CN111597294A - Information searching method and device - Google Patents
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- CN111597294A CN111597294A CN201910124629.XA CN201910124629A CN111597294A CN 111597294 A CN111597294 A CN 111597294A CN 201910124629 A CN201910124629 A CN 201910124629A CN 111597294 A CN111597294 A CN 111597294A
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Abstract
The disclosure provides an information searching method and device, and relates to the field of computers. The original search word is converted into another search word which is mutually related to the original search word through conversion of the search word, and the search is carried out based on the converted search word, so that the problem of low recall rate of the search result caused by the search based on the original search word is solved.
Description
Technical Field
The present disclosure relates to the field of computers, and in particular, to an information search method and apparatus.
Background
Information search based on search terms is a common information search technology, and information containing the search terms can be searched by using the technology, so whether the search terms are proper or not affects the recall rate of search results.
For example, "stool" is also called "stool young" in dialects in some areas, and "stool" is a more standard expression, so that "stool" is used in description of many information, and if a user inputs "stool young" to perform a search, the searched information is less, resulting in a lower recall rate of search results.
Disclosure of Invention
According to the method and the device, the original search word is converted into another search word which is mutually related to the original search word through conversion of the search word, and searching is carried out based on the converted search word, so that the problem that the recall rate of the search result is low due to the fact that searching is carried out based on the original search word is solved.
Some embodiments of the present disclosure provide an information search method, including:
receiving a search request of a user;
converting a first search word requesting a search into a second search word correlated with the first search word;
and searching based on the converted second search word.
In some embodiments, it is determined whether the location area where the user requesting the search is located at an effective location where the first search term requesting the search is located, and the step of converting the search term is performed when the location area where the user requesting the search is located at the effective location where the first search term requesting the search is located.
In some embodiments, whether the first search word requesting for searching meets a preset effective condition is judged; and under the condition of meeting the preset effective condition, executing the conversion step of the search terms.
In some embodiments, the method further comprises a step of determining the search terms related to each other, including:
the method comprises the steps of obtaining search information of each user in at least one position area, wherein the search information comprises a search word and a first search object based on the search word, and the first search object is a search object which is subjected to preset user behaviors in the search objects obtained based on the search word;
for each location area: determining the correlation degree between the search word of the position area and each first search object based on the search word according to the search information of each user of the position area, wherein the correlation degree between the search word of the position area and each object in the object set forms a corresponding vector of the search word, the object set comprises each first search object based on the search word and other objects, and the correlation degree between the search word and the other objects is configured to be a preset value;
and determining the search words which are mutually related according to the similarity of different vectors of the same or different position areas.
In some embodiments, the relevance between the search term of the location area and any one of the first search objects based on the search term is based on: and determining at least one of a ratio information of the number of the any one first search object based on the search word to the number of all first search objects based on the search word, and a similarity between the search word and the description information of the any one first search object.
In some embodiments, the ratio information is:
a ratio of the number of the any one first search object based on the search term to the number of all first search objects based on the search term;
alternatively, the first and second electrodes may be,
a ratio of a first number to a second number, the first number being based on a sum of the number of the any one first search object of the search term and a first smoothing factor, the second number being based on a sum of the number of all first search objects of the search term and a second smoothing factor.
In some embodiments, the similarity between the search term and the description information of the arbitrary one of the first search objects is:
the ratio of the first number of words to the second number of words,
wherein the content of the first and second substances,
the first number of characters is the number of repeated characters possessed by the search word and the description information of the arbitrary one of the first search objects,
the second number of characters is the total number of characters remaining after the repeated characters are removed from the search word and the description information of the arbitrary one of the first search objects.
In some embodiments, each user of at least one location area:
the method comprises the steps of clustering users based on the geographic position information of the users, wherein the users in the same class are located in the same position area.
In some embodiments, search terms corresponding to different vectors with similarity higher than a preset condition in the same position area are determined as the search terms related to each other.
