CN108170293A - Input the personalized recommendation method and device of association - Google Patents
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
- G06F3/02—Input arrangements using manually operated switches, e.g. using keyboards or dials
- G06F3/023—Arrangements for converting discrete items of information into a coded form, e.g. arrangements for interpreting keyboard generated codes as alphanumeric codes, operand codes or instruction codes
- G06F3/0233—Character input methods
- G06F3/0237—Character input methods using prediction or retrieval techniques
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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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Abstract
The present invention provides a kind of personalized recommendation method and device for inputting association, this method includes：By receiving search query input by user, identify the type of current search query, when analyzing the Pinyin information in the part or all of phonetic hit input association Candidate Set of current search query, associate candidate word using the historical search word corresponding to the Pinyin information of hit as input, the personalized recommendation of input association is carried out, improves the efficiency of the personalized recommendation method of input association.User does not need to Manual Override search term and is re-searched for can accurately expecting suitable search term to express search intention yet, and then can improve the accuracy of the personalized recommendation method of input association.Further combined with existing input association model, the searching cost of user can be reduced, user is helped quickly and easily to find search result, the export effect of entire search box is improved, can further promote search experience.
Description
Technical Field
The invention relates to the technical field of computers, in particular to an input association personalized recommendation method and device.
Background
With the rapid development of networks, people nowadays prefer to search some materials for learning or interested by themselves through a search engine. In the process of using the existing search engine, when a user manually inputs, such as inputting pinyin incorrectly, and after clicking a search result, any recommended word on a page is displayed, at the moment, the user needs to manually rewrite the search word for re-searching, if the user has a query with high frequency and needs to repeatedly search, such as official website addressing and video and audio, the user needs to creep as complete pinyin bytes every time, the user cannot accurately think of a proper search word to express a search intention, and the existing input association recommendation method has the defects of low efficiency, low accuracy and high input cost.
Disclosure of Invention
In view of the above, the present invention has been made to provide an input association personalized recommendation method and apparatus that overcomes or at least partially solves the above problems.
According to an aspect of the present invention, there is provided a personalized recommendation method for input association, including:
receiving a search query input by a user, and identifying the type of the current search query;
if the current search query is identified to be a pinyin type, acquiring a preset input association candidate set, wherein the input association candidate set comprises user history search words and corresponding pinyin information;
and when partial or all pinyins of the current search query hit the pinyin information in the input association candidate set, taking the historical search word corresponding to the hit pinyin information as an input association candidate word, and performing personalized recommendation of input association.
Optionally, the performing personalized recommendation of input association by using the history search word corresponding to the hit pinyin information as an input association candidate word includes:
according to the search query, obtaining a preset number of input association candidate words of the search query from an existing input association recommendation model;
and uniformly sequencing the acquired input association candidate words with the preset number and the history search words corresponding to the hit pinyin information, and taking the sequencing result as the input association for personalized recommendation.
Optionally, the uniformly sorting the acquired preset number of input associated candidate words and the historical search words corresponding to the hit pinyin information includes:
and uniformly sequencing according to the sequence that the priority level of the historical search word corresponding to the hit pinyin information is higher than the priority levels of the input association candidate words in the preset number.
Optionally, the method further comprises:
and mining a user search behavior log in the network, extracting hot spot candidate words from the user search behavior log, and generating an existing input association candidate model.
Optionally, the method further comprises:
acquiring a user history search record, and extracting user history search words from the user history search record;
translating the extracted historical search words of the user to obtain pinyin information corresponding to the historical search words of the user;
and establishing the input association candidate set according to the corresponding relation between the historical search words of the user and pinyin information obtained by translating the historical search words.
Optionally, if the method is applied to a browser, the obtaining of the user history search record includes:
and acquiring the user history search records recorded by the browser from the Local Storage of the browser.
Optionally, the method further comprises: and storing the established input association candidate set locally in the browser.
Optionally, analyzing pinyin information that part of pinyins of the current search query hit in the input association candidate set includes:
acquiring a prefix of a current search query, wherein the prefix comprises at least one complete pinyin field starting from a pinyin initial position, and one complete pinyin field corresponds to one Chinese character;
prefix matching is carried out on the pinyin prefix of the query and the prefix of pinyin information corresponding to each user historical search word in the input association candidate set;
if the input association candidate set has pinyin information with consistent prefix matching, part of pinyin of the current search query hits the pinyin information in the input association candidate set.
Optionally, analyzing pinyin information that part of pinyins of the current search query hit in the input association candidate set includes:
acquiring a plurality of complete pinyin fields in the pinyin of the search query, wherein one complete pinyin field corresponds to one Chinese character;
matching the obtained multiple complete pinyin fields with pinyin information corresponding to historical search words of each user in the input association candidate set;
if the pinyin fields matched with the specified number of complete pinyin fields of the search query exist in the pinyin information corresponding to at least one user historical search word, part of pinyin of the current search query hits pinyin information of the pinyin information in the input association candidate set.
