CN110619093A - Method, apparatus, electronic device, and computer-readable storage medium for determining an order of search items - Google Patents
Method, apparatus, electronic device, and computer-readable storage medium for determining an order of search items Download PDFInfo
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/953—Querying, e.g. by the use of web search engines
- G06F16/9535—Search customisation based on user profiles and personalisation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/953—Querying, e.g. by the use of web search engines
- G06F16/9537—Spatial or temporal dependent retrieval, e.g. spatiotemporal queries
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Abstract
The present disclosure discloses a method of determining an order of search terms, comprising: determining a search term; determining a search term corresponding to the search term; determining a click data set of the search item corresponding to the search word according to a region information set; and determining the sequence of the search items corresponding to the search terms according to the click data set. The embodiment of the disclosure provides a method and a device for determining a sequence of search items, and the click data of the search items corresponding to search words is related to a region, so that the sequence of the search items determined based on the click data has the characteristics of the region, and better user experience can be brought.
Description
Technical Field
The present disclosure relates to the field of information processing, and in particular, to a method and an apparatus for determining an order of search items, an electronic device, and a computer-readable storage medium.
Background
With the coming of the information age, how to accurately acquire required information from vast information ocean is a main problem to be solved in the field of search.
The conventional method related to search is a common method, which is to crawl associated data from various data sources in a network for a search word and form corresponding search items, then determine a display sequence of the search items according to click data of the search items in unit time by applying a click model algorithm and the like, so that the search items with highest association degree or most accurate association degree with the search word are displayed in the front column, display the search items corresponding to the search word according to the conventional common method without characteristics, and possibly fail to meet the requirements of users or have poor experience.
Disclosure of Invention
In view of the foregoing drawbacks, embodiments of the present disclosure provide a method, an apparatus, an electronic device, and a computer-readable storage medium for determining a sequence of search terms, where click data of a search term corresponding to a search term is related to a region, so that the sequence of the search term determined based on the click data has a regional characteristic, and better user experience can be brought.
In a first aspect, an embodiment of the present disclosure provides a method for determining an order of search terms, including: determining a search term; determining a search term corresponding to the search term; determining a click data set of the search item corresponding to the search word according to a region information set; and determining the sequence of the search items corresponding to the search terms according to the click data set.
In a second aspect, an embodiment of the present disclosure provides an apparatus for determining an order of search terms, including: the search word determining module is used for determining search words; the search item determining module is used for determining search items corresponding to the search terms; the click data set determining module is used for determining a click data set of the search item corresponding to the search word according to a region information set; and the sequence determining module is used for determining the sequence of the search items corresponding to the search terms according to the click data set.
In a third aspect, an embodiment of the present disclosure provides an electronic device, including: a memory for storing computer readable instructions; and one or more processors coupled with the memory for executing the computer readable instructions, such that the processors when executed implement the method of determining an order of search terms of any of the preceding first aspects.
In a fourth aspect, the present disclosure provides a non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores computer instructions, which when executed by a computer, cause the computer to perform the method of determining an order of search items according to any one of the first aspect.
The present disclosure discloses a method, an apparatus, an electronic device, and a computer-readable storage medium for determining an order of search items. Wherein the method of determining an order of search terms comprises: determining a search term; determining a search term corresponding to the search term; determining a click data set of the search item corresponding to the search word according to a region information set; and determining the sequence of the search items corresponding to the search terms according to the click data set. According to the method for determining the sequence of the search items and the like provided by the embodiment of the disclosure, as the click data of the search items corresponding to the search words is related to the region, the sequence of the search items determined based on the click data has the characteristics of the region, and better user experience can be brought.
The foregoing is a summary of the present disclosure, and for the purposes of promoting a clear understanding of the technical means of the present disclosure, the present disclosure may be embodied in other specific forms without departing from the spirit or essential attributes thereof.
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.
