CN113934938A - Information display method and device, readable medium and electronic equipment - Google Patents
Information display method and device, readable medium and electronic equipment Download PDFInfo
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Abstract
The disclosure relates to a method, a device, a readable medium and an electronic device for information display, relating to the technical field of information search, wherein the method comprises the following steps: the method comprises the steps of obtaining search information and search results, determining a plurality of pieces of recommended search information and initial sequencing corresponding to the search information according to the search results, determining recommendation scores of the recommended search information according to historical search data of each piece of recommended search information, adjusting the initial sequencing according to the recommendation scores to obtain target sequencing of the recommended search information, and displaying the target recommended search information according to the target sequencing. According to the method and the device, the ranking of the original recommended search information is adjusted through the recommendation scores, the target recommended search information is displayed according to the obtained target ranking, the quality of the displayed target recommended search information can be ensured, a user can quickly obtain a search result meeting the search requirements of the user through the high-quality target recommended search information, and the convenience and the search experience of the user in information search are improved.
Description
Technical Field
The present disclosure relates to the field of information search technologies, and in particular, to a method and an apparatus for displaying information, a readable medium, and an electronic device.
Background
With the continuous development of information technology, users obtain required information by searching information on the internet, and the information is becoming one of important applications of the internet. When a user inputs search information to search for information, the search requirement may not be accurately expressed or the current search result may not be satisfied. In the prior art, the information search can be performed by recommending related search terms to the user, so that the search cost is reduced, a new search requirement is triggered, and the search experience of the user is improved.
The inventor finds that recommending related search terms requires estimating the click rate of each search term, ranking the search terms based on the click rate, screening a plurality of target search terms, and showing the target search terms to the user in the process of implementing the method. However, the content quality of the target search terms is low, which may cause search results obtained by the user through information search by using the search terms to be not in line with the search requirements of the user, thereby affecting the convenience and search experience of the user in information search.
Disclosure of Invention
This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the detailed description. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter.
In a first aspect, the present disclosure provides a method for displaying information, the method comprising:
acquiring search information and a search result corresponding to the search information;
determining a plurality of pieces of recommended search information corresponding to the search information and initial sequencing of the plurality of pieces of recommended search information according to the search result;
determining a recommendation score of each piece of recommended search information according to historical search data of the recommended search information; the historical search data of the recommended search information is data generated by searching the recommended search information in a historical time period;
adjusting the initial ranking according to the recommendation score to obtain target rankings of the plurality of pieces of recommended search information;
and displaying target recommended search information according to the target sequence, wherein the target recommended search information is a preset number of pieces of recommended search information sequenced at the top in the target sequence.
In a second aspect, the present disclosure provides an apparatus for information presentation, the apparatus comprising:
the acquisition module is used for acquiring search information and a search result corresponding to the search information;
the determining module is used for determining a plurality of pieces of recommended search information corresponding to the search information and the initial sequence of the recommended search information according to the search result;
the determining module is further configured to determine a recommendation score of each piece of recommended search information according to historical search data of the piece of recommended search information; the historical search data of the recommended search information is data generated by searching the recommended search information in a historical time period;
the adjusting module is used for adjusting the initial ranking according to the recommendation score to obtain the target ranking of the plurality of pieces of recommended search information;
and the display module is used for displaying the target recommended search information according to the target sequence, wherein the target recommended search information is a preset number of pieces of recommended search information sequenced at the top in the target sequence.
In a third aspect, the present disclosure provides a computer readable medium having stored thereon a computer program which, when executed by a processing apparatus, performs the steps of the method of the first aspect of the present disclosure.
In a fourth aspect, the present disclosure provides an electronic device comprising:
a storage device having a computer program stored thereon;
processing means for executing the computer program in the storage means to implement the steps of the method of the first aspect of the present disclosure.
According to the technical scheme, the method comprises the steps of firstly obtaining search information and search results corresponding to the search information, determining a plurality of pieces of recommended search information corresponding to the search information and initial sequencing of the plurality of pieces of recommended search information according to the search results, determining the recommendation score of the recommended search information according to historical search data of each piece of recommended search information, adjusting the initial sequencing according to the recommendation score to obtain target sequencing of the plurality of pieces of recommended search information, and displaying the target recommended search information according to the target sequencing. According to the method and the device, the recommendation score of each piece of recommended search information is calculated through historical search data, the sequencing of the original pieces of recommended search information is adjusted according to the recommendation scores, the sequencing of the recommended search information with high content quality is advanced, the target recommended search information is displayed according to the obtained target sequencing, the quality of the displayed target recommended search information can be ensured, a user can quickly obtain a search result meeting the search requirement of the user through the high-quality target recommended search information, and the convenience and the search experience of the user in information search are improved.