Optionally, analyzing all pinyins of the current search query hit the pinyin information in the input association candidate set, including:
matching the pinyin of the search query with pinyin information corresponding to historical search words of each user in the input association candidate set;
and if all pinyins of the search query are matched with the pinyin information corresponding to at least one user historical search word, all pinyins of the current search query hit the pinyin information in the input association candidate set.
Optionally, the method further comprises:
if the current search query is identified and obtained to be not the pinyin type, acquiring a preset input association candidate set;
and analyzing whether part or all of the keywords of the current search query hit the historical search words in the input association candidate set, and if so, taking the hit historical search words as input association candidate words to perform personalized recommendation of input association.
According to another aspect of the present invention, there is provided a personalized recommendation apparatus for inputting a conjuction, including:
the identification module is suitable for receiving a search query input by a user and identifying the type of the current search query;
the acquisition module is suitable for acquiring a preset input association candidate set if the current search query is identified to be a pinyin type, wherein the input association candidate set comprises user history search words and corresponding pinyin information;
and the recommending module is suitable for analyzing that partial or all pinyins of the current search query hit the pinyin information in the input association candidate set, and taking a historical search word corresponding to the hit pinyin information as an input association candidate word to perform personalized recommendation of the input association.
Optionally, the recommendation module is further adapted to:
according to the search query, obtaining a preset number of input association candidate words of the search query from an existing input association recommendation model;
and uniformly sequencing the acquired input association candidate words with the preset number and the history search words corresponding to the hit pinyin information, and taking the sequencing result as the input association for personalized recommendation.
Optionally, the recommendation module is further adapted to:
and uniformly sequencing according to the priority level of the historical search word corresponding to the hit pinyin information and the priority level of the input association candidate words higher than the preset number.
Optionally, the apparatus further comprises:
the generating module is suitable for mining a user searching behavior log in a network, extracting hot spot candidate words from the user searching behavior log and generating an existing input association candidate model.
Optionally, the apparatus further comprises a setup module adapted to:
acquiring a user history search record, and extracting user history search words from the user history search record;
translating the extracted historical search words of the user to obtain pinyin information corresponding to the historical search words of the user;
and establishing the input association candidate set according to the corresponding relation between the historical search words of the user and pinyin information obtained by translating the historical search words.
Optionally, if the apparatus is applied to a browser, the establishing module is further adapted to:
and acquiring the user history search records recorded by the browser from the Local Storage of the browser.
Optionally, the system further comprises a storage module adapted to:
and storing the established input association candidate set locally in the browser.
Optionally, the recommendation module is further adapted to:
acquiring a prefix of a current search query, wherein the prefix comprises at least one complete pinyin field starting from a pinyin initial position, and one complete pinyin field corresponds to one Chinese character;
prefix matching is carried out on the pinyin prefix of the query and the prefix of pinyin information corresponding to each user historical search word in the input association candidate set;
if the input association candidate set has pinyin information with consistent prefix matching, part of pinyin of the current search query hits the pinyin information in the input association candidate set.
Optionally, the recommendation module is further adapted to:
acquiring a plurality of complete pinyin fields in the pinyin of the search query, wherein one complete pinyin field corresponds to one Chinese character;
matching the obtained multiple complete pinyin fields with pinyin information corresponding to historical search words of each user in the input association candidate set;
if the pinyin fields matched with the specified number of complete pinyin fields of the search query exist in the pinyin information corresponding to at least one user historical search word, part of pinyin of the current search query hits pinyin information of the pinyin information in the input association candidate set.
Optionally, the recommendation module is further adapted to:
matching the pinyin of the search query with pinyin information corresponding to historical search words of each user in the input association candidate set;
and if all pinyins of the search query are matched with the pinyin information corresponding to at least one user historical search word, all pinyins of the current search query hit the pinyin information in the input association candidate set.
Optionally, the obtaining module is further adapted to: if the current search query is identified and obtained to be not the pinyin type, acquiring a preset input association candidate set;
the recommendation module is further adapted to: and analyzing whether part or all of the keywords of the current search query hit the historical search words in the input association candidate set, and if so, taking the hit historical search words as input association candidate words to perform personalized recommendation of input association.
According to yet another aspect of the present invention, there is also provided a computer program comprising computer readable code which, when run on a computing device, causes the computing device to perform the method of inputting a associative personalized recommendation as described in any of the embodiments above.
According to a further aspect of the invention, there is also provided a computer readable medium in which a computer program as described above is stored.