FIG. 1 is a flow diagram of an embodiment of a method for determining an order of search terms provided by an embodiment of the present disclosure;
fig. 2 is a flow chart of an alternative embodiment of determining a set of regional information provided by the present disclosure;
FIG. 3 is a flow diagram of an alternative embodiment of a method of determining an order of search terms provided by an embodiment of the present disclosure;
FIG. 4 is a schematic structural diagram of an embodiment of an apparatus for determining an order of search terms according to an embodiment of the present disclosure;
fig. 5 is a schematic structural diagram of an electronic device provided according to an embodiment of the present disclosure.
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.
Before describing the embodiments of the present disclosure, a brief introduction of some prior art in the search area is provided for a better understanding of the embodiments of the present disclosure. As described in the background and understood by those skilled in the art, when a user searches through a search engine, a search word is typically input on an interface displayed by the search engine, and then the search engine displays search items corresponding to the search word to the user in a determined order, where a process of obtaining a search item of the search word by inputting the search word may be referred to as query, and a search item corresponding to the search word may also be referred to as doc of the search word, where the search item of the search word may be determined by means of a crawler technology, an indexing technology, a relevance calculation technology, and the like, and for the above related technologies, various existing or future technologies may be used, and are not expanded herein. In the prior art, during a search performed by a user through a search engine, the search engine or other computing device records various search data of the user through a log file or the like, for example, records search data of a certain search term (including, for example, the number of searches, the search frequency) of the user and click data of a search term of the search term (including, for example, the number of clicks, the click rate, and/or the order of clicked search terms, etc.) of the user, and the like. In order to display a search term more related or accurate to a search term in the front column, a device for determining the sequence of the search term may determine the sequence (which may also be referred to as a display sequence) of the search term according to click data of the search term corresponding to the search term in unit time (for example, including last year and all year), where the unit time (for example, including last year) may be set arbitrarily, and details of related technologies such as a click model algorithm are not repeated in the embodiments of the present disclosure.
The method for determining the order of the search items provided by this embodiment may be performed by an apparatus for determining the order of the search items, which may be implemented as software, may be implemented as hardware, or may be implemented as a combination of software and hardware, for example, the search includes a computer device, so that the method for determining the order of the search items provided by this disclosure is performed by the computer device, as will be understood by those skilled in the art, the computer device may include various types, for example, a server, and as an example, the method for determining the order of the search items provided by this disclosure may be performed by one server, and the method for determining the order of the search items provided by this disclosure may be performed by cooperation of multiple servers.
Fig. 1 is a flowchart of an embodiment of a method for determining an order of search terms according to an embodiment of the present disclosure, which may be performed by the apparatus for determining an order of search terms described above.
As shown in fig. 1, a method of determining an order of search items according to an embodiment of the present disclosure includes the steps of:
step S101, determining a search word;
in step S101, the device for determining the sequence of the search terms determines a search term, where the search term corresponds to one or more search terms, as will be understood by those skilled in the art, after a user inputs the search term through a search engine, the search engine will retrieve and display the search term corresponding to the search term to the user, where the process may be referred to as query and sometimes also referred to as query, and it should be noted that the device for determining the sequence of the search terms in this disclosure may be a computer device independent from the search engine, or may be the search engine itself.
Alternatively, the search term may include one or more search terms, and in the case of including a plurality of search terms, the same search term corresponds to each of the plurality of search terms, in which case the search engine will retrieve and present the same search term regardless of whether the user inputs one or more of the plurality of search terms through the search engine.
Step S102, determining a search item corresponding to the search word;
in step S102, the means for determining the sequence of the search terms determines the search terms corresponding to the search terms, and as mentioned above, after the user inputs the search terms through the search engine, the search engine will call up and display the search terms corresponding to the search terms to the user. It will be understood by those skilled in the art that the search term corresponding to the search term may be obtained by crawling, indexing, and storing and maintaining the network data in a specific form, and then applying a calculation method, such as an association calculation method, etc., where existing or future crawling, indexing, storing, and maintaining techniques and/or association calculation techniques may be applied to the embodiments of the present disclosure, and the embodiments of the present disclosure are not limited thereto.