Additional features and advantages of the disclosure will be set forth in the detailed description which follows.
Drawings
The above and other features, advantages and aspects of various embodiments of the present disclosure will become more apparent by referring to the following detailed description when taken in conjunction with the accompanying drawings. Throughout the drawings, the same or similar reference numbers refer to the same or similar elements. It should be understood that the drawings are schematic and that elements and features are not necessarily drawn to scale. In the drawings:
FIG. 1 is a flow diagram illustrating a method of information presentation in accordance with an exemplary embodiment;
FIG. 2 is a flow chart of one step 101 shown in accordance with the embodiment shown in FIG. 1;
FIG. 3 is a flowchart illustrating one step 104 according to the embodiment shown in FIG. 1;
FIG. 4 is a block diagram illustrating an apparatus for information presentation in accordance with an exemplary embodiment;
FIG. 5 is a block diagram of a determination module shown in accordance with the embodiment shown in FIG. 4;
FIG. 6 is a block diagram of an adjustment module shown in accordance with the embodiment of FIG. 4;
FIG. 7 is a block diagram illustrating an electronic device in accordance with an example embodiment.
Detailed Description
Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure are shown in the drawings, it is to be understood that the present disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein, but rather are provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the disclosure are for illustration purposes only and are not intended to limit the scope of the disclosure.
It should be understood that the various steps recited in the method embodiments of the present disclosure may be performed in a different order, and/or performed in parallel. Moreover, method embodiments may include additional steps and/or omit performing the illustrated steps. The scope of the present disclosure is not limited in this respect.
The term "include" and variations thereof as used herein are open-ended, i.e., "including but not limited to". The term "based on" is "based, at least in part, on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". Relevant definitions for other terms will be given in the following description.
It should be noted that the terms "first", "second", and the like in the present disclosure are only used for distinguishing different devices, modules or units, and are not used for limiting the order or interdependence relationship of the functions performed by the devices, modules or units.
It is noted that references to "a", "an", and "the" modifications in this disclosure are intended to be illustrative rather than limiting, and that those skilled in the art will recognize that "one or more" may be used unless the context clearly dictates otherwise.
The names of messages or information exchanged between devices in the embodiments of the present disclosure are for illustrative purposes only, and are not intended to limit the scope of the messages or information.
FIG. 1 is a flow chart illustrating a method of information presentation in accordance with an exemplary embodiment. As shown in fig. 1, the method may include the steps of:
And step 102, determining a plurality of pieces of recommended search information corresponding to the search information and initial sequencing of the plurality of pieces of recommended search information according to the search result.
For example, when a user searches information on the internet, the user may input corresponding search information to a search engine according to the search requirement of the user, and receive a search result corresponding to the search information returned by the search engine. And then, determining a plurality of pieces of recommended search information according to the search results, determining the ranking score of each piece of recommended search information based on a click rate ranking mode, and determining the initial ranking of the plurality of pieces of recommended search information according to the ranking score from large to small. The recommended search information is information recommended to the user according to the search result and possibly meeting the search requirement of the user, and may be a search keyword or a search key sentence, for example. For example, when the search information input to the search engine by the user is "game", the search engine returns a search result related to "game" to the user, and then the search result related to "game" may be analyzed to determine that the plurality of recommended search information are "stand-alone game", "network game", "mobile game" and "game play", and then the ranking score of each recommended search information may be determined based on the click-through rate ranking, and the initial ranking of the plurality of recommended search information may be determined according to the order of the ranking scores from large to small: the game system comprises a mobile phone game, an online game, a stand-alone game and a game strategy.
And 103, determining the recommendation score of each piece of recommended search information according to the historical search data of each piece of recommended search information. The historical search data of the recommended search information is data generated by performing information search on the recommended search information in a historical time period.
Further, some bad contents (such as a title party, negatively exaggerated recommended search information, and the like) can be amplified by the click-through rate, which affects the content quality of the recommended search information. Specifically, first, the information search process of each piece of recommended search information may be preprocessed in a history time period before information search is performed according to the search information to acquire history search data. The information search process of each piece of recommended search information comprises a process of searching information by recommending search information by a large number of different users, the historical search data is information obtained by aggregating data generated in the information search process of the recommended search information, user information does not need to be considered, and the historical search data can comprise feedback data of historical search results of the users aiming at each piece of recommended search information in a historical time period.
Then, a recommendation score of each piece of recommended search information (i.e., a negative feedback score when the user performs information search through the recommended search information) may be determined based on the history search data of each piece of recommended search information. The process of determining the recommendation score of each piece of recommended search information is actually a process of finding out recommended search information unsatisfactory to the user from historical search data.