In the embodiment of the invention, firstly, the type of the current search query is identified by receiving the search query input by a user, then, when partial or all pinyins of the current search query hit pinyin information in the input association candidate set, the historical search word corresponding to the hit pinyin information is used as the input association candidate word for personalized recommendation of the input association, and the efficiency of the personalized recommendation method of the input association is improved. The user can accurately think of the proper search word to express the search intention without manually rewriting the search word for re-searching, and the accuracy of inputting the associative personalized recommendation method can be further improved. The existing input association model is further combined, the search cost of a user can be reduced, the user can be helped to quickly and conveniently find a search result, the derivation effect of the whole search box is improved to a certain extent, and the search experience can be further improved.
The foregoing description is only an overview of the technical solutions of the present invention, and the embodiments of the present invention are described below in order to make the technical means of the present invention more clearly understood and to make the above and other objects, features, and advantages of the present invention more clearly understandable.
The above and other objects, advantages and features of the present invention will become more apparent to those skilled in the art from the following detailed description of specific embodiments thereof, taken in conjunction with the accompanying drawings.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:
FIG. 1 is a flow diagram illustrating a method for inputting a suggested personalized recommendation in accordance with one embodiment of the present invention;
FIG. 2 is a schematic diagram illustrating a part of pinyin hits of a current search query in pinyin information corresponding to a user history search word in the personalized recommendation method for input association according to an embodiment of the present invention;
FIG. 3a shows a schematic diagram of the derivation of a candidate set of input associations using a recommendation method for existing input associations;
FIG. 3b shows a schematic diagram of input idea candidate set derivation for the personalized recommendation method of input idea according to an embodiment of the invention;
FIG. 4 is a schematic structural diagram of a personalized recommendation device for input association according to an embodiment of the present invention;
FIG. 5 is a schematic diagram illustrating an alternative input-associative personalized recommendation apparatus according to an embodiment of the present invention;
FIG. 6 illustrates a block diagram of a computing device for performing a method of personalized recommendation for input association in accordance with the present invention; and
fig. 7 illustrates a storage unit for holding or carrying program code implementing the personalized recommendation method of input association according to the present invention.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
In order to solve the technical problem, an embodiment of the present invention provides a personalized recommendation method for input association. Fig. 1 is a flowchart illustrating a personalized recommendation method for inputting a conjuction according to an embodiment of the present invention. Referring to fig. 1, the method includes at least steps S102 to S106.
Step S102, receiving a search query input by a user, and identifying the type of the current search query.
In this step, the type of the search query may be pinyin or hanzi.
The search query may be a partial or complete pinyin field or a partial or complete chinese character field. For example: "qinghuadaoxue"/"qinghua", "Qinghua university"/"Qinghua", etc. In this embodiment, the listed different types of search queries are only illustrative, and the search query types mentioned herein may also be other search query types, which is not specifically limited in this embodiment of the present invention.
And step S104, if the current search query is identified and obtained to be the pinyin type, acquiring a preset input association candidate set, wherein the input association candidate set comprises the historical search words of the user and corresponding pinyin information.
In this step, an input association candidate set formed by combining the user history search words and the pinyin which has a one-to-one correspondence relationship with the user history search words is predefined. Wherein, the input association candidate set is displayed in a Chinese character mode.
And step S106, when part or all pinyins of the current search query hit pinyin information in the input association candidate set, taking a historical search word corresponding to the hit pinyin information as an input association candidate word, and performing personalized recommendation of input association.
For example: when the current search query is 'qinchuadaxue' or 'qinghua', the historical search word 'qinghua university' corresponding to the 'qinghuadaxue' or 'qinghua' is used as an input association candidate word, and personalized recommendation of input association is carried out. Therefore, the embodiment of the invention identifies the type of the current search query by receiving the search query input by the user, analyzes that when part or all pinyins of the current search query hit pinyin information in the input association candidate set, and takes a historical search word corresponding to the hit pinyin information as an input association candidate word to perform personalized recommendation of the input association, thereby improving the efficiency of the personalized recommendation method of the input association. The user can accurately think of the proper search word to express the search intention without manually rewriting the search word for re-searching, thereby improving the accuracy of inputting the associative personalized recommendation method.
The embodiment of the invention further combines the existing input association model, can reduce the search cost of the user, helps the user to quickly and conveniently find the search result, can improve the export effect of the whole search box, and further improves the search experience.
Referring to step S102 above, in an embodiment of the present invention, before receiving a search query input by a user and identifying a type of a current search query, a preset input association candidate set is already established. Wherein, the preset input association candidate set can be established by the following method:
firstly, obtaining a user history search record, and extracting a user history search word from the user history search record;
secondly, translating the extracted historical search terms of the user to obtain pinyin information corresponding to the historical search terms of the user;
and finally, establishing an input association candidate set according to the historical search words of the user and the corresponding relation between the pinyin information obtained by translating the historical search words.