S103, determining a click data set of the search item corresponding to the search word according to a region information set;
in step S103, a click data set of the search term corresponding to the search term is determined according to the region information set. As described above, when a user searches using a search engine, the search engine or the like records various search data of the user, for example, records region information of a current location of the user, or records region information submitted by the user during registration, etc., through a log file or the like, so that search data, for example, click data, of the user for the search item corresponding to the search word corresponds to the region information, and thus step S103 can be implemented by using the region information recorded by the search engine. In an alternative embodiment, in step S103, the means for determining the sequence of the search terms determines that, of the click data of the search term corresponding to the search word, the click data corresponding to the region information set is the click data set of the search term corresponding to the search word, and in this alternative embodiment, since the click data set is determined according to the region information set, it may be considered that the click data set corresponds to or is related to the region information set. For example, the region information set includes one or more region information, and for a piece of click data of the search item corresponding to the search word, if the region information corresponding to the click data is the same as the region information in the region information set or belongs to the geographic range of the region information in the region information set, the click data belongs to the click data set. For example, the region information set includes beijing city and hebeibei province, and the region information corresponding to the first click data is beijing city, then the first click data is determined to belong to the click data set; the region information corresponding to the second click data is Shijiazhuang city, and the Shijiazhuang city belongs to Hebei province, so that the second click data is determined to belong to the click data set; and the region information corresponding to the third click data is Shenzhen city, and since Shenzhen city does not belong to Hebei province or Beijing city, the third click data is determined not to belong to the click data set, namely the click data set does not include the third click data.
It should be noted that the click data related to the embodiment of the present disclosure includes, for example, information about a display order of a search item clicked among the search items corresponding to the search term displayed by the search engine by the user, a number (times) of clicks of the search item clicked, a click rate of the search item clicked, and/or a sum of numbers (times) of clicks of search items of the search term, and may also include various forms of data related to clicks of search items of the search term, which is not limited by the present disclosure.
It should be noted that the search data of the user recorded by the search engine and the like has a time characteristic, for example, a time that may be recorded when the user clicks on the search item corresponding to the search term may occur, so in step S103, the click data set may be determined according to a preset time period, for example, the click data set may be determined according to the region information set from the click data of the search item corresponding to the search term that occurs in the last year, or the click data set may be determined according to the region information set from the click data of the search item corresponding to the search term that occurs in the last natural month.
S104, determining the sequence of the search items corresponding to the search terms according to the click data set.
In step S104, the means for determining the order of search items determines the order of the search items corresponding to the search word based on the set of click data determined in step S103, so that when the user searches for the search word through the search engine, the search items corresponding to the search word are displayed in the order determined in step S104.
It should be noted that, when determining the order of the search items corresponding to the search terms according to the click data set, an existing or future algorithm, such as various forms of click model algorithms, may be used, which is not limited in this disclosure.
Since the click data set in step S104 includes click data of the search term corresponding to the search term, and the click data corresponds to or is related to the region information set, determining the sequence of the search term corresponding to the search term according to the click data set will make the determined sequence of the search term have regional characteristics, which can bring better user experience.
Fig. 2 is a flowchart illustrating an alternative embodiment of determining a set of regional information provided by the present disclosure. In the method for determining the sequence of search items provided by the embodiment of the disclosure, it is expected that the determined search items have regional characteristics, so the click data set is determined according to the region information set, and then the sequence of the search items corresponding to the search terms is determined according to the click data set corresponding to the region information set, but different regions may have different characteristics, for example, related searches may be performed on food, and the north and south preferences of food may be greatly different, and if the region information set includes both the north region and the south region, the determined sequence of the search items about the food based on the region information set may bring negative user experience. In view of this, the embodiment of the present disclosure further provides an optional embodiment of the determining the region information set, so as to enable the sequence of the search items to exhibit an accurate region characteristic, thereby bringing about good user experience.
