memory 101, the processor 102 and the communication interface 103 are directly or indirectly electrically connected to each other to realize data transmission or interaction. For example, the components may be electrically connected to each other via one or more communication buses or signal lines. The memory 101 may be used for storing software programs and modules, such as program instructions/modules of the corresponding task management scheduling device provided in the embodiments of the present application, and the processor 102 executes the software programs and modules stored in the memory 101, thereby executing various functional applications and data processing. The communication interface 103 may be used for communicating signaling or data with other node devices.
The Memory 101 may be, but is not limited to, a Random Access Memory 101 (RAM), a Read Only Memory 101 (ROM), a Programmable Read Only Memory 101 (PROM), an Erasable Read Only Memory 101 (EPROM), an electrically Erasable Read Only Memory 101 (EEPROM), and the like.
The processor 102 may be an integrated circuit chip having signal processing capabilities. The Processor 102 may be a general-purpose Processor 102, including a Central Processing Unit (CPU) 102, a Network Processor 102 (NP), and the like; but may also be a Digital Signal processor 102 (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware components.
It will be appreciated that the configuration shown in FIG. 2 is merely illustrative and that electronic device 100 may include more or fewer components than shown in FIG. 2 or have a different configuration than shown in FIG. 2. The components shown in fig. 2 may be implemented in hardware, software, or a combination thereof.
The following takes a server as an execution subject to exemplarily explain an article search result presentation method provided by the present application:
referring to fig. 3, the method for displaying search results of an article includes:
s102, obtaining a first keyword to be searched.
S104, preprocessing the first keyword to be searched to generate one or more target words.
S106, determining a plurality of pieces of target articles from the database according to the target words, and scoring each piece of target article according to the target words to obtain a first score of each piece of target article.
And S108, determining a second score of each piece of the target article according to the historical access record, wherein the historical access record comprises the accessed times and/or the accessed time length of each piece of the target article.
And S110, summing the first score and the second score of each piece of the target articles to obtain a total score of each piece of the target articles, and displaying the plurality of pieces of the target articles according to the size sequence of the total scores.
When searching of related articles is needed, a user can send a first keyword to be searched to a server through a terminal. The first keyword to be searched is information which the user wants to search. It may be a session, e.g., "how expensive the Guangzhou rented car is", or it may be a phrase, e.g., the user searches for "rent car"; alternatively, the first keyword to be searched may also be a plurality of phrases, such as "car rental in guangzhou", which is not limited in this application.
In addition, the method for the server to obtain the first keyword to be searched is not limited in this application. For example, a user may send a search request to the server by using a mobile phone, optionally, a corresponding app is installed in the mobile phone of the user, and after the app is opened by the user, a communication connection is formed between the electronic terminal and the server, and at this time, the user can implement a search. Or, the user may also use the first keyword to be searched sent by the computer, for example, the user accesses a corresponding web page through the computer and inputs the first keyword to be searched, thereby implementing data search.
After receiving the first keyword to be searched, the server determines one or more target keywords from the first keyword to be searched, then determines a plurality of pieces of target articles from the database according to the target words, scores each piece of target articles according to the target words to obtain a first score of each piece of target articles,
for example, if the first keyword to be searched input by the user is "how to rent car in Guangzhou", the server may determine that the target word is "Guangzhou, rent car, and charge" according to the first keyword to be searched, and then determine the multi-target keyword from the database by using the three target words. The database is stored with a plurality of articles in advance, and as an optional implementation manner, the articles in the database are increased in real time. For example, the server can crawl relevant articles in the industry and store them in a database.
After the server determines a plurality of pieces of target articles from the database according to the target words, for example, the articles containing the target words in the articles are determined as the target articles. And then scoring each piece of target articles according to the target words, and further acquiring a first score of each piece of target articles.
If the target articles are displayed in a sorted manner according to the first score, the sorted order of the target articles is relatively fixed, and therefore, in the application, the server further determines a second score of each piece of the target articles according to the historical access record, where the historical access record includes the accessed times and the accessed time length of each piece of the target articles, and of course, the historical access record may only include the accessed times or the accessed time length, which is not limited in this application. And then summing the first score and the second score of each piece of the target articles to obtain the total score of each piece of the target articles, and displaying the pieces of the target articles according to the size sequence of the total score. It will be appreciated that the server ranks articles according to the score of the articles from large to small.
Through the setting mode, the target articles can be sorted through the sum of the first score and the second score, and the second score is determined according to the historical access record, so that the display sequence of the target articles can be corrected by using the behavior data of the user, the final display sequence can better meet the use requirements of the user, and the experience of the user is higher.
Optionally, as an implementation manner of the present application, please refer to fig. 4, where S104 includes:
s1041, performing word segmentation processing on the first keyword to obtain at least one word to be analyzed.
