CN113946740A - Processing method and device for user cabin search association, electronic equipment and medium - Google Patents
Processing method and device for user cabin search association, electronic equipment and medium Download PDFInfo
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Abstract
The invention discloses a processing method, a device, electronic equipment and a storage medium for user cockpit search association, wherein the method comprises the following steps: acquiring a current search word of a current user; querying a general corpus based on the search terms to obtain a plurality of current association terms and initial evaluation information of each current association term; adjusting at least part of evaluation information of the current association words based on the user information of the current user and the current scene; sequencing the current multiple association words based on the adjusted latest evaluation information to obtain a sequencing result; and finally feeding back the sorted plurality of associative words to the user. The problem of single and random results of the user searching in the cabin is solved, and various searching requirements of the user in the cabin are better met.
Description
Technical Field
The present invention relates to the field of cabins, and in particular, to a method and an apparatus for processing user cabin search association, an electronic device, and a storage medium.
Background
During the driving process of the vehicle, users often have different search intentions.
In the prior art, a user inputs an input word into a car machine, the car machine transmits the input word into a search server, the search server gives a search prompt word list through calculation, and then the car machine displays the search prompt word list to the user through a search engine interface for the user to select.
The search prompt words are usually randomly ordered in the search prompt word list, and the search prompt words are usually historical search records of the user and are ordered based on the search time, however, the method cannot accurately meet the current search requirement of the user.
Disclosure of Invention
The invention provides a processing method and device for user cabin search association, electronic equipment and a storage medium, and aims to solve the problem that various search requirements of a user in a cabin cannot be met.
According to a first aspect of the present invention, there is provided a processing method for user cabin search association, applied to a vehicle, comprising:
acquiring a current search word of a current user;
inquiring a total corpus based on the current search word to obtain a plurality of corresponding current association words and initial evaluation information of each current association word, wherein the evaluation information represents the correlation between the current association words and the current search word;
optionally, the adjusting the evaluation information of at least part of the current association words based on the user information of the current user and the current scene includes:
determining a current special corpus in a plurality of special corpuses based on the user information of the current user and the current scene;
the plurality of special corpora comprise a plurality of user corpora and a plurality of scene corpora; the corpus in each user corpus is constructed in a manner of being adaptive to a corresponding user, and each scene corpus is constructed in a manner of being adaptive to a corresponding scene;
and inquiring the current associated words in the current corpus to obtain an inquiry result, and adjusting at least part of evaluation information of the current associated words based on the inquiry result.
Adjusting at least part of evaluation information of the current association words based on the user information of the current user and the current scene; wherein the scenario characterizes at least one of: time information, location information, weather information;
optionally, the querying, in the current corpus, the current associated word to obtain a query result, and adjusting evaluation information of at least part of the current associated word based on the query result, includes:
if any one target associative word in the plurality of current associative words belongs to at least one current corpus, then: determining corresponding click frequency evaluation information; the corresponding click frequency evaluation information represents the frequency of the first association word in the current special corpus to which the target association word belongs; and adjusting the evaluation information of the target association words based on the corresponding click frequency evaluation information.
Optionally, each specialized corpus is configured with a corresponding weighted value, and weighted values of at least some specialized corpora are different;
the adjusting the evaluation information of the target associative word based on the corresponding click frequency evaluation information includes:
and superposing the product of the click frequency evaluation information and the weighted value of the corresponding corpus on the basis of the evaluation information of the target associative word.
Sequencing the current association words based on the latest evaluation information of the current association words to obtain a current sequencing result; furthermore, the ranking result can reflect the correlation among words represented by the large volume data in the overall corpus and can also reflect the personalized preference of the user.
And feeding back the current association words to the user based on the current sorting result.
According to a second aspect of the present invention, there is provided a processing apparatus for user cabin search association, comprising:
the acquisition module is used for acquiring the current search terms of the current user;
and the query module is used for querying the overall corpus based on the current search word to obtain a plurality of corresponding current association words and initial evaluation information of each current association word, and the evaluation information represents the correlation between the current association words and the current search word.
The adjusting module is used for adjusting at least part of evaluation information of the current association words based on the user information of the current user and the current scene; wherein the scenario characterizes at least one of: time information, location information, weather information;
the sorting module is used for sorting the current association words based on the latest evaluation information of the current association words to obtain a current sorting result;
and the feedback module is used for feeding back the current associated words to the user based on the current sorting result.
According to a third aspect of the invention, there is provided an electronic device comprising a memory and a processor,
the memory is used for storing codes;
the processor is adapted to execute the code in the memory for implementing the method according to the first aspect and its alternatives.