As shown in fig. 2, in this alternative embodiment, in step S103: before determining the click data set of the search term corresponding to the search term according to the region information set, the method further includes:
step S201, determining M search items, wherein M is a positive integer;
in step S201, the means for determining the order of search items determines M search items. Wherein the M search terms correspond to one or more search terms. In this alternative embodiment, it is desirable that each region in the determined region information set has the same or similar preferences and characteristics, so in step S201, M is made to take a larger value as much as possible to determine a larger number of search terms, so as to determine a suitable region information set based on the M search terms.
In an alternative embodiment, determining the M search terms comprises: determining a preset time period; determining P high-frequency search terms in the preset time period, wherein P is a positive integer; determining the first Q search items in the preset time period corresponding to each high-frequency search word in the P high-frequency search words, wherein Q is a positive integer, and M is P. The high-frequency search words comprise P search words, the number of times of searching in the preset time period reaches a preset value, or comprise the first P search words, the number of times of searching in the preset time period is the highest. The preset sequence includes an existing sequence of the search items corresponding to each of the P high-frequency search terms, and as can be understood by those skilled in the art, for one search term of the P high-frequency search terms, the search items corresponding to the one search term are already sorted by an order-determining algorithm in the prior art, for example, a click model algorithm is applied according to click data in a certain time period.
As an example, when the preset period includes a period of the last natural month, i.e., from 0 point on the first day to 24 points on the last day of the last natural month, so as to determine the M search terms, the first step: determining P search terms, the number of which reaches a preset value, searched in the time period of the last natural month, or P search terms, the number of which is the highest, searched in the time period of the last natural month, and for each search term in the P search terms, including a search term corresponding thereto, as understood by those skilled in the art, the search terms corresponding to the P search terms have a presentation order, so that the second step: the first Q search terms corresponding to each of the P search terms are determined, which results in M ═ P × Q search terms, and optionally, M ═ 200, and Q ═ 100, that is, 20000 search terms are obtained for each search term taking the first 100 of the 200 search terms searched most in the period of the last natural month.
Step S202, determining click data sets corresponding to the M search terms;
in step S202, the means for determining the order of the search terms determines click data sets corresponding to the M search terms, wherein the click data sets corresponding to the M search terms include click data for each of the M search terms. As described above, the click data according to the embodiment of the present disclosure includes, for example, information on a display order of a search item clicked among the search items corresponding to the search term displayed by the search engine by the user, a number (times) of clicks of the search item clicked, a click rate of the search item clicked, and/or a sum of the number (times) of clicks of the search items of the search term, and may also include various forms of data related to clicks of the search item of the search term, which is not limited by the present disclosure. As mentioned above, the search data of the user recorded by the search engine and the like has a time characteristic, for example, a time that may be recorded when the user clicks on the search item corresponding to the search term, so in step S202, the click data sets corresponding to the M search items may be determined according to a preset time period, and the selection of the preset time period is not limited in the present disclosure.
Step S203, determining N click data subsets according to N pieces of region information and the click data sets corresponding to the M search items, wherein the N click data subsets correspond to the N pieces of region information one by one, and N is a positive integer;
the M search terms include a large number of search terms, and the click data corresponding to the M search terms includes click data corresponding to different regions, so in step S203, N click data subsets may be determined according to N region information and the click data sets corresponding to the M search terms, where the N click data subsets correspond to the N region information one-to-one, and N is a positive integer. As described above, when a user searches using a search engine, the search engine or the like records various search data of the user through a log file or the like, for example, records region information of a current location of the user, or region information submitted by the user at the time of registration, so that the search data, for example, click data, of the search item corresponding to the search word by the user corresponds to the region information, and thus step S203 can be implemented by using the region information recorded by the search engine.