S1042, filtering and parking the at least one word to be analyzed.
And S1043, performing synonym conversion on the processed words to be analyzed to determine one or more target words.
After receiving the first keyword to be searched, the server performs word segmentation processing on the first keyword, and optionally, the server may perform word segmentation processing on the first keyword by using the ending word segmentation.
For example, when the first keyword input by the user is "how to rent a car in Guangzhou", the server, after receiving the first keyword, may categorize the first keyword into "four words, namely" Guangzhou, car renting, charging, and how ".
The server then filters the segmented words to exclude unnecessary words, for example, for the above four words, since "how" is only a help word, which has little influence on the actual search result, the server removes the words, so that the words processed by the filtered parking words are "guangzhou, car rental, fee".
As an alternative implementation manner, a database connected to the server stores a plurality of preset filterable words, such as "do, wool," and the like. On the basis, after word segmentation processing is carried out by the server, all words after word segmentation processing are compared with the filterable words stored in the database, and then which words can be deleted are determined.
After the process of filtering the parked words is performed, if the search is performed directly according to the remaining words as the target words, there is a possibility that the search range is small. For example, if two words a and B are similar words, the word searched by the user is a, and then the article is a full-use B, then the server may not display B at this time, so that the search result may not be accurate enough.
In view of this, the server provided in the present application may further perform synonym transformation on the filtered parked words to be analyzed, so as to determine one or more target words. For example, a synonym for rental car is rental car, a synonym for charging is unit price, etc. By determining synonyms, the search results of the server can be made more comprehensive.
For example, if the analyzed word after the filtered parking word processing is A, B and a has the synonym C, the server determines the target article from the database according to A, B as a group of target words and B, C as a group of synonyms.
Certainly, in practical use, the user may also input only one word group, and on this basis, after the server performs the word segmentation processing and the filtering word parking processing, the obtained word is still the word itself.
As an alternative implementation, referring to fig. 5, S106 includes:
s1061, obtaining the title score and the content score of each target article according to the target words.
S1062, summing the title score and the content score to obtain a first score.
It can be understood that, when the server obtains the first score, after obtaining the target articles, the server obtains the title score and the content score of each target article according to the target words, and then sums the title score and the content score to obtain the first score.
Optionally, before S102, referring to fig. 6, the method further includes:
s101-1, preprocessing each article to obtain a plurality of second keywords of each article.
S101-2, calculating the weight of each second keyword according to the TextRank algorithm.
S106 includes:
s1063, determining the article corresponding to the second keyword and the target word as the target article.
S1064, obtaining the title score according to the number of the second keywords corresponding to the target words contained in the title of each piece of the target article.
S1065, obtaining content scores according to the weights of the second keywords corresponding to the target words contained in the content of each piece of target article.
That is, in the present application, after the server obtains the articles, each article of the articles is preprocessed to obtain a plurality of second keywords of each article. Each article comprises a title and a content, and as an optional implementation manner, the server respectively preprocesses the title and the content of each article to obtain a second keyword of the title and the content.
And then carrying out filtering and word-placing processing on the titles of the articles, and then carrying out synonym conversion, thereby obtaining a plurality of second keywords of the articles.
And for the preprocessing of the article content, word segmentation processing is firstly carried out, then filtering and parking word processing is carried out, and the weight of each second keyword is calculated according to the TextRank algorithm. The TextRank algorithm determines the weight of each second keyword based on the fact that if a word appears after many words, the greater the weight of the word, indicating that the word is important.
For example, in an article, if a phrase X appears 50 times in the article content and another phrase Y appears 40 times in the article content, however, the word preceding X is always a, and the word preceding Y is not only a, but also B, C, etc., and constitutes AY, BY, CY, etc., the weight of Y is also set higher, e.g., the weight of Y is set to 1 and the weight of X is set to 0.8.
Moreover, as a possible implementation manner of the present application, the number of the second keywords determined for each article is fixed, for example, the number of the second keywords determined for each article is 80, and 80 second keywords with the highest weight are selected as the second keywords of each article.
Therefore, after the server determines the target words input by the user, the target words are matched with the second keywords of each article in the database, and when the articles contain all the target words, the articles are taken as the target articles.
For example, when the determined target word is A, B, if the second keyword of an article is A, B, C, D. . . Then the article may be taken as the target article. And when the second keyword of an article is B, C, D. . . The article cannot be regarded as the target article.
After determining the target articles, the server also continues to calculate the first score for each of the target articles. In this application, the first score is the sum of the title score and the content score of each targeted article.
When calculating the title score, the number of the second keywords corresponding to the target word contained in the title of each target article can be determined. For example, the target word is A, B, and the title score of the first text article is 1 if the title of the first text article includes two target words, i.e., a and B; and the title of the second text article, which only contains A but not B, has a title score of 0.5.