And 104, adjusting the initial ranking according to the recommendation score to obtain a plurality of target rankings of the recommended search information.
And 105, displaying the target recommendation search information according to the target sequence. The target recommended search information is a preset number of pieces of recommended search information ranked at the top in the target ranking.
For example, after determining the recommendation score of each piece of recommended search information, a target score of each piece of recommended search information may be determined according to the recommendation score of each piece of recommended search information in combination with the ranking score of the piece of recommended search information, where the target score may be understood as a score of each piece of recommended search information obtained by introducing negative feedback information for the piece of recommended search information on the basis of the ranking score of each piece of originally recommended search information. Then, the initial ranking can be adjusted according to the sequence of the target scores from large to small to obtain the target ranking of the plurality of pieces of recommended search information, and the preset number of pieces of target recommended search information which are ranked in the front are displayed according to the target ranking. For example, in a case that the recommended search information is a search keyword (at this time, the target recommended search information is a target search keyword), the target search keywords may be sequentially displayed in a designated area of a display page where the search result is located according to a sequence in the target ranking (the designated area may be, for example, a middle area of the display page). According to the target sorting, unsatisfactory recommended search information of the user can be suppressed, and the target recommended search information meeting the search requirements of the user is recommended to the user, so that the user is guided to initiate a new search behavior, derived requirements are met, and further more information search requests of the user are stimulated.
In summary, the present disclosure first obtains search information and a search result corresponding to the search information, determines a plurality of pieces of recommended search information corresponding to the search information and an initial ranking of the plurality of pieces of recommended search information according to the search result, determines a recommendation score of the recommended search information according to historical search data of each piece of recommended search information, adjusts the initial ranking according to the recommendation score, obtains a target ranking of the plurality of pieces of recommended search information, and displays the target recommended search information according to the target ranking. According to the method and the device, the recommendation score of each piece of recommended search information is calculated through historical search data, the sequencing of the original pieces of recommended search information is adjusted according to the recommendation scores, the sequencing of the recommended search information with high content quality is advanced, the target recommended search information is displayed according to the obtained target sequencing, the quality of the displayed target recommended search information can be ensured, a user can quickly obtain a search result meeting the search requirement of the user through the high-quality target recommended search information, and the convenience and the search experience of the user in information search are improved.
Alternatively, step 101 may be implemented by:
and acquiring search information currently input by a user, and searching information according to the search information to obtain a search result. Alternatively, the first and second electrodes may be,
and acquiring search information input by a user according to a preset period, and searching information according to the search information to obtain a search result.
For example, the process of ranking the plurality of pieces of recommended search information may be to obtain search information currently input by the user to perform an information search each time the user performs an information search, to obtain a search result, and determine the plurality of pieces of recommended search information and an initial ranking of the plurality of pieces of recommended search information according to the search result (i.e., the recommended search information needs to be ranked once for each search). The process of ranking the plurality of pieces of recommended search information may also be a process of obtaining search information input by a user according to a preset period in an offline manner to perform information search, so as to obtain a search result, and determining the plurality of pieces of recommended search information and an initial ranking of the plurality of pieces of recommended search information according to the search result (i.e., performing ranking of the recommended search information periodically offline).
Fig. 2 is a flow chart illustrating a step 101 according to the embodiment shown in fig. 1. As shown in fig. 2, step 102 may include the steps of:
For example, after the search result corresponding to the search information is obtained, a plurality of pieces of recommended search information may be determined according to the search result. Recommending search information may be understood as inferring information that a user may want to query based on search results (which typically has some relevance to the search results). For example, TF-IDF (english: Term Frequency-Inverse Document Frequency) may be used to determine a plurality of target keywords from the search results (the process of determining the target keywords actually selects keywords with higher importance from the search results), and then a collaborative filtering algorithm may be used to determine a plurality of search keywords from the historical search data of each target keyword, and the search keywords may be used as the recommended search information.
And 1023, determining a ranking score corresponding to each piece of recommended search information through a pre-trained ranking model according to the plurality of pieces of recommended search information.
And step 1024, determining initial sorting according to the sorting scores.
Specifically, each piece of recommended search information may be sequentially input into a pre-trained ranking model, so as to obtain a ranking score corresponding to each piece of recommended search information output by the ranking model. The ranking model may be, for example, a CTR (Click-Through-Rate) prediction model. An initial ranking of the plurality of recommended search information may then be determined in order of decreasing ranking scores.
Optionally, the historical search data of the recommended search information includes feedback data triggered by the user for a historical search result in a historical time period, and the historical search result is obtained by performing information search according to the recommended search information. Step 103 may be implemented by:
and determining the recommendation score of each piece of recommended search information according to the feedback data of the recommended search information.