In some embodiments, search terms corresponding to different vectors with similarity higher than a preset condition in different position areas are determined as the search terms related to each other.
Some embodiments of the present disclosure provide an information search apparatus including:
a memory; and
a processor coupled to the memory, the processor configured to perform the information search method of any of the preceding embodiments based on instructions stored in the memory.
Some embodiments of the present disclosure propose a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the information search method of any of the foregoing embodiments.
Some embodiments of the present disclosure provide an information search apparatus including:
a receiving unit configured to receive a search request of a user;
a conversion unit configured to convert a first search word requesting a search into a second search word correlated with the first search word;
a search unit configured to perform a search based on the converted second search word.
Drawings
The drawings that will be used in the description of the embodiments or the related art will be briefly described below. The present disclosure will be more clearly understood from the following detailed description, which proceeds with reference to the accompanying drawings,
it is to be understood that the drawings in the following description are merely exemplary of the disclosure, and that other drawings may be derived from those drawings by one of ordinary skill in the art without undue inventive faculty.
Fig. 1 is a schematic flow chart diagram of some embodiments of the disclosed information search method.
Fig. 2 is a schematic flow chart of another embodiment of the information search method of the present disclosure.
Fig. 3 is a schematic flow chart of another embodiment of the information search method of the present disclosure.
FIG. 4 is a flow diagram illustrating some embodiments of the present disclosure for determining interrelated search terms.
Fig. 5 is a schematic diagram of some embodiments of the disclosed information search apparatus.
Fig. 6 is a schematic diagram of some embodiments of the disclosed information search apparatus.
FIG. 7 is a schematic diagram of some embodiments of the disclosed information handling system.
FIG. 8 is a schematic diagram of an exemplary optical storage device shown in the present disclosure.
Detailed Description
The technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the drawings in the embodiments of the present disclosure.
The descriptions of "first", "second", etc. in this disclosure are used only to distinguish different objects, and are not used to indicate the meaning of size, timing, etc.
Fig. 1 is a schematic flow chart diagram of some embodiments of the disclosed information search method. The method may be performed by an information search apparatus, for example.
As shown in fig. 1, the method of this embodiment includes:
step 110, receiving a search request of a user, where the request may carry a first search term requested to be searched by the user.
Step 120, converting the first search word requesting the search into a second search word correlated to the first search word.
Wherein search terms representing the same object but represented differently may be configured as search terms that are related to each other, or search terms representing similar objects may be configured as search terms that are related to each other, but are not limited to the illustrated examples. For example, "stool" and "litter" both represent "stools," which may be configured as interrelated search terms. Both "computer" in chinese and "computer" in english denote "computer", and the "computer" in chinese and "computer" in english may be configured as search words associated with each other. The "stool" and the "chair" representing similar objects may be configured as search words associated with each other.
And step 130, searching based on the converted second search word.
For example, a search is conducted using the second search term to search for information containing the second search term. Or, the second search word and the first search word are used for searching for the information containing the second search word and the first search word.
The original search word is converted into another search word which is mutually related to the original search word through conversion of the search word, and the search is carried out based on the converted search word, so that the problem of low recall rate of the search result caused by the search based on the original search word is solved.
For example, the user uses the dialect "stool" to search, the searched information is less, the "stool" is converted into the standard language "stool", and the search is performed according to the "stool", so that more information can be searched, and the recall rate of the search result is improved.
Fig. 2 is a schematic flow chart of another embodiment of the information search method of the present disclosure. The method may be performed by an information search apparatus, for example.
As shown in fig. 2, the method of this embodiment includes:
step 210, receiving a search request of a user, where the request may carry a first search term requested to be searched by the user.
Step 220, determining whether the location area where the user requesting the search is located at the effective location where the first search term requesting the search is located, if the determination result is "yes", performing step 230 of converting the search term, and if the determination result is "no", for example, performing step 250.