And when the content score is calculated, the content score is obtained according to the weight of the second keyword corresponding to the target word contained in the content of each target article. For example, in the content of the first article, the weight of a is 0.5, the weight of B is 0.8, and the content score is 0.5+0.8=1.3, and in the content of the second article, the weight of a is 1, and the weight of B is 0.5, and the content score is 1+0.5= 1.5.
Further, the server may sum the title score and the content score to obtain a first score, for example, based on the above example, the first score of the first piece of text is 1+1.3=2.3, and the first score of the second piece of text is 0.5+1.5= 2.
Meanwhile, as a possible implementation manner of the present application, when the first score is calculated, since the importance of the title is greater than that of the content. Therefore, coefficients are also set for the title scores and the content scores of the articles, for example, the coefficient of the title score is 3, and the coefficient of the content score is 2, and based on the above example, the first score of the first volume article is 1 × 3+1.3 × 2=5.6, and the first score of the second volume article is 0.5 × 3+1.5 × 2= 4.5. Of course, the content score may be determined in other manners, for example, as another possible implementation manner of the present application, when the content score is calculated, the content score may also be obtained according to the number of the second keywords corresponding to the target word included in the content of each piece of the target article and the weight of the second keywords corresponding to the target word included in the content of the target article.
For example, when the determined target word is A, B, the content of the first text article includes two target words, a and B, and the weights of a and B are 0.5 and 0.8, respectively, the matching degree score is 1, and the weight score is (0.5+0.8)/2=0.65, the content score of the first text article is 0.65 + 1= 0.65. The content of the second text article only contains the target words a, and if the weight of a is 0.8, the matching degree score is 0.5, and the content score of the first text article is 0.8 by 0.5= 0.4.
And the server can bury points in the front-end page to further acquire and store the behavior data of the user, and then count and analyze the behavior data of the user to further determine a second score of each target article.
If all the target articles are directly ranked and displayed through the determined first scores, all the rankings are fixed. In view of this, the present application corrects the ranking of the target article by acquiring the historical behavior data of the user.
In one implementation, the server obtains the accessed times and the accessed time duration of each piece of the target articles, and further determines a second score of each piece of the target articles. For example, after determining multiple pieces of target articles and sequencing the articles, if the user browses the target articles with the longest browsing time at most and arranges the target articles in the third ranking, the server may determine the second score of the target articles to be 1, and for the target articles that the user has not browsed, the second score of the target articles to be 0.
Of course, the basis for determining the second score is not specifically limited in the present application, and for example, the second score of the target article that is browsed by the user after clicking for the first time after sorting may be the highest.
Second embodiment
On the basis of the foregoing embodiment, please refer to fig. 7, the present application further provides an article search result displaying apparatus 300, and each module in the article search result displaying apparatus 300 can be used to execute the task scheduling management method described above. The article search result presentation apparatus 300 includes:
the data obtaining module 310 is configured to obtain a first keyword to be searched.
The data processing module 320 is configured to pre-process the first keyword to be searched to generate one or more target words.
The data processing module 320 is further configured to determine multiple pieces of target articles from the database according to the target word, and score each piece of target article according to the target word to obtain a first score of each piece of target article.
The data processing module 320 is further configured to determine a second score of each piece of the target article according to a historical access record, where the historical access record includes the number of times each piece of the target article was accessed and the time duration of the access.
The data processing module 320 is further configured to sum the first score and the second score of each piece of the targeted articles to obtain a total score of each piece of the targeted articles, and display the pieces of the targeted articles in order according to the size of the total score.
The data processing module 320 is further configured to obtain a title score and a content score of each target article according to the target word, and sum the title score and the content score to obtain a first score.
The data processing module 320 is further configured to pre-process each article to obtain a plurality of second keywords of each article; calculating the weight of each second keyword according to a TextRank algorithm;
the data processing module 320 is further configured to determine that the article corresponding to the second keyword and the target word is a target article;
the data processing module 320 is further configured to obtain a title score according to the number of the second keywords corresponding to the target word included in the title of each piece of the target article; and acquiring content scores according to the weight of the second keywords corresponding to the target words contained in the content of each piece of target article.
The data processing module 320 is further configured to perform word segmentation processing on the first keyword to obtain at least one word to be analyzed, perform filtering word parking processing on the at least one word to be analyzed, and perform synonym transformation on the processed word to be analyzed to determine one or more target words.
Moreover, it should be noted that the electronic device 100 may be a general-purpose computer or a special-purpose computer, and both of them may be used to implement the article search result displaying method according to the embodiment of the present invention. Although only one computer is shown in embodiments of the invention, for convenience, the functions described herein may be implemented in a distributed fashion across multiple similar platforms to balance processing loads.
The embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by the processor 102, the method for displaying the search result of the article disclosed in the above embodiment is implemented.