The feedback data comprises at least one of whether to click the historical search result, the number of times of the click operation, the position of the click operation in the display page where the historical search result is located, the stay time of the click operation in the display page, whether to turn the display page, whether to adjust the search information, the number of times of adjusting the search information and the time for completing the information search.
For example, after the initial ranking of the plurality of pieces of recommended search information is determined, the feedback data of each piece of recommended search information may be sequentially input into a pre-trained decision tree model, so as to obtain the recommendation score of the piece of recommended search information. It should be noted that the decision tree model is actually used for comprehensively judging the satisfaction degree of the user on the historical search result through various types of data in the historical search data. When information search is carried out according to certain recommended search information, whether a user clicks the historical search result of the recommended search information is a key index for measuring the satisfaction degree of the user, and the times of clicking, the position in a clicking display page, the stay time of the user on the display page, whether the user turns pages of the display page, whether the user adjusts the search information, the times of adjusting the search information by the user and the time for completing the information search are also important indexes for reflecting the satisfaction degree of the user, so that the decision tree model can determine the recommendation score of the recommended search information (namely, judge whether the historical search result of the recommended search information is negatively fed back) according to the preset influences (such as positive and negative feedback signals) of the factors on the satisfaction degree of the user.
Fig. 3 is a flow chart illustrating one step 104 according to the embodiment shown in fig. 1. As shown in fig. 3, step 104 may include the steps of:
For example, after determining the recommendation score of each piece of recommended search information, a target score corresponding to each piece of recommended search information may be determined by using a preset formula according to the ranking score and the recommendation score. Wherein the preset formula can be expressed as: and m is l (1-n), m is the target score, l is the ranking score, and n is the recommendation score. Then, the target ranks of the plurality of recommended search information may be determined in order of the target scores from large to small. For example, the ranking score of the plurality of recommended search information A, B, C is 10/9/8, when the initial ranking is: A. b, C are provided. And the recommendation score of the recommended search information a is 0.5, the recommendation score of the recommended search information B is 0.4, and the recommendation score of the recommended search information C is 0.4, then the target scores of the plurality of recommended search information A, B, C are respectively: 5. 5.4, 4.8, then the target rank is: B. a, C are provided. In one scenario, if the plurality of pieces of recommended search information are found to be the same as the plurality of pieces of recommended search information recommended to the user before, the target ranking of the plurality of pieces of recommended search information that has been adjusted before may be directly used as the target ranking of the plurality of pieces of recommended search information this time.
In another scenario, if the target score corresponding to each piece of recommended search information is smaller than a preset score threshold (which indicates that all pieces of recommended search information at this time cannot be satisfied by the user), a prompt message may be sent to the user to prompt the user to adjust the originally input search information, obtain the adjusted search information obtained by adjusting the search information, and adjust the search result corresponding to the search information. And then determining a plurality of pieces of adjustment recommended search information corresponding to the adjustment search information and adjustment ranks of the plurality of pieces of adjustment recommended search information according to the adjustment search result (the adjustment ranks are initial ranks of the plurality of pieces of adjustment recommended search information). The plurality of adjusted recommended search information may then be used as recommended search information to update the plurality of recommended search information and determine a target ranking of the updated plurality of recommended search information. And finally, displaying a preset number of pieces of target recommended search information which are sorted in the front according to the updated target sorting of the plurality of pieces of recommended search information.
In summary, the present disclosure first obtains search information and a search result corresponding to the search information, determines a plurality of pieces of recommended search information corresponding to the search information and an initial ranking of the plurality of pieces of recommended search information according to the search result, determines a recommendation score of the recommended search information according to historical search data of each piece of recommended search information, adjusts the initial ranking according to the recommendation score, obtains a target ranking of the plurality of pieces of recommended search information, and displays the target recommended search information according to the target ranking. According to the method and the device, the recommendation score of each piece of recommended search information is calculated through historical search data, the sequencing of the original pieces of recommended search information is adjusted according to the recommendation scores, the sequencing of the recommended search information with high content quality is advanced, the target recommended search information is displayed according to the obtained target sequencing, the quality of the displayed target recommended search information can be ensured, a user can quickly obtain a search result meeting the search requirement of the user through the high-quality target recommended search information, and the convenience and the search experience of the user in information search are improved.
FIG. 4 is a block diagram illustrating an apparatus for information presentation in accordance with an example embodiment. As shown in fig. 4, the apparatus 200 includes:
the obtaining module 201 is configured to obtain search information and a search result corresponding to the search information.
The determining module 202 is configured to determine, according to the search result, a plurality of pieces of recommended search information corresponding to the search information and an initial ranking of the plurality of pieces of recommended search information.