In an optional embodiment, among the click data corresponding to the M search terms, click data corresponding to first region information in the N region information is determined as a first click data subset in the N click data subsets, where the first click data subset corresponds to the first region information, and similarly, click data subsets other than the first click data subset in the N click data subsets may be determined according to region information other than the first region information domain in the N region information.
In yet another optional embodiment, click data corresponding to the N regional information is obtained from the click data sets corresponding to the M search terms; and dividing click data corresponding to the N pieces of region information into N click data subsets according to the N pieces of region information, wherein the N click data subsets correspond to the N pieces of region information one by one.
Step S204, respectively determining N click score vectors corresponding to the M search items according to the N click data subsets, wherein each click score vector in the N click score vectors comprises M dimensions, and the N click score vectors respectively correspond to the N region information corresponding to the N click data subsets one by one;
since the N click data subsets include click data of the M search terms generated by N different regions, in step S204, click score vectors may be calculated for the M search terms based on the N click data subsets, so as to obtain N click score vectors, where each click score vector includes M dimensions. Wherein, an existing or future click score vector calculation method may be adopted, for example, a click model algorithm is applied to each of the N click data subsets, so as to obtain N click score vectors, each click score vector including click scores (i.e., M dimensions) corresponding to the M search terms.
Step S205, clustering the N click score vectors into X classes by a clustering algorithm, wherein X is a positive integer;
the clustering algorithm can gather the same or similar features together according to the dimension of the input vector, and common clustering algorithms comprise a K-Means algorithm, a K-Medoids algorithm, a Clarans algorithm and the like. In step S205, a clustering algorithm may be applied to the N click score vectors determined in step S204 for clustering, and since the N click score vectors correspond to N pieces of region information one to one, region information having the same or similar click preferences may be clustered together by the clustering algorithm. In an alternative embodiment, the clustering algorithm would group the N click score vectors into 4 or 5 classes, i.e., X ═ 4 or 5, by including a K-Means algorithm, e.g., entering a cluster value of 4 or 5, etc. For the clustering result, it can be obviously found that the click score vectors corresponding to the region information of Beijing, Shanghai, Shenzhen, etc. are grouped into one type, and the click score vectors corresponding to the region information of hong Kong, Macau, Taiwan, etc. are grouped into one type, etc.
Step S206, determining a first class from the X classes;
step S207, determining the region information set according to the region information corresponding to the click score vector in the first class.
In step S206 and step S207, the first category may be determined from the clustering result, and the region information set may be determined according to the region information corresponding to the click score vector in the first category. Optionally, the union of the region information corresponding to the click score vectors in the first class is used as the region information set.
The region information set determined in the above manner has the same or similar click preferences as the users of the regions corresponding to the region information set, and then the click data set of the search items corresponding to the search terms in step S101 is determined according to the region information set, and the order of the search items is determined based on the click data set, so that the order of the search items determined based on the click data set has region characteristics, and better user experience can be brought.
FIG. 3 is a flow diagram illustrating an alternative embodiment of a method of determining an order of search terms provided by the present disclosure.
As shown in fig. 3, in this alternative embodiment, in addition to steps S101 to S104 provided in the embodiment of the present disclosure, after step S104, the method further includes:
step S301, receiving a query from a client, wherein the query corresponds to the search term;
the order of the search terms corresponding to the search terms is determined in step S104, so that when a user submits a query corresponding to the search terms through a client, the user can be presented with the order of the search terms determined in step S104. Therefore, in step S301, a query of the user is first received from the client, the query corresponding to the search term.
Step S302, in response to determining that the relevant region of the client belongs to the region information set, displaying the search items corresponding to the search terms according to the sequence of the search items corresponding to the search terms.
In step S302, if it is determined that the relevant region of the client belongs to the region information set, the search terms corresponding to the search terms are displayed according to the sequence of the search terms corresponding to the search terms, where optionally, the relevant region includes a user registration region of the client or a region where the client is located. That is, the sequence of the search items corresponding to the search terms is related to the region information set, which reflects the search preference of the user in the region corresponding to the region information set to some extent, and when it is determined that the client submitting the query is also related to the region information, the search result is presented to the user according to the sequence of the search items corresponding to the search terms determined in step S104, so as to bring a good user experience to the user.