If the method is applied to the browser, user history search records recorded by the browser are obtained from a Local Storage of the browser, and the established input association candidate set is stored in the Local browser.
Referring to step S104, in an embodiment of the present invention, when the current search query is identified and found not to be the pinyin type, a preset input association candidate set is also obtained.
Referring to step S106 above, in an embodiment of the present invention, the pinyin information in the partial pinyin hit input association candidate set of the current search query may be analyzed as follows:
firstly, acquiring a prefix of a current search query, wherein the prefix comprises at least one complete pinyin field starting from a pinyin initial position, and one complete pinyin field corresponds to one Chinese character;
then, prefix matching is carried out on the pinyin prefix of the query and the prefix of pinyin information corresponding to each user history search word in the input association candidate set;
and finally, if the input association candidate set has pinyin information with consistent prefix matching, part of pinyin of the query currently searched hits the pinyin information in the input association candidate set.
In an embodiment of the present invention, analyzing pinyin information in a part of pinyin hit input association candidate sets of a current search query further comprises the following steps:
acquiring a plurality of complete pinyin fields in pinyin of search query, wherein one complete pinyin field corresponds to one Chinese character;
matching the obtained multiple complete pinyin fields with pinyin information corresponding to historical search words of each user in the input association candidate set;
if the pinyin fields matched with the specified number of complete pinyin fields of the search query exist in the pinyin information corresponding to at least one user historical search word, part of pinyin of the current search query hits pinyin information input in the association candidate set.
In one embodiment, referring to fig. 2, the pinyin information corresponding to the historical search word of the user includes the pinyin "qinghuaadaaxue" corresponding to "qinghua university", and when the search query is "qinghua", the pinyin information in the input association candidate set is hit by a part of the pinyins representing the current search query.
Referring to step S106 above, in an embodiment of the present invention, the pinyin information in all pinyin hit input association candidate sets of the current search query may be analyzed as follows:
matching the pinyin of the search query with pinyin information corresponding to historical search words of each user in the input association candidate set;
and if all pinyins of the searched query are matched with the pinyin information corresponding to at least one user historical search word, all pinyins of the searched query hit and input pinyin information in the association candidate set.
In a specific embodiment, the pinyin information corresponding to the historical search words of the user includes the pinyin "chongdianbao" corresponding to the "power bank", and when the search query is "chongdianbao", the search query represents that part of the pinyin of the current search query hits and inputs the pinyin information in the association candidate set.
Referring to step S106 above, in an embodiment of the present invention, the input of the associated personalized recommendation may be performed as follows:
firstly, acquiring a preset number of input association candidate words of a search query from an existing input association recommendation model according to the search query;
and then, uniformly sequencing the acquired input association candidate words with the preset number and the history search words corresponding to the hit pinyin information, and taking the sequencing result as the input association for personalized recommendation.
In an embodiment of the present invention, the obtained preset number of input association candidate words and the history search words corresponding to the hit pinyin information may be uniformly ordered in the following manner:
and uniformly sequencing according to the priority level of the historical search words corresponding to the hit pinyin information and the priority level of the input association candidate words higher than the preset number of the input association candidate words.
In an embodiment of the present invention, the unified ranking according to the priority levels of the historical search words corresponding to the hit pinyin information and the priority levels of the input associated candidate words higher than the preset number may be implemented in the following manner:
performing first sequencing according to the sequence that the priority level of the acquired historical search words of the user is higher than the priority levels of the input association candidate words in the preset number;
and for the first sorting result, keeping the position sequence of the input association candidate words in the preset number unchanged, performing second sorting on the historical search words of the user according to the sequence of descending historical search times, and recommending the second sorting result as the input association.
The priority level of the historical search terms of the user is related to the number of search times of the historical search terms, and the priority level is higher when the number of search times is larger.
In one embodiment, the Local Storage of the browser stores a preset number of input association candidate words: the user inputs the qinghua for the first time, selects the preset input association candidate word 'qinghua' for searching, and then respectively inputs the qinghua for two times and selects the preset input association candidate word 'qinghua university' for searching, and at the moment, the input association candidate words 'qinghua' and 'qinghua university' are both history search words of the user. Referring to fig. 3a, fig. 3a is a schematic diagram of the input association candidate set derivation using the existing recommendation method for input association. Wherein, the sequencing process of the emotion, the Qinghua university, the Qinghua, the blue and white porcelain and the blue and white porcelain lyrics is as follows:
firstly, sequencing the emotion, the Qinghua university, the Qinghua, the blue-white porcelain and the blue-white porcelain lyrics integrally, wherein the emotion and the Qinghua university belong to user historical search words, and the priority level of the emotion and the Qinghua university is higher than that of input association candidate words such as the emotion, the blue-white porcelain and the blue-white porcelain lyrics, so that the Qinghua university and the Qinghua university are ranked in front of the input association candidate words such as the emotion, the blue-white porcelain and the blue-white porcelain lyrics;
then, the historical search words "Qinghua" and "Qinghua university" of the user are ranked according to the search times, and the "Qinghua university" is ranked in front of the "Qinghua" because the search times of the "Qinghua university" are more than the "Qinghua".