According to a fourth aspect of the present invention, there is provided a storage medium having a program stored thereon, wherein the program, when executed by a processor, implements the method of the first aspect and its alternatives.
The invention provides a processing method and device for user cockpit search association, electronic equipment and a storage medium, which can search association words in a general corpus without being limited to historical search records of users, effectively enrich the content of the association words, further match and inquire more association words for the users, and are beneficial to meeting various demand possibilities of the users.
On the basis, the relevance between the current association words and the current search words is used as one of the bases for ranking the current association words, so that the ranking result can be ensured to be pertinently and accurately adapted to the current search words of the user, the ranking result can accurately meet the search requirement embodied by the current search words, and the user experience is improved.
In addition, the invention also adjusts the sequencing based on different users and different scenes, so that the sequencing result can pertinently meet the search habits and preferences of different users and scenes, and further improve the user experience.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a flow diagram illustrating a method for processing user cabin search associations in accordance with an embodiment of the present invention;
FIG. 2 is a schematic diagram illustrating adjustment and evaluation information for determining a corpus of specials according to an embodiment of the present invention;
FIG. 3 is a diagram illustrating the determination of final adjusted assessment information in accordance with an embodiment of the present invention;
FIG. 4 is a schematic diagram of program modules of a processing means for user cabin search associations in accordance with an embodiment of the present invention;
fig. 5 is a schematic structural diagram of an electronic device in an embodiment of the invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The terms "first," "second," "third," "fourth," and the like in the description and in the claims, as well as in the drawings, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in other sequences than described or illustrated herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
The technical solution of the present invention will be described in detail below with specific examples. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments.
The processing method of the user cabin association according to the embodiment can be applied to an intelligent vehicle-mounted terminal or a server connected to the intelligent vehicle-mounted terminal.
The intelligent vehicle-mounted terminal can be a vehicle machine of the vehicle, can also be any other intelligent equipment connected to the vehicle machine, and can also be terminal equipment of a driver, such as a mobile phone, a tablet personal computer and the like.
Referring to fig. 1, the method for processing the user cabin association includes:
s11, acquiring the current search word of the current user;
the current search term can be understood as the search term currently input by the current user, which can be manually input or recognized by voice input, and the text content of the current search term is determined without departing from the scope of the embodiment of the invention;
s12, based on the current search word, querying the overall corpus to obtain a plurality of corresponding current association words and the initial evaluation information of each current association word,
the evaluation information characterizes the correlation between the current association word and the current search word; in some examples, the relevance may be based on similarity between the associated word and the text of the search word to show the relevance of the two; such as; the search word "haar" is input, which displays the corresponding association words "harvard", "harbin", etc.
The initial evaluation information may be information obtained by counting and evaluating the frequency and the number of co-occurrence of the preceding and following words in the overall corpus (for example, the initial evaluation information may be a quantitative specific score or rating information);
in one embodiment, the corpus of the overall corpus is derived from vehicle data, such as: the overall corpus is constructed based on the processed vehicle data;
the vehicle data includes at least one of: map data; real-time location data of the vehicle; user behavior data; searching for input text data; and the vehicle networking text is acquired based on the service platform.
Such as: the spatial location of the vehicle, the weather the user is currently located, etc.
After the vehicle data is obtained, it may also be subject to basic processing, including, for example:
text decryption: the method comprises the steps of decrypting cpsp, a mall, a poi/aoi, user behaviors and the like to obtain decrypted texts;
and (3) filtering meaningless linguistic data: such as special symbols, emoticons, pure digital mixed English, pure web addresses, system messages, and most of repeated content removal;
risk filtering, comprising the following:
information desensitization: sensitive information including order numbers, telephones and the like is filtered;
negative filtration: the filtering includes negative information such as risk text, advertisement text, anger \35881, curse text, yellow gambling poison political text, and the like.
Pseudo high-frequency corpus filtering: high frequency due to repeated input, such as in a bar.
Performing corpus compression on the acquired vehicle data subjected to basic processing, and extracting entity words and phrases of the corpus, such as 'filter, maintenance, when to test driving' and the like; and aggregating the compressed linguistic data based on the same key words, and taking the highest sentence frequency linguistic data for each aggregation group, wherein if the 'when', the associative words 'what time to ship, what time to ship' or aggregated into the highest frequency 'what time to ship' are input.