The determining module 202 is further configured to determine a recommendation score of each piece of recommended search information according to the historical search data of the piece of recommended search information. The historical search data of the recommended search information is data generated by performing information search on the recommended search information in a historical time period.
And the adjusting module 203 is configured to adjust the initial ranking according to the recommendation score to obtain a target ranking of the plurality of pieces of recommended search information.
The display module 204 is configured to display the target recommended search information according to the target ranking, where the target recommended search information is a preset number of pieces of recommended search information ranked at the top in the target ranking.
Optionally, the obtaining module 201 is configured to:
and acquiring search information currently input by a user, and searching information according to the search information to obtain a search result. Alternatively, the first and second electrodes may be,
and acquiring search information input by a user according to a preset period, and searching information according to the search information to obtain a search result.
FIG. 5 is a block diagram illustrating a determination module according to the embodiment shown in FIG. 4. As shown in fig. 5, the determining module 202 includes:
the first determining sub-module 2021 is configured to determine a target keyword from the search result.
The processing sub-module 2022 is configured to determine a plurality of search keywords from the historical search data of the target keyword by using a collaborative filtering algorithm, and use the search keywords as the recommended search information.
The first determining sub-module 2021 is further configured to determine, according to the plurality of pieces of recommended search information, a ranking score corresponding to each piece of recommended search information through a pre-trained ranking model.
The first determining sub-module 2021 is further configured to determine an initial ranking according to the ranking score.
Optionally, the historical search data of the recommended search information includes feedback data triggered by the user for a historical search result in a historical time period, and the historical search result is obtained by performing information search according to the recommended search information. The determination module 202 is configured to:
and determining the recommendation score of each piece of recommended search information according to the feedback data of the recommended search information.
The feedback data comprises at least one of whether to click the historical search result, the number of times of the click operation, the position of the click operation in the display page where the historical search result is located, the stay time of the click operation in the display page, whether to turn the display page, whether to adjust the search information, the number of times of adjusting the search information and the time for completing the information search.
Optionally, the determining module 202 is configured to:
and inputting the feedback data of each piece of recommended search information into a pre-trained decision tree model to obtain the recommendation score of the recommended search information.
Fig. 6 is a block diagram of an adjustment module according to the embodiment shown in fig. 4. As shown in fig. 6, the adjusting module 203 includes:
the second determining sub-module 2031 is configured to determine, according to the ranking score and the recommendation score, a target score corresponding to each piece of recommended search information.
The adjusting submodule 2032 is configured to adjust the initial rank according to the target score to obtain a target rank.
Optionally, the obtaining module 201 is further configured to obtain adjusted search information obtained after the search information is adjusted and an adjusted search result corresponding to the adjusted search information if the target score corresponding to each piece of recommended search information is smaller than a preset score threshold.
The determining module 202 is further configured to determine, according to the adjustment search result, a plurality of adjustment recommended search information corresponding to the adjustment search information and an adjustment ranking of the plurality of adjustment recommended search information.
The determining module 202 is further configured to use the plurality of adjusted recommended search information as recommended search information to update the plurality of recommended search information, and determine a target ranking of the updated plurality of recommended search information.
Optionally, the presentation module 204 is configured to:
and sequentially displaying the target search keywords in the designated area of the display page where the search result is located according to the sequence in the target sequence.
In summary, the present disclosure first obtains search information and a search result corresponding to the search information, determines a plurality of pieces of recommended search information corresponding to the search information and an initial ranking of the plurality of pieces of recommended search information according to the search result, determines a recommendation score of the recommended search information according to historical search data of each piece of recommended search information, adjusts the initial ranking according to the recommendation score, obtains a target ranking of the plurality of pieces of recommended search information, and displays the target recommended search information according to the target ranking. According to the method and the device, the recommendation score of each piece of recommended search information is calculated through historical search data, the sequencing of the original pieces of recommended search information is adjusted according to the recommendation scores, the sequencing of the recommended search information with high content quality is advanced, the target recommended search information is displayed according to the obtained target sequencing, the quality of the displayed target recommended search information can be ensured, a user can quickly obtain a search result meeting the search requirement of the user through the high-quality target recommended search information, and the convenience and the search experience of the user in information search are improved.
Referring now to fig. 7, a schematic diagram of an electronic device (e.g., the terminal device or the server of fig. 1) 300 suitable for implementing embodiments of the present disclosure is shown. The terminal device in the embodiments of the present disclosure may include, but is not limited to, a mobile terminal such as a mobile phone, a notebook computer, a digital broadcast receiver, a PDA (personal digital assistant), a PAD (tablet computer), a PMP (portable multimedia player), a vehicle terminal (e.g., a car navigation terminal), and the like, and a stationary terminal such as a digital TV, a desktop computer, and the like. The electronic device shown in fig. 7 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present disclosure.