Therefore, after two times of sequencing, the final sequencing results are ' Qinghua university ', ' Qinghua ', love words ', ' blue and white porcelain ' and ' blue and white porcelain lyrics '. Fig. 3b may be referred to for a specific sorting result, where fig. 3b is a schematic diagram of deriving an input association candidate set of the input association-based personalized recommendation method according to an embodiment of the present invention.
In an embodiment of the present invention, the method further includes: and mining a user search behavior log in the network, extracting hot candidate words from the user search behavior log, and generating an existing input association candidate model.
In one embodiment, when many network users search for the recently popular movie "aryls" through a search engine, a user search behavior log "aryls" is mined, and when other network users input a search query "fanghua" through the search engine, "aryls" are displayed as hot spot candidate words and as input association candidate words "aryls movies".
Based on the same inventive concept, an input association personalized recommendation device is further provided in the embodiments of the present invention, and fig. 4 is a schematic structural diagram of an input association personalized recommendation device according to an embodiment of the present invention. Referring to fig. 4, the apparatus 400 for inputting a suggested personalized recommendation may include at least an identification module 410, an acquisition module 420, and a recommendation module 430.
The functions of the components or devices of the input association personalized recommendation device 400 and the connection relationship between the components will now be described:
the identification module 410 is suitable for receiving a search query input by a user and identifying the type of the current search query;
an obtaining module 420, coupled to the identifying module 410, adapted to obtain a preset input association candidate set if the current search query obtained by identification is a pinyin type, where the input association candidate set includes user history search words and corresponding pinyin information;
the recommending module 430 is coupled with the obtaining module 420 and is adapted to analyze that when part or all pinyins of the current search query hit pinyin information in the input association candidate set, take historical search words corresponding to the hit pinyin information as input association candidate words and perform personalized recommendation of input association.
In an embodiment of the present invention, the recommending module 430 is further adapted to obtain a preset number of input association candidate words of the search query from the existing input association recommending model according to the search query.
In an embodiment of the present invention, the recommending module 430 is further adapted to perform a unified ranking according to the priority level of the historical search word corresponding to the hit pinyin information, which is higher than the priority level of the input association candidate words in a preset number.
An embodiment of the present invention further provides another personalized recommendation device for inputting associations, and fig. 5 is a schematic structural diagram of another personalized recommendation device for inputting associations according to an embodiment of the present invention. Referring to fig. 5, the input association-based personalized recommendation apparatus 400 includes a generation module 440, a creation module 450, and a storage module 460 in addition to the above modules. Wherein,
and the generating module 440 is coupled with the recommending module 430 and is adapted to mine a user search behavior log in the network, extract hotspot candidate words from the user search behavior log, and generate an existing input association candidate model.
The establishing module 450 is coupled to the generating module 440 and adapted to obtain a historical search record of the user, extract a historical search word of the user from the historical search record of the user, translate the extracted historical search word of the user to obtain pinyin information corresponding to the historical search word of the user, and establish an input association candidate set according to a corresponding relationship between the historical search word of the user and the pinyin information obtained by translating the historical search word of the user.
In an embodiment of the present invention, if the apparatus is applied to a browser, the creating module 450 is further adapted to obtain a user history search record recorded in a Local Storage of the browser.
The storing module 460, coupled to the establishing module 450, stores the established input association candidate set locally in the browser.
In an embodiment of the present invention, the recommending module 430 is further adapted to obtain a prefix of the currently searched query, where the prefix includes at least one complete pinyin field starting from the pinyin initial position, and one complete pinyin field corresponds to one chinese character, perform prefix matching on the pinyin prefix of the query and prefixes of pinyin information corresponding to historical search words of each user in the input association candidate set, and if there is pinyin information whose prefix matching is consistent in the input association candidate set, hit in part of the pinyins of the currently searched query in the input association candidate set.
In an embodiment of the present invention, the recommending module 430 is further adapted to obtain a plurality of complete pinyin fields in the pinyin for a search query, where one complete pinyin field corresponds to one chinese character, match the obtained plurality of complete pinyin fields with the pinyin information corresponding to each user history search word in the input association candidate set, and if at least one pinyin information corresponding to a user history search word has pinyin fields that match the specified number of complete pinyin fields of the search query, hit the pinyin information in the input association candidate set in a part of the pinyins of the currently searched query.