In summary, the present application provides an article search result displaying method and a related apparatus, first obtaining a first keyword to be searched, then preprocessing the first keyword to be searched to generate one or more target words, then determining multiple target articles from a database according to the target words, scoring each target article according to the target words to obtain a first score of each target article, then determining a second score of each target article according to a historical access record, where the historical access record includes the number of times each target article is accessed and the time length of the accessed target article, and finally summing the first score and the second score of each target article to obtain a total score of each target article, and displaying the multiple target articles in order of magnitude of the total score. Due to the fact that the ranking can be achieved through the sum of the first score and the second score, and the second score is determined according to the historical access record, the display sequence of the target article can be corrected through the behavior data of the user, the final display sequence can better meet the use requirements of the user, and the experience of the user is higher.
The above description is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
It will be evident to those skilled in the art that the present application is not limited to the details of the foregoing illustrative embodiments, and that the present application may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the application being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Claims (10)
1. A method for displaying article search results is characterized in that the method comprises the following steps:
acquiring a first keyword to be searched;
preprocessing the first keywords to be searched to generate one or more target words;
determining a plurality of pieces of target articles from a database according to the target words, and scoring each piece of target article according to the target words to obtain a first score of each piece of target article;
determining a second score of each piece of the target article according to a historical access record, wherein the historical access record comprises the accessed times and/or the accessed time length of each piece of the target article;
and summing the first score and the second score of each target article to obtain a total score of each target article, and displaying the multiple target articles according to the magnitude order of the total scores.
2. The method for displaying search results of articles according to claim 1, wherein the step of determining a plurality of pieces of target articles from a database according to the target word and scoring each piece of target article according to the target word to obtain a first score of each piece of target article comprises:
acquiring title scores and content scores of each piece of target articles according to the target words;
and summing the title score and the content score to obtain the first score.
3. The method for displaying search results of articles according to claim 2, wherein before the step of determining a plurality of pieces of articles from the database according to the target word and scoring each piece of article according to the target word to obtain the first score of each piece of article, the method further comprises:
preprocessing each article to obtain a plurality of second keywords of each article;
calculating the weight of each second keyword according to a TextRank algorithm;
the step of determining a plurality of target articles from the database according to the target words comprises the following steps:
determining an article corresponding to the second keyword and the target word as a target article;
the step of scoring each piece of the target articles according to the target words to obtain a first score of each piece of the target articles comprises:
obtaining title scores according to the number of second keywords corresponding to the target words contained in the titles of each piece of target article;
and acquiring content scores according to the weight of the second keyword corresponding to the target word contained in the content of each piece of target article.
4. The article search result presentation method of claim 1, wherein the step of preprocessing the first keyword to be searched to generate one or more target words comprises:
performing word segmentation processing on the first keyword to obtain at least one word to be analyzed;
performing filtering word parking processing on the at least one word to be analyzed;
and carrying out synonym transformation on the processed words to be analyzed so as to determine one or more target words.
5. An article search result presentation apparatus, the apparatus comprising:
the data acquisition module is used for acquiring a first keyword to be searched;
the data processing module is used for preprocessing the first keyword to be searched to generate one or more target words;
the data processing module is further used for determining multiple pieces of target articles from a database according to the target words and scoring each piece of target article according to the target words to obtain a first score of each piece of target article;
the data processing module is further used for determining a second score of each piece of the target article according to a historical access record, wherein the historical access record comprises the accessed times and the accessed duration of each piece of the target article;
and the data processing module is further used for summing the first score and the second score of each target article to obtain a total score of each target article, and displaying the multiple target articles according to the size sequence of the total scores.
6. The apparatus for displaying search results of articles according to claim 5, wherein the data processing module is further configured to obtain a title score and a content score of each piece of a target article according to the target word, and sum the title score and the content score to obtain the first score.
7. The article search result presentation apparatus of claim 6, wherein the data processing module is further configured to pre-process each article to obtain a plurality of second keywords for each article; calculating the weight of each second keyword according to a TextRank algorithm;
the data processing module is further used for determining that the article corresponding to the second keyword and the target word is a target article;
the data processing module is further used for obtaining title scores according to the number of second keywords corresponding to the target words contained in the titles of each piece of target articles; and acquiring content scores according to the weight of the second keyword corresponding to the target words contained in the content of each piece of target article.
8. The apparatus for displaying search results of articles according to claim 5, wherein the data processing module is further configured to perform word segmentation on the first keyword to obtain at least one word to be analyzed, perform filtered word parking processing on the at least one word to be analyzed, and perform synonym transformation on the processed word to be analyzed to determine one or more target words.
9. An electronic device, comprising:
a memory for storing one or more programs;
a processor;
the one or more programs, when executed by the processor, implement the method of any of claims 1-4.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1-4.
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Application publication date: 20200512 |