After the processed vehicle data is obtained, word segmentation is performed on each corpus one by one, and a text co-occurrence algorithm is used for marking a relevance score (which can be directly or indirectly used as initial evaluation information) on each pair of words after segmentation, wherein the front words are used as search words, the rear words are used as association words, and then the words are all used as the corpus in the overall corpus. The corpus is a text with sentences as basic units. If a 'Harvard/Furward' dog, a 'Harvard/big dog' and a 'Harvard/dog' are respectively constructed for the 'Harvard big dog', and then the front and back word correlation scores are calculated. This constructs an overall corpus. As can be seen, in the overall corpus, the corresponding relations between the corresponding association words and search words and the relevance scores (i.e., the initial evaluation information) are recorded.
S13: adjusting at least part of evaluation information of the current association words based on the user information of the current user and the current scene;
wherein the scenario characterizes at least one of: time information, location information, weather information; the time information can represent one or more time points and one or more time intervals, the position information can represent one or more position points and one or more position ranges, the weather information can represent weather states such as sunny days, cloudy days and rainy days, and can represent any weather-related information such as wind power, rainfall, humidity and temperature.
S14: sequencing the current association words based on the latest evaluation information of the current association words to obtain a current sequencing result;
the latest evaluation information is used as the evaluation information of sequencing basis; in one example, the evaluation information adjusted in step S13 may be the latest evaluation information;
in another example, the evaluation information after the adjustment in step S13 and the adjustment again based on the adjustment record may be the latest evaluation information.
And S15, feeding back the current associative words to the user based on the current sorting result.
In the scheme, the method is not limited to historical search records of the user, the content of the association words is effectively enriched, and then more association words can be matched and inquired for the user, so that the method is favorable for meeting the various requirement possibilities of the user.
On the basis, the relevance between the current association words and the current search words is used as one of the bases for sorting the current association words, so that the sorting result can be ensured to be pertinently and accurately adapted to the current search words of the user, the sorting result can accurately meet the search requirement embodied by the current search words, and the user experience is improved;
in addition, the invention also adjusts the sequencing based on different scenes of different users, so that the sequencing result can pertinently meet the search habits and preferences of different users and scenes, and further improve the user experience.
Referring to fig. 2, step S13 may include:
s131: determining a current special corpus in a plurality of special corpuses based on the user information of the current user and the current scene;
the plurality of special corpora comprise a plurality of user corpora and a plurality of scene corpora;
the corpus in each user corpus is constructed in a manner of being adapted to a corresponding user, and further, as long as different user corpora are constructed for different users, the scope of the embodiment of the present invention is not deviated.
In some examples, the corpora in the user corpus may be part or all of the corpora in the search word previously input by the user and/or the selected associated word (or expanded based on the corpora).
Furthermore, the corpus in the user corpus not only accords with the personal recent preference of the user, but also is derived from the overall corpus, so that the corpus has corresponding initial evaluation information, and a sufficient basis can be provided for sequencing.
The corpus in each scene corpus is constructed in a manner of being adapted to a corresponding scene, and further, as long as different scene corpora are constructed for different scenes, the scope of the embodiment of the invention is not deviated.
In some examples, the corpus in the scene corpus is based on the real-time position of the vehicle and/or map data of the vehicle at the real-time position and the corpus including operations performed at the real-time position; the operation performed at the real-time location may be to find a gas station, mcdonald's work site, etc. at the real-time location.
S132: and inquiring the current associated words in the current corpus to obtain an inquiry result, and adjusting at least part of evaluation information of the current associated words based on the inquiry result.
The query result may include: whether a current associative word is found in each current corpus (which current corpus or corpora the current associative word appears in can also be understood as); furthermore, in the above scheme, the adjustment of the evaluation information can reflect whether the current special corpus contains the current associative word, and thus the query result can reflect the search habit of the same user and the same scene; therefore, the adjustment based on the method can effectively meet the search habit of the same user in the same scene, and further improve the user experience.
For further example, in order to more accurately reflect the preference of the user, the query result may further include: and click frequency evaluation information, wherein the click frequency evaluation information represents the number of clicks of a certain associative word by a user in a period of time.
That is, the adjusted evaluation information is the initial evaluation information + frequency evaluation information, which is a weighted value of the adjusted evaluation information in the corresponding corpus.
For a further example, referring to fig. 3, step S132 may include:
s1321: if any one target associative word in the plurality of current associative words belongs to at least one current corpus, then: determining corresponding click frequency evaluation information;
the corresponding click frequency evaluation information represents the click frequency of the target associative word in the current special corpus to which the target word belongs;
the frequency is defined as the number of times per unit time, and the click frequency evaluation information is arbitrary information describing the frequency, for example: if the user clicks the corpus a ten times in one day or one week, the frequency corresponding to the corpus a is 10 times/day or 10 times/week.
S1322: and adjusting the evaluation information of the target association words based on the corresponding click frequency evaluation information.