In an embodiment of the present invention, the recommending module 430 is further adapted to match the pinyin of the search query with pinyin information corresponding to each user history search word in the input association candidate set, and if all the pinyins of the search query are matched with the pinyin information corresponding to at least one user history search word, all the pinyins of the current search query hit the pinyin information in the input association candidate set.
In an embodiment of the present invention, the obtaining module 420 is further adapted to obtain a preset input association candidate set if it is identified that the current search query is not a pinyin type.
In an embodiment of the present invention, the recommending module 430 is further adapted to analyze whether part or all of the keywords of the current search query hit the historical search words in the input association candidate set, and if so, perform personalized recommendation of the input association by using the hit historical search words as the input association candidate words.
Embodiments of the present invention further provide a computer program, which includes computer readable code, when the computer readable code runs on a computing device, causes the computing device to execute the personalized recommendation method of inputting a conjecture according to any of the above embodiments.
Embodiments of the present invention also provide a computer readable medium in which a computer program as above is stored.
According to any one or a combination of the above preferred embodiments, the following advantages can be achieved by the embodiments of the present invention:
in the embodiment of the invention, the type of the current search query is identified by receiving the search query input by the user, and then the history search word corresponding to the hit pinyin information is used as an input association candidate word to perform the personalized recommendation of the input association, so that the efficiency of the personalized recommendation method of the input association is improved. The user can accurately think of the proper search word to express the search intention without manually rewriting the search word for re-searching, thereby improving the accuracy of inputting the associative personalized recommendation method. The existing input association model is further combined, the search cost of a user can be reduced, the user can be helped to quickly and conveniently find a search result, the export effect of the whole search box can be improved, and the search experience is further improved.
In the description provided herein, numerous specific details are set forth. It is understood, however, that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.
Similarly, it should be appreciated that in the foregoing description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be interpreted as reflecting an intention that: that the invention as claimed requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.
Those skilled in the art will appreciate that the modules in the device in an embodiment may be adaptively changed and disposed in one or more devices different from the embodiment. The modules or units or components of the embodiments may be combined into one module or unit or component, and furthermore they may be divided into a plurality of sub-modules or sub-units or sub-components. All of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or elements of any method or apparatus so disclosed, may be combined in any combination, except combinations where at least some of such features and/or processes or elements are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.
Furthermore, those skilled in the art will appreciate that while some embodiments described herein include some features included in other embodiments, rather than other features, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the claims, any of the claimed embodiments may be used in any combination.
The various component embodiments of the invention may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. It will be appreciated by those skilled in the art that a microprocessor or Digital Signal Processor (DSP) may be used in practice to implement some or all of the functions of some or all of the components of the input-associative personalized recommendation device according to embodiments of the present invention. The present invention may also be embodied as apparatus or device programs (e.g., computer programs and computer program products) for performing a portion or all of the methods described herein. Such programs implementing the present invention may be stored on computer-readable media or may be in the form of one or more signals. Such a signal may be downloaded from an internet website or provided on a carrier signal or in any other form.
For example, FIG. 6 illustrates a block diagram of a computing device that may implement the personalized recommendation method of input association. The computing device conventionally includes a computer program product or computer-readable medium in the form of a processor 610 and a memory 620. The memory 620 may be an electronic memory such as a flash memory, an EEPROM (electrically erasable programmable read only memory), an EPROM, a hard disk, or a ROM. The memory 620 has a memory space 630 storing program code 631 for performing any of the method steps of the method described above. For example, the memory space 630 storing the program codes may include respective program codes 631 respectively for implementing various steps in the above methods. The program code can be read from or written to one or more computer program products. These computer program products comprise a program code carrier such as a hard disk, a Compact Disc (CD), a memory card or a floppy disk. Such a computer program product is typically a portable or fixed storage unit as shown for example in fig. 7. The storage unit may have storage segments, storage spaces, etc. arranged similarly to the memory 620 in the computing device of fig. 6. The program code may be compressed, for example, in a suitable form. Typically, the memory unit comprises computer readable code 631' for performing the steps of the method of the invention, i.e. code that can be read by a processor such as 610, which when run by a computing device causes the computing device to perform the steps of the method described above.
It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The usage of the words first, second and third, etcetera do not indicate any ordering. These words may be interpreted as names.
Thus, it should be appreciated by those skilled in the art that while a number of exemplary embodiments of the invention have been illustrated and described in detail herein, many other variations or modifications consistent with the principles of the invention may be directly determined or derived from the disclosure of the present invention without departing from the spirit and scope of the invention. Accordingly, the scope of the invention should be understood and interpreted to cover all such other variations or modifications.