The effective position where the first search term is located may be, for example, a position area where the first search term is located.
For example, taking the search words "bench" and "stool" associated with each other as an example, the effective position of the dialect "bench" of the guangdong may be set to the guangdong, for example. When the user requesting the search searches for "bench young" in the Guangdong, the "bench young" is converted into a "bench" for searching. When the user searches for the 'stool boy' in other areas, the 'stool boy' may have other meanings in other areas, the user can search according to the 'stool boy' without converting the search words at the moment, and therefore the effectiveness of conversion of the search words is improved.
For another example, the effective position of the standard language "stool" may be set to null, so that the search based on the standard language "stool" is not converted into the search based on the dialect "stool", thereby improving the effectiveness of the search term conversion.
In step 230, the first search term of the requested search is converted into a second search term that is related to the first search term.
And step 240, searching is carried out based on the converted second search word, and the step 130 is specifically referred to.
A search is performed based on the original first search term to search for information containing the first search term, step 250.
On the basis of the embodiment shown in fig. 1, in this embodiment, a step of determining an effective position of a search term is added, and when a condition of the effective position of the search term is satisfied, conversion and search of the search term are performed, so that the effectiveness of conversion of the search term is improved, and it is ensured that a search result based on the converted search term is improved relative to a search result based on an original search term.
Fig. 3 is a schematic flow chart of another embodiment of the information search method of the present disclosure. The method may be performed by an information search apparatus, for example.
As shown in fig. 3, the method of this embodiment includes:
step 310, receiving a search request of a user, where the request may carry a first search term requested to be searched by the user.
In step 320, it is determined whether the first search term requested to be searched satisfies a preset validation condition, and in case that the determination result is yes, the search term conversion step 330 is performed, and in case that the determination result is no, for example, step 350 may be performed.
And setting the effective condition of each search word according to the conversion direction of the search words which are mutually related.
For example, if the conversion direction of the first search word and the second search word associated with each other is that the first search word should be converted into the second search word, the effective condition is that the first search word is used as the search word for the user to request for searching. Through the setting of the effective condition, if the user requests to search for the first search word, the step 330-340 is executed, the search is carried out based on the converted second search word, and if the user requests to search for the second search word, the step 350 is executed, the search is still carried out based on the second search word, the second search word is not converted into the first search word, and the search is also not carried out based on the first search word. Thus, the effectiveness of search term conversion is improved, and some undesirable search term conversion events are prevented from occurring.
For example, taking the search terms "young stool" and "stool" associated with each other as an example, the conversion direction should be, for example, that "young stool" is converted into "stool", and the validation condition may be set as "young stool" as the search term for the user to request for search. By setting the validation condition, if the search for the "stool young" is requested, the search is performed based on the "stool" converted from the "stool young", and if the search for the "stool" is requested, the conversion of the search word is not performed, and the search is still performed according to the "stool". Thus, the effectiveness of search term conversion is improved, and some undesirable search term conversion events are prevented from occurring.
In step 330, the first search term of the request search is converted into a second search term correlated to the first search term.
Step 340, searching is performed based on the converted second search term, specifically referring to step 130.
Step 350, a search is performed based on the original first search term to search for information containing the first search term.
On the basis of the embodiment shown in fig. 1, the present embodiment adds a step of determining a search term validation condition, and executes conversion and search of a search term when the search term validation condition is satisfied, so as to improve the validity of conversion of the search term, ensure that a search result based on the converted search term is improved relative to a search result based on the original search term, and prevent some undesirable events of conversion of the search term.
The present disclosure also provides a method for automatically determining the search terms related to each other by using big data through a data mining technology. The correlated search terms can be determined more comprehensively and more accurately than the correlated search terms determined based on human experience.
FIG. 4 is a flow diagram illustrating some embodiments of the present disclosure for determining interrelated search terms. The method may be performed by an information search apparatus, for example.