As shown in fig. 7, the electronic device 300 may include a processing means (e.g., a central processing unit, a graphics processor, etc.) 301 that may perform various appropriate 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 necessary 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.
Generally, the following devices may be connected to the I/O interface 305: input devices 306 including, for example, a touch screen, touch pad, 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 devices 308 including, for example, magnetic tape, hard disk, etc.; and a communication device 309. The communication means 309 may allow the electronic device 300 to communicate wirelessly or by wire with other devices to exchange data. While fig. 7 illustrates an electronic device 300 having various means, it is to be understood that not all illustrated means are required to be implemented or provided. More or fewer devices may alternatively be implemented or provided.
In particular, according to an embodiment of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program carried on a non-transitory computer readable medium, the computer program containing program code for performing the method illustrated by the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication means 309, or installed from the storage means 308, or installed from the ROM 302. The computer program, when executed by the processing device 301, performs the above-described functions defined in the methods of the embodiments of the present disclosure.
It should be noted that the computer readable medium in the present disclosure can be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination 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 present 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 contrast, in the present disclosure, a computer readable signal medium may comprise a propagated data signal with computer readable program code embodied therein, either in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. 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, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.
In some embodiments, the clients, servers may communicate using any currently known or future developed network Protocol, such as HTTP (HyperText Transfer Protocol), and may interconnect with any form or medium of digital data communication (e.g., a communications network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the Internet (e.g., the Internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed network.
The computer readable medium may be embodied in the electronic device; or may exist separately without being assembled 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 search information and a search result corresponding to the search information; determining a plurality of pieces of recommended search information corresponding to the search information and initial sequencing of the plurality of pieces of recommended search information according to the search result; determining a recommendation score of each piece of recommended search information according to historical search data of the recommended search information; the historical search data of the recommended search information is data generated by searching the recommended search information in a historical time period; adjusting the initial ranking according to the recommendation score to obtain target rankings of the plurality of pieces of recommended search information; and displaying target recommended search information according to the target sequence, wherein the target recommended search information is a preset number of pieces of recommended search information sequenced at the top in the target sequence.
Computer program code for carrying out operations for the present disclosure may be written in any combination of one or more programming languages, including but not limited to 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 type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
The flowchart 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 modules described in the embodiments of the present disclosure may be implemented by software or hardware. The name of a module does not in some cases constitute a limitation of the module itself, and for example, an acquisition module may also be described as a "module that acquires search information and search results".
The functions described herein above may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), systems on a chip (SOCs), Complex Programmable Logic Devices (CPLDs), and the like.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on 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.
Example 1 provides, in accordance with one or more embodiments of the present disclosure, a method of information presentation, comprising: acquiring search information and a search result corresponding to the search information; determining a plurality of pieces of recommended search information corresponding to the search information and initial sequencing of the plurality of pieces of recommended search information according to the search result; determining a recommendation score of each piece of recommended search information according to historical search data of the recommended search information; the historical search data of the recommended search information is data generated by searching the recommended search information in a historical time period; adjusting the initial ranking according to the recommendation score to obtain target rankings of the plurality of pieces of recommended search information; and displaying target recommended search information according to the target sequence, wherein the target recommended search information is a preset number of pieces of recommended search information sequenced at the top in the target sequence.
Example 2 provides the method of example 1, wherein the obtaining search information and a search result corresponding to the search information includes: acquiring search information currently input by a user, and searching information according to the search information to obtain a search result; or acquiring search information input by a user according to a preset period, and searching information according to the search information to obtain the search result.
Example 3 provides the method of example 1, wherein determining, according to the search result, a plurality of pieces of recommended search information corresponding to the search information and an initial ranking of the plurality of pieces of recommended search information includes: determining a target keyword from the search result; determining a plurality of search keywords from the historical search data of the target keywords by using a collaborative filtering algorithm, and taking the search keywords as the recommended search information; determining a ranking score corresponding to each piece of recommended search information through a pre-trained ranking model according to the plurality of pieces of recommended search information; and determining the initial sorting according to the sorting score.
Example 4 provides the method of example 1, where the historical search data of the recommended search information includes feedback data triggered by a user for a historical search result in a historical time period, and the historical search result is obtained by performing information search according to the recommended search information; the determining the recommendation score of the recommended search information according to the historical search data of each piece of recommended search information includes: determining a recommendation score of each piece of recommended search information according to the feedback data of the recommended search information; the feedback data comprises at least one of whether to click the historical search result, the number of times of the click operation, the position of the click operation in the display page where the historical search result is located, the stay time of the click operation in the display page, whether to turn the display page, whether to adjust the search information, the number of times of adjusting the search information and the time for completing the information search.