Claims (10)
1. A method of inputting a suggested personalized recommendation, comprising:
receiving a search query input by a user, and identifying the type of the current search query;
if the current search query is identified to be a pinyin type, acquiring a preset input association candidate set, wherein the input association candidate set comprises user history search words and corresponding pinyin information;
and when partial or all pinyins of the current search query hit the pinyin information in the input association candidate set, taking the historical search word corresponding to the hit pinyin information as an input association candidate word, and performing personalized recommendation of input association.
2. The method of claim 1, wherein the personalized recommendation of the input association is performed by taking the historical search word corresponding to the hit pinyin information as an input association candidate word, and includes:
according to the search query, obtaining a preset number of input association candidate words of the search query from an existing input association recommendation model;
and uniformly sequencing the acquired input association candidate words with the preset number and the history search words corresponding to the hit pinyin information, and taking the sequencing result as the input association for personalized recommendation.
3. The method according to claim 1 or 2, wherein the uniformly sorting the acquired preset number of input association candidate words and the history search words corresponding to the hit pinyin information includes:
and uniformly sequencing according to the sequence that the priority level of the historical search word corresponding to the hit pinyin information is higher than the priority levels of the input association candidate words in the preset number.
4. The method according to any one of claims 1-3, further comprising:
and mining a user search behavior log in the network, extracting hot spot candidate words from the user search behavior log, and generating an existing input association candidate model.
5. The method of any of claims 1-4, further comprising:
acquiring a user history search record, and extracting user history search words from the user history search record;
translating the extracted historical search words of the user to obtain pinyin information corresponding to the historical search words of the user;
and establishing the input association candidate set according to the corresponding relation between the historical search words of the user and pinyin information obtained by translating the historical search words.
6. The method according to any one of claims 1-5, wherein, if the method is applied to a browser, the obtaining the user history search record comprises:
and acquiring the user history search records recorded by the browser from the Local Storage of the browser.
7. The method of any of claims 1-6, further comprising: and storing the established input association candidate set locally in the browser.
8. An input association personalized recommendation apparatus comprising:
the identification module is suitable for receiving a search query input by a user and identifying the type of the current search query;
the acquisition module is suitable for acquiring a preset input association candidate set if the current search query is identified to be a pinyin type, wherein the input association candidate set comprises user history search words and corresponding pinyin information;
and the recommending module is suitable for analyzing that partial or all pinyins of the current search query hit the pinyin information in the input association candidate set, and taking a historical search word corresponding to the hit pinyin information as an input association candidate word to perform personalized recommendation of the input association.
9. An electronic device, comprising:
a processor; and
a memory arranged to store computer executable instructions that, when executed, cause the processor to perform the method of personalized recommendation for input association according to any of claims 1-7.
10. A computer storage medium, wherein the computer storage medium stores one or more programs that, when executed by an electronic device including a plurality of application programs, cause the electronic device to perform the personalized recommendation method of inputting a conjecture according to any one of claims 1-7.
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108983995A (en) * | 2018-06-19 | 2018-12-11 | 深圳市元征科技股份有限公司 | Information association method, device, terminal and medium |
| CN109446407A (en) * | 2018-09-18 | 2019-03-08 | 深圳壹账通智能科技有限公司 | Correlation recommendation method, apparatus, computer equipment and storage medium |
| CN109491516A (en) * | 2018-11-02 | 2019-03-19 | 北京字节跳动网络技术有限公司 | Input display methods, device, storage medium and the electronic equipment of associational word |
| CN109582155A (en) * | 2018-11-23 | 2019-04-05 | 北京字节跳动网络技术有限公司 | Input recommended method, device, storage medium and the electronic equipment of associational word |