Fig. 4 is a schematic structural diagram illustrating an embodiment of an apparatus 400 for determining an order of search terms according to an embodiment of the present disclosure, and as shown in fig. 4, the apparatus 400 for determining an order of search terms includes a search term determining module 401, a search term determining module 402, a click data set determining module 403, and an order determining module 404.
The search term determining module 401 is configured to determine a search term; the search item determination module 402 is configured to determine a search item corresponding to the search term; the click data set determining module 403 is configured to determine, according to a region information set, a click data set of the search term corresponding to the search term; the order determining module 404 is configured to determine, according to the click data set, an order of the search items corresponding to the search term.
The apparatus shown in fig. 4 may perform the method of the embodiment shown in fig. 1, fig. 2, and/or fig. 3, and for parts of this embodiment not described in detail, reference may be made to the related description of the embodiment shown in fig. 1, fig. 2, and/or fig. 3. The implementation process and technical effect of the technical solution are described in the embodiments shown in fig. 1, fig. 2, and/or fig. 3, and are not described herein again.
Referring now to FIG. 5, a block diagram of an electronic device 500 suitable for use in implementing embodiments of the present disclosure is shown. The electronic devices in the embodiments of the present disclosure may include, but are not limited to, mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), in-vehicle terminals (e.g., car navigation terminals), and the like, and fixed terminals such as digital TVs, desktop computers, and the like. The electronic device shown in fig. 5 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. 5, electronic device 500 may include a processing means (e.g., central processing unit, graphics processor, etc.) 501 that may perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM)502 or a program loaded from a storage means 508 into a Random Access Memory (RAM) 503. In the RAM 503, various programs and data necessary for the operation of the electronic apparatus 500 are also stored. The processing device 501, the ROM 502, and the RAM 503 are connected to each other through a bus or a communication line 504. An input/output (I/O) interface 505 is also connected to the bus or communication line 504.
Generally, the following devices may be connected to the I/O interface 505: input devices 506 including, for example, a touch screen, touch pad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; output devices 507 including, for example, a Liquid Crystal Display (LCD), speakers, vibrators, and the like; storage devices 508 including, for example, magnetic tape, hard disk, etc.; and a communication device 509. The communication means 509 may allow the electronic device 500 to communicate with other devices wirelessly or by wire to exchange data. While fig. 5 illustrates an electronic device 500 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 embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network via the communication means 509, or installed from the storage means 508, or installed from the ROM 502. The computer program performs the above-described functions defined in the methods of the embodiments of the present disclosure when executed by the processing device 501.
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 include, 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.
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 perform the method of determining an order of search items in the above embodiments.
Computer program code for carrying out operations for aspects of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any 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 units described in the embodiments of the present disclosure may be implemented by software or hardware. Where the name of an element does not in some cases constitute a limitation on the element itself.
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.
In accordance with one or more embodiments of the present disclosure, there is provided a method of determining an order of search terms, including: determining a search term; determining a search term corresponding to the search term; determining a click data set of the search item corresponding to the search word according to a region information set; and determining the sequence of the search items corresponding to the search terms according to the click data set.
Further, before determining the click data set of the search term corresponding to the search term according to the region information set, the method further includes: determining M search terms, wherein M is a positive integer; determining click data sets corresponding to the M search terms; determining N click data subsets according to the N pieces of region information and the click data sets corresponding to the M search items, wherein the N click data subsets correspond to the N pieces of region information one by one, and N is a positive integer; determining N click score vectors corresponding to the M search items according to the N click data subsets, wherein each click score vector in the N click score vectors comprises M dimensions, and the N click score vectors correspond to the N region information corresponding to the N click data subsets one by one; clustering the N click score vectors into X classes by a clustering algorithm, wherein X is a positive integer; determining a first class from the X classes; and determining the region information set according to the region information corresponding to the click score vector in the first class.