The adjusted evaluation information is added with the click frequency evaluation information of the user after the click frequency of different words on the initial evaluation information, so that the preference of the user on certain words is better expressed, and the search requirements of the user on different contents are accurately met.
Wherein, each speciality corpus is configured with a corresponding weighted value, and the weighted values of at least part of the speciality corpora are different;
in one example, the processing method of the user cabin association further includes:
and superposing the product of the click frequency evaluation information and the corresponding weighted value on the basis of the evaluation information of the target associative word. Such as:
a, B, C three association words associated with the search word D are found in the overall corpus, where the initial evaluation information of a and D is a, the initial evaluation information of B and D is B, and the initial evaluation information of C and D is C, when the user inputs the current search word D, the association word A, B, C associated with D appears, and a is found in the user corpus, C is found in the scene corpus, the weighting value of the user corpus is m, the weighting value of the scene corpus is n, the weighting value of the overall corpus is 1, the frequency evaluation information of a is x, the frequency evaluation information of B is y, and the frequency evaluation information of C is z, and then the corresponding adjusted evaluation information is obtained as follows:
a corresponds to the adjusted evaluation information a + m x;
b corresponds to the adjusted evaluation information B + y;
c corresponds to adjusted evaluation information C + n z;
and when the user inputs the current search word D, outputting related associated word sequencing results which are sequentially arranged from high to low according to the adjusted evaluation information.
Adjusting the evaluation information of one or more current associated words according to the adjustment records of the sorting result of the associated words based on the current user, sorting the corresponding associated words according to the adjusted evaluation information, and obtaining the final associated word sequence, namely the output sequence of the user.
In this step, frequency-limited query is also performed to avoid the engineering process of repeated mass query by malicious or system problems.
Because the data are processed in S12 and S13, the data are processed three times based on the initial data in the total corpus and the data matched with the user corpus and the scene corpus and the data of the clicking frequency of the corpus, single and random results searched by the user in the cabin can be solved better, and various searching requirements of the user in the cabin are met better.
Fig. 4 is a schematic diagram of program modules of a processing device for user cabin search association according to an embodiment of the present invention.
Referring to fig. 4, the user cabin search association processing apparatus 200 includes:
an obtaining module 201, configured to obtain a current search term of a current user;
a query module 202, configured to query the corpus based on the current search term to obtain a plurality of corresponding current association terms and initial evaluation information of each current association term, where the evaluation information represents a correlation between the current association term and the current search term;
an adjusting module 203, configured to adjust evaluation information of at least part of current association words based on the user information of the current user and a current scene; wherein the scenario characterizes at least one of: time information, location information, weather information;
the sorting module 204 is configured to sort the current associated words based on the latest evaluation information of the current associated words to obtain a current sorting result;
a feedback module 205, configured to feed back the plurality of current associated words to the user based on the current sorting result.
Optionally, the adjusting module 203 is specifically configured to:
determining a current special corpus in a plurality of special corpuses based on the user information of the current user and the current scene;
the plurality of special corpora comprise a plurality of user corpora and a plurality of scene corpora; the corpus in each user corpus is constructed by being adaptive to one user, and each scene corpus is constructed by being adaptive to one corresponding scene;
and inquiring the current associated words in the current corpus to obtain an inquiry result, and adjusting at least part of evaluation information of the current associated words based on the inquiry result.
Optionally, the adjusting module 203 is specifically configured to:
if any one target associative word in the plurality of current associative words belongs to at least one current corpus, then: determining corresponding click frequency evaluation information; the corresponding click frequency evaluation information represents the frequency of the first association word in the current special corpus to which the target association word belongs;
and adjusting the evaluation information of the target association words based on the corresponding click frequency evaluation information.
Optionally, each specialized corpus is configured with a corresponding weighted value, and weighted values of at least some specialized corpora are different;
the adjusting module 203 is specifically configured to:
and superposing the product of the click frequency evaluation information and the corresponding weighted value on the basis of the evaluation information of the target associative word.
Optionally, the user cabin search association processing apparatus 200 further includes:
and the secondary adjusting module is used for adjusting the evaluation information of one or more current association words based on the adjusting record of the current user on the sequencing result of the association words.
In summary, the user cabin search association processing apparatus provided in this embodiment can perform three times of processing on data based on the initial data in the total corpus, the data adapted to the user corpus and the scene corpus, and the data of the click frequency of a corpus, and finally can better solve the single and random result of the user search in the cabin, and better satisfy various search requirements of the user in the cabin.
Fig. 5 is a schematic structural diagram of an electronic device in an embodiment of the invention.