| CN109582847A (en) * | 2018-11-23 | 2019-04-05 | 咪咕视讯科技有限公司 | Information processing method and device and storage medium |
| CN111274502A (en) * | 2020-01-19 | 2020-06-12 | 珠海格力电器股份有限公司 | Search ranking method and device, computer equipment and storage medium |
| CN112307183A (en) * | 2020-10-30 | 2021-02-02 | 北京金堤征信服务有限公司 | Search data identification method and device, electronic equipment and computer storage medium |
Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20100088303A1 (en) * | 2008-10-03 | 2010-04-08 | Microsoft Corporation | Mining new words from a query log for input method editors |
| CN102681987A (en) * | 2011-03-07 | 2012-09-19 | 北京无限讯奇信息技术有限公司 | Convenient index solution for mobile phone search |
| CN103186615A (en) * | 2011-12-30 | 2013-07-03 | 北大方正集团有限公司 | Search prompting method and system |
| CN103365833A (en) * | 2012-03-28 | 2013-10-23 | 百度在线网络技术（北京）有限公司 | Context scene based candidate word input prompt method and system for implementing same |
| CN103678675A (en) * | 2013-12-25 | 2014-03-26 | 乐视网信息技术（北京）股份有限公司 | Method, server and system for achieving searching through Pinyin |
| CN104143001A (en) * | 2014-08-01 | 2014-11-12 | 百度在线网络技术（北京）有限公司 | Search term recommending method and device |
| CN104199954A (en) * | 2012-06-26 | 2014-12-10 | 北京奇虎科技有限公司 | Recommendation system and method for search input |
| CN105824833A (en) * | 2015-01-07 | 2016-08-03 | 苏宁云商集团股份有限公司 | Keyword recommendation method and system based on user behavior feedback |
| CN106919703A (en) * | 2017-03-09 | 2017-07-04 | 北京微影时代科技有限公司 | Film information searching method and device |
| CN107273537A (en) * | 2017-06-30 | 2017-10-20 | 深圳创维数字技术有限公司 | One kind search words recommending method, set top box and storage medium |
| CN107273457A (en) * | 2017-06-01 | 2017-10-20 | 珠海市魅族科技有限公司 | A kind of searching method and device, computer installation and computer-readable recording medium |
-
2017
- 2017-12-29 CN CN201711489711.XA patent/CN108170293A/en active Pending
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20100088303A1 (en) * | 2008-10-03 | 2010-04-08 | Microsoft Corporation | Mining new words from a query log for input method editors |
| CN102681987A (en) * | 2011-03-07 | 2012-09-19 | 北京无限讯奇信息技术有限公司 | Convenient index solution for mobile phone search |
| CN103186615A (en) * | 2011-12-30 | 2013-07-03 | 北大方正集团有限公司 | Search prompting method and system |
| CN103365833A (en) * | 2012-03-28 | 2013-10-23 | 百度在线网络技术（北京）有限公司 | Context scene based candidate word input prompt method and system for implementing same |
| CN104199954A (en) * | 2012-06-26 | 2014-12-10 | 北京奇虎科技有限公司 | Recommendation system and method for search input |
| CN103678675A (en) * | 2013-12-25 | 2014-03-26 | 乐视网信息技术（北京）股份有限公司 | Method, server and system for achieving searching through Pinyin |
| CN104143001A (en) * | 2014-08-01 | 2014-11-12 | 百度在线网络技术（北京）有限公司 | Search term recommending method and device |
| CN105824833A (en) * | 2015-01-07 | 2016-08-03 | 苏宁云商集团股份有限公司 | Keyword recommendation method and system based on user behavior feedback |
| CN106919703A (en) * | 2017-03-09 | 2017-07-04 | 北京微影时代科技有限公司 | Film information searching method and device |
| CN107273457A (en) * | 2017-06-01 | 2017-10-20 | 珠海市魅族科技有限公司 | A kind of searching method and device, computer installation and computer-readable recording medium |
| CN107273537A (en) * | 2017-06-30 | 2017-10-20 | 深圳创维数字技术有限公司 | One kind search words recommending method, set top box and storage medium |
Non-Patent Citations (1)
| Title |
|---|
| 刘佳奇: "酒店订购平台搜索系统的设计与实现", 《中国优秀硕士学位论文全文数据库 信息科技辑》 * |
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108983995A (en) * | 2018-06-19 | 2018-12-11 | 深圳市元征科技股份有限公司 | Information association method, device, terminal and medium |
| CN108983995B (en) * | 2018-06-19 | 2022-05-13 | 深圳市元征科技股份有限公司 | Information association method, device, terminal and medium |
| CN109446407A (en) * | 2018-09-18 | 2019-03-08 | 深圳壹账通智能科技有限公司 | Correlation recommendation method, apparatus, computer equipment and storage medium |
| CN109491516A (en) * | 2018-11-02 | 2019-03-19 | 北京字节跳动网络技术有限公司 | Input display methods, device, storage medium and the electronic equipment of associational word |
| CN109582155A (en) * | 2018-11-23 | 2019-04-05 | 北京字节跳动网络技术有限公司 | Input recommended method, device, storage medium and the electronic equipment of associational word |
| CN109582847A (en) * | 2018-11-23 | 2019-04-05 | 咪咕视讯科技有限公司 | Information processing method and device and storage medium |
| CN109582847B (en) * | 2018-11-23 | 2021-08-24 | 咪咕视讯科技有限公司 | Information processing method and device and storage medium |
| CN111274502A (en) * | 2020-01-19 | 2020-06-12 | 珠海格力电器股份有限公司 | Search ranking method and device, computer equipment and storage medium |
| CN112307183A (en) * | 2020-10-30 | 2021-02-02 | 北京金堤征信服务有限公司 | Search data identification method and device, electronic equipment and computer storage medium |
| CN112307183B (en) * | 2020-10-30 | 2024-04-19 | 北京金堤征信服务有限公司 | Search data identification method, apparatus, electronic device and computer storage medium |
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