Example 5 provides the method of example 4, wherein determining the recommendation score for each piece of recommended search information according to the feedback data for the piece of recommended search information, includes: and inputting the feedback data of each piece of recommended search information into a pre-trained decision tree model to obtain a recommendation score of the recommended search information.
Example 6 provides the method of example 3, wherein the adjusting the initial ranking according to the recommendation score to obtain a target ranking of the plurality of recommended search information includes: determining a target score corresponding to each piece of recommended search information according to the sorting score and the recommendation score; and adjusting the initial sequence according to the target score to obtain the target sequence.
Example 7 provides the method of example 6, further comprising, in accordance with one or more embodiments of the present disclosure: if the target score corresponding to each piece of recommended search information is smaller than a preset score threshold, obtaining adjusted search information obtained after the search information is adjusted and an adjusted search result corresponding to the adjusted search information; determining a plurality of pieces of adjustment recommendation search information corresponding to the adjustment search information and adjustment sequencing of the plurality of pieces of adjustment recommendation search information according to the adjustment search result; and taking the plurality of pieces of adjusted recommended search information as the recommended search information to update the plurality of pieces of recommended search information and determine the target sequence of the plurality of pieces of updated recommended search information.
Example 8 provides the method of example 1, where, in a case where the recommended search information is a search keyword, the presenting of the target recommended search information in the target ranking includes: and sequentially displaying the target search keywords in the designated area of the display page where the search result is located according to the sequence in the target sequence.
Example 9 provides, in accordance with one or more embodiments of the present disclosure, an apparatus for information presentation, the apparatus comprising: the acquisition module is used for acquiring search information and a search result corresponding to the search information; the determining module is used for determining a plurality of pieces of recommended search information corresponding to the search information and the initial sequence of the recommended search information according to the search result; the determining module is further configured to determine a recommendation score of each piece of recommended search information according to historical search data of the piece of recommended search information; the historical search data of the recommended search information is data generated by searching the recommended search information in a historical time period; the adjusting module is used for adjusting the initial ranking according to the recommendation score to obtain the target ranking of the plurality of pieces of recommended search information; and the display module is used for displaying the target recommended search information according to the target sequence, wherein the target recommended search information is a preset number of pieces of recommended search information sequenced at the top in the target sequence.
Example 10 provides a computer-readable medium having stored thereon a computer program that, when executed by a processing device, implements the steps of the methods of examples 1-8, in accordance with one or more embodiments of the present disclosure.
Example 11 provides, in accordance with one or more embodiments of the present disclosure, an electronic device, comprising: a storage device having a computer program stored thereon; processing means for executing the computer program in the storage means to implement the steps of the methods of examples 1 to 8.
The foregoing description is only exemplary of the preferred embodiments of the disclosure and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the disclosure herein is not limited to the particular combination of features described above, but also encompasses other embodiments in which any combination of the features described above or their equivalents does not depart from the spirit of the disclosure. For example, the above features and (but not limited to) the features disclosed in this disclosure having similar functions are replaced with each other to form the technical solution.
Further, while operations are depicted in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order. Under certain circumstances, multitasking and parallel processing may be advantageous. Likewise, while several specific implementation details are included in the above discussion, these should not be construed as limitations on the scope of the disclosure. Certain features that are described in the context of separate embodiments can also be implemented in combination in a single embodiment. Conversely, various features that are described in the context of a single embodiment can also be implemented in multiple embodiments separately or in any suitable subcombination.
Although the subject matter has been described in language specific to structural features and/or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims. With regard to the apparatus in the above-described embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be elaborated here.
Claims (11)
1. A method of information presentation, the method comprising:
acquiring search information and a search result corresponding to the search information;
determining a plurality of pieces of recommended search information corresponding to the search information and initial sequencing of the plurality of pieces of recommended search information according to the search result;
determining a recommendation score of each piece of recommended search information according to historical search data of the recommended search information; the historical search data of the recommended search information is data generated by searching the recommended search information in a historical time period;
adjusting the initial ranking according to the recommendation score to obtain target rankings of the plurality of pieces of recommended search information;
and displaying target recommended search information according to the target sequence, wherein the target recommended search information is a preset number of pieces of recommended search information sequenced at the top in the target sequence.
2. The method according to claim 1, wherein the obtaining search information and the search result corresponding to the search information includes:
acquiring search information currently input by a user, and searching information according to the search information to obtain a search result; alternatively, the first and second electrodes may be,
and acquiring search information input by a user according to a preset period, and searching information according to the search information to obtain the search result.