Referring to fig. 5, an electronic device 30 is provided, which includes:
a processor 31; and
a memory 32 for storing executable commands of the processor;
wherein the processor 31 is configured to perform the above-mentioned method via execution of the executable instructions.
The processor 31 is capable of communicating with the memory 32 via a bus 33.
The present embodiments also provide a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the above-mentioned method.
Those of ordinary skill in the art will understand that: all or a portion of the steps of implementing the above-described method embodiments may be performed by hardware associated with program instructions. The program may be stored in a computer-readable storage medium. When executed, the program performs steps comprising the method embodiments described above; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. A method for processing user cabin search associations, comprising:
acquiring a current search word of a current user;
inquiring a total corpus based on the current search word to obtain a plurality of corresponding current association words and initial evaluation information of each current association word, wherein the evaluation information represents the correlation between the current association words and the current search word;
adjusting at least part of evaluation information of the current association words based on the user information of the current user and the current scene; wherein the scenario characterizes at least one of: time information, location information, weather information;
sequencing the current association words based on the latest evaluation information of the current association words to obtain a current sequencing result;
and feeding back the current association words to the user based on the current sorting result.
2. The treatment method according to claim 1,
the adjusting the evaluation information of at least part of the current association words based on the user information of the current user and the current scene comprises:
determining a current special corpus in a plurality of special corpuses based on the user information of the current user and the current scene;
the plurality of special corpora comprise a plurality of user corpora and a plurality of scene corpora; the corpus in each user corpus is adapted to be constructed for one user, and each scene corpus is adapted to be constructed for one corresponding scene;
and inquiring the current associated words in the current corpus to obtain an inquiry result, and adjusting at least part of evaluation information of the current associated words based on the inquiry result.
3. The processing method according to claim 2,
the querying, in the current corpus, the current associated word to obtain a query result, and adjusting evaluation information of at least part of the current associated word based on the query result, including:
if any one target associative word in the plurality of current associative words belongs to at least one current corpus, then: determining corresponding click frequency evaluation information; the corresponding click frequency evaluation information represents the click frequency of the target association words in the current special corpus to which the target association words belong;
and adjusting the evaluation information of the target association words based on the corresponding click frequency evaluation information.
4. The process of claim 3, wherein each specialized corpus is configured with corresponding weighting values, and weighting values of at least some specialized corpora are different;
the adjusting the evaluation information of the target associative word based on the corresponding click frequency evaluation information includes:
and superposing the product of the click frequency evaluation information and the weighted value of the corresponding corpus on the basis of the evaluation information of the target associative word.
5. The process of claim 2, wherein the corpus of specials is derived from a corpus of corpora, the corpus of corpora being derived from vehicle data.
6. The process of claim 5, wherein the vehicle data comprises at least one of:
map data;
real-time location data of the vehicle;
user behavior data;
searching the input text;
and the vehicle networking text is acquired based on the service platform.
7. The processing method according to any one of claims 1 to 6,
the method for ranking the current association words based on the latest evaluation information of the current association words further comprises the following steps before a current ranking result is obtained:
and adjusting the evaluation information of one or more current association words based on the adjustment record of the current user on the sequencing result of the association words.
8. A processing apparatus for user cabin search associations, comprising:
the acquisition module is used for acquiring the current search terms of the current user;
the query module is used for querying the overall corpus based on the current search word to obtain a plurality of corresponding current association words and initial evaluation information of each current association word, and the evaluation information represents the correlation between the current association words and the current search word;
the adjusting module is used for adjusting at least part of evaluation information of the current association words based on the user information of the current user and the current scene; wherein the scenario characterizes at least one of: time information, location information, weather information;
the sorting module is used for sorting the current association words based on the latest evaluation information of the current association words to obtain a current sorting result;
and the feedback module is used for feeding back the current associated words to the user based on the current sorting result.
9. An electronic device comprising a memory, a processor and a program stored on the memory and executable on the processor, wherein the steps of the method of any of claims 1-7 are implemented when the program is executed by the processor.
10. A storage medium having a program stored thereon, wherein the program, when executed by a processor, performs the steps of the method of any one of claims 1 to 7.
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| CN116662634A (en) * | 2023-08-02 | 2023-08-29 | 中国标准化研究院 | Knowledge graph-based path analysis reasoning research system and method |
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| CN116662634A (en) * | 2023-08-02 | 2023-08-29 | 中国标准化研究院 | Knowledge graph-based path analysis reasoning research system and method |
| CN116662634B (en) * | 2023-08-02 | 2023-10-31 | 中国标准化研究院 | Knowledge graph-based path analysis reasoning research system and method |
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