Further, the determining M search terms includes: determining a preset time period; determining P high-frequency search terms in the preset time period, wherein P is a positive integer; determining the first Q search items in the preset time period corresponding to each high-frequency search word in the P high-frequency search words, wherein Q is a positive integer, and M is P.
Further, the P high-frequency search terms include P search terms, the number of times of which is searched in the preset time period reaches a preset value, or include the first P search terms, the number of times of which is searched in the preset time period is the highest.
Further, the determining N click data subsets according to the N pieces of region information and the click data sets corresponding to the M search terms, where the N click data subsets correspond to the N pieces of region information one to one, includes: acquiring click data corresponding to the N pieces of region information from the click data sets corresponding to the M search terms; and dividing click data corresponding to the N pieces of region information into N click data subsets according to the N pieces of region information, wherein the N click data subsets correspond to the N pieces of region information one by one.
Further, the determining the region information set according to the region information corresponding to the click score vector in the first class includes: and taking the union of the region information corresponding to the click score vectors in the first class as the region information set.
Further, after the determining the order of the search terms corresponding to the search terms according to the click data set, the method further includes: receiving a query from a client, the query corresponding to the search term; and in response to determining that the relevant region of the client belongs to the region information set, displaying the search items corresponding to the search terms according to the sequence of the search items corresponding to the search terms.
Further, the relevant region includes a user registration region of the client or a region where the client is located.
In accordance with one or more embodiments of the present disclosure, there is provided an apparatus for determining an order of search items, including: the search word determining module is used for determining search words; the search item determining module is used for determining search items corresponding to the search terms; the click data set determining module is used for determining a click data set of the search item corresponding to the search word according to a region information set; and the sequence determining module is used for determining the sequence of the search items corresponding to the search terms according to the click data set.
Further, the apparatus for determining the sequence of search terms further includes a geographic information set determination module, where the geographic information set determination module is configured to: determining M search terms, wherein M is a positive integer; determining click data sets corresponding to the M search terms; determining N click data subsets according to the N pieces of region information and the click data sets corresponding to the M search items, wherein the N click data subsets correspond to the N pieces of region information one by one, and N is a positive integer; determining N click score vectors corresponding to the M search items according to the N click data subsets, wherein each click score vector in the N click score vectors comprises M dimensions, and the N click score vectors correspond to the N region information corresponding to the N click data subsets one by one; clustering the N click score vectors into X classes by a clustering algorithm, wherein X is a positive integer; determining a first class from the X classes; and determining the region information set according to the region information corresponding to the click score vector in the first class.
Further, the region information set determining module is further configured to: determining a preset time period; determining P high-frequency search terms in the preset time period, wherein P is a positive integer; determining the first Q search items in the preset time period corresponding to each high-frequency search word in the P high-frequency search words, wherein Q is a positive integer, and M is P.
Further, the P high-frequency search terms include P search terms, the number of times of which is searched in the preset time period reaches a preset value, or include the first P search terms, the number of times of which is searched in the preset time period is the highest.
Further, the region information set determining module is further configured to: acquiring click data corresponding to the N pieces of region information from the click data sets corresponding to the M search terms; and dividing click data corresponding to the N pieces of region information into N click data subsets according to the N pieces of region information, wherein the N click data subsets correspond to the N pieces of region information one by one.
Further, the region information set determining module is further configured to: and taking the union of the region information corresponding to the click score vectors in the first class as the region information set.
Further, the apparatus for determining an order of search items further comprises a search presentation module, the search presentation module is configured to: receiving a query from a client, the query corresponding to the search term; and in response to determining that the relevant region of the client belongs to the region information set, displaying the search items corresponding to the search terms according to the sequence of the search items corresponding to the search terms.
Further, the relevant region includes a user registration region of the client or a region where the client is located.