3. The method according to claim 1, wherein the determining, according to the search result, a plurality of pieces of recommended search information corresponding to the search information and an initial ranking of the plurality of pieces of recommended search information includes:
determining a target keyword from the search result;
determining a plurality of search keywords from the historical search data of the target keywords by using a collaborative filtering algorithm, and taking the search keywords as the recommended search information;
determining a ranking score corresponding to each piece of recommended search information through a pre-trained ranking model according to the plurality of pieces of recommended search information;
and determining the initial sorting according to the sorting score.
4. The method according to claim 1, wherein the historical search data of the recommended search information comprises feedback data triggered by a user for historical search results in a historical time period, and the historical search results are obtained by searching information according to the recommended search information; the determining the recommendation score of the recommended search information according to the historical search data of each piece of recommended search information includes:
determining a recommendation score of each piece of recommended search information according to the feedback data of the recommended search information;
the feedback data comprises at least one of whether to click the historical search result, the number of times of the click operation, the position of the click operation in the display page where the historical search result is located, the stay time of the click operation in the display page, whether to turn the display page, whether to adjust the search information, the number of times of adjusting the search information and the time for completing the information search.
5. The method of claim 4, wherein determining the recommendation score for each of the recommended search information based on the feedback data for that recommended search information comprises:
and inputting the feedback data of each piece of recommended search information into a pre-trained decision tree model to obtain a recommendation score of the recommended search information.
6. The method of claim 3, wherein the adjusting the initial ranking to obtain the target ranking of the plurality of recommended search information according to the recommendation score comprises:
determining a target score corresponding to each piece of recommended search information according to the sorting score and the recommendation score;
and adjusting the initial sequence according to the target score to obtain the target sequence.
7. The method of claim 6, further comprising:
if the target score corresponding to each piece of recommended search information is smaller than a preset score threshold, obtaining adjusted search information obtained after the search information is adjusted and an adjusted search result corresponding to the adjusted search information;
determining a plurality of pieces of adjustment recommendation search information corresponding to the adjustment search information and adjustment sequencing of the plurality of pieces of adjustment recommendation search information according to the adjustment search result;
and taking the plurality of pieces of adjusted recommended search information as the recommended search information to update the plurality of pieces of recommended search information and determine the target sequence of the plurality of pieces of updated recommended search information.
8. The method according to claim 1, wherein in a case that the recommended search information is a search keyword, the presenting the target recommended search information in the target ranking comprises:
and sequentially displaying the target search keywords in the designated area of the display page where the search result is located according to the sequence in the target sequence.
9. An apparatus for information presentation, the apparatus comprising:
the acquisition module is used for acquiring search information and a search result corresponding to the search information;
the determining module is used for determining a plurality of pieces of recommended search information corresponding to the search information and the initial sequence of the recommended search information according to the search result;
the determining module is further configured to determine a recommendation score of each piece of recommended search information according to historical search data of the piece of recommended search information; the historical search data of the recommended search information is data generated by searching the recommended search information in a historical time period;
the adjusting module is used for adjusting the initial ranking according to the recommendation score to obtain the target ranking of the plurality of pieces of recommended search information;
and the display module is used for displaying the target recommended search information according to the target sequence, wherein the target recommended search information is a preset number of pieces of recommended search information sequenced at the top in the target sequence.
10. A computer-readable medium, on which a computer program is stored, characterized in that the program, when being executed by processing means, carries out the steps of the method of any one of claims 1 to 8.
11. An electronic device, comprising:
a storage device having a computer program stored thereon;
processing means for executing the computer program in the storage means to carry out the steps of the method according to any one of claims 1 to 8.
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| CN202111235924.6A CN113934938A (en) | 2021-10-22 | 2021-10-22 | Information display method and device, readable medium and electronic equipment |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115017200A (en) * | 2022-06-02 | 2022-09-06 | 北京百度网讯科技有限公司 | Search result sorting method and device, electronic equipment and storage medium |
| CN115718772A (en) * | 2022-11-24 | 2023-02-28 | 腾讯科技（深圳）有限公司 | Recommended resource determination method, data processing method, device and computer medium |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115017200A (en) * | 2022-06-02 | 2022-09-06 | 北京百度网讯科技有限公司 | Search result sorting method and device, electronic equipment and storage medium |
| CN115017200B (en) * | 2022-06-02 | 2023-08-25 | 北京百度网讯科技有限公司 | Method and device for sorting search results, electronic equipment and storage medium |
| WO2023231288A1 (en) * | 2022-06-02 | 2023-12-07 | 北京百度网讯科技有限公司 | Sorting method and apparatus for search results, and electronic device and storage medium |
| CN115718772A (en) * | 2022-11-24 | 2023-02-28 | 腾讯科技（深圳）有限公司 | Recommended resource determination method, data processing method, device and computer medium |
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