According to one or more embodiments of the present disclosure, there is provided an electronic device including: a memory for storing computer readable instructions; and one or more processors coupled with the memory for executing the computer readable instructions, such that the processors when executed implement the method of determining an order of search terms of any of the preceding first aspects.
According to one or more embodiments of the present disclosure, there is provided a non-transitory computer readable storage medium characterized in that it stores computer instructions which, when executed by a computer, cause the computer to perform the method of determining the order of search items of any of the preceding first aspects.
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.
Claims (11)
1. A method of determining an order of search terms, comprising:
determining a search term;
determining a search term corresponding to the search term;
determining a click data set of the search item corresponding to the search word according to a region information set;
and determining the sequence of the search items corresponding to the search terms according to the click data set.
2. The method of determining an order of search terms of claim 1, wherein prior to the determining a click data set of the search terms corresponding to the search term from a set of geographic information, the method further comprises:
determining M search terms, wherein M is a positive integer;
determining click data sets corresponding to the M search terms;
determining N click data subsets according to the N pieces of region information and the click data sets corresponding to the M search items, wherein the N click data subsets correspond to the N pieces of region information one by one, and N is a positive integer;
determining N click score vectors corresponding to the M search items according to the N click data subsets, wherein each click score vector in the N click score vectors comprises M dimensions, and the N click score vectors correspond to the N region information corresponding to the N click data subsets one by one;
clustering the N click score vectors into X classes by a clustering algorithm, wherein X is a positive integer;
determining a first class from the X classes;
and determining the region information set according to the region information corresponding to the click score vector in the first class.
3. The method of determining an order of search terms of claim 2, wherein said determining M search terms comprises:
determining a preset time period;
determining P high-frequency search terms in the preset time period, wherein P is a positive integer;
determining the first Q search items in the preset time period corresponding to each high-frequency search word in the P high-frequency search words, wherein Q is a positive integer, and M is P.
4. The method of determining an order of search items according to claim 3, wherein the P high frequency search terms include P search terms searched for a predetermined number of times in the predetermined time period, or include the first P search terms searched for a highest number of times in the predetermined time period.
5. The method for determining the order of search terms according to any one of claims 2 to 4, wherein the determining N subsets of click data according to N region information and the click data sets corresponding to the M search terms, the N subsets of click data corresponding to the N region information one-to-one includes:
acquiring click data corresponding to the N pieces of region information from the click data sets corresponding to the M search terms;
and dividing click data corresponding to the N pieces of region information into N click data subsets according to the N pieces of region information, wherein the N click data subsets correspond to the N pieces of region information one by one.
6. The method for determining the order of search terms according to any one of claims 2-4, wherein the determining the set of regional information according to the regional information corresponding to the click score vector in the first class comprises:
and taking the union of the region information corresponding to the click score vectors in the first class as the region information set.
7. The method of determining an order of search terms of claim 1, wherein after said determining an order of the search terms corresponding to the search term from the click data set, the method further comprises:
receiving a query from a client, the query corresponding to the search term;
and in response to determining that the relevant region of the client belongs to the region information set, displaying the search items corresponding to the search terms according to the sequence of the search items corresponding to the search terms.
8. The method of claim 7, wherein the relevant geographic area comprises a user registration geographic area of the client or a geographic area in which the client is located.
9. An apparatus for determining an order of search terms, comprising:
the search word determining module is used for determining search words;
the search item determining module is used for determining search items corresponding to the search terms;
the click data set determining module is used for determining a click data set of the search item corresponding to the search word according to a region information set;
and the sequence determining module is used for determining the sequence of the search items corresponding to the search terms according to the click data set.
10. An electronic device, comprising:
a memory for storing computer readable instructions; and
a processor for executing the computer readable instructions such that the processor when executed implements a method of determining an order of search terms according to any of claims 1-8.
11. A non-transitory computer readable storage medium storing computer readable instructions which, when executed by a computer, cause the computer to perform the method of determining an order of search terms of any of claims 1-8.
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