As shown in fig. 4, the method of this embodiment includes:
and step 410, clustering the users based on the geographical position information of each user, wherein each user in the same class is located in the same position area.
Wherein the geographical location information of the respective users can be determined by analyzing the occurrence places of the behaviors of the respective users. For example, the occurrence places of behaviors such as browsing, purchasing and commenting of the user are counted, and the occurrence place with the most occurrence is determined as the geographical position of the user.
Step 420, obtaining search information of each user in at least one location area, where the search information includes a search term and a first search object based on the search term, and the first search object is a search object in which a preset user behavior occurs among search objects obtained based on the search term.
The search information has a location attribute, and based on the search information generated by the user in a certain location area, the search information and the location attribute value of the search word in the search information are the location area, so that the search word in the certain location area is described later.
The preset user behavior is, for example, a click behavior or a purchase behavior, but is not limited to the examples given. For example, a search object purchased by or clicked by a user among search objects obtained based on search word search is determined as a first search object.
Step 430, for each location area: according to the search information of each user in the position area, determining the correlation between the search word in the position area and each first search object based on the search word, wherein the correlation between the search word in the position area and each object in the object set constitutes a corresponding vector of the search word, the object set comprises each first search object based on the search word and other objects, and the correlation between the search word and other objects is configured to be a preset value, for example, 0.
Wherein, the correlation degree between the search word of the position area and any one first search object based on the search word is according to: and determining at least one of a ratio information of the number of any one of the first search objects based on the search word to the number of all of the first search objects based on the search word, and a similarity between the search word and the description information of any one of the first search objects. The formula is expressed as:
wherein the content of the first and second substances,
a search word q representing the location area and any one of the first search objects O based on the search wordiP represents the ratio information of the number of any one first search object based on the search term and the number of all first search objects based on the search term,
represents the search word q and any one of the first search objects OiDescription information D ofiThe similarity between a and b represents the weight, a + b is 1, and the value range of a and b is [0, 1%]. In some embodiments, setting a>b is, for example, 0.8 for a and 0.2 for b. Degree of correlation
When determined only from the scale information P, a is 1 and b is 0. Degree of correlation
According to similarity only
When determined, a is 0 and b is 1.
In some embodiments, the scale information P is: the ratio of the number of any one first search object based on the search term to the number of all first search objects based on the search term. The formula is expressed as:
wherein the content of the first and second substances,
representing any one of the first search objects O based on the search term qiThe number of the (c) component(s),
representing the number of all first search objects based on the search term q.
For example, there are users 1-5 in the same location area, user 1 and user 4 input the search word q1, and purchase search object O from many search objects1User 2 also enters search term q1 and purchases search object O from many search objects2User 3 and user 5 also enter search term q1 and purchase search object O from many search objects3Then O is1、O2、O3Are all the first search objects based on the search word q1, the first search object O based on the search word q11Number of (2)
To 2, a first search object O based on the search term q12Number of (2)
1, based on the search term q13Number of (2)
Is 2. In calculating the search term q1 of the location area and the first search object O based on the search term1Degree of correlation between
In time, correspond to
In calculating the search term q1 of the location area and the first search object O based on the search term2Degree of correlation between
In time, correspond to
In some embodiments, the scale information P is: a ratio of a first number to a second number, the first number being based on a sum of a number of any one of the first search objects of the search term and the first smoothing factor, the second number being based on a sum of a number of all of the first search objects of the search term and the second smoothing factor.
Wherein, alpha represents a first smoothing factor, beta represents a second smoothing factor, and the meanings of other symbols refer to the above. In some embodiments, α < β. For example, α is 20 and β is 100. By setting the smoothing factor, the value range of P is smoother.
Wherein the search word q is associated with any one of the first search objects OiDescription information D ofiSimilarity between them
Comprises the following steps: a ratio of the first number of words to the second number of words, wherein: the first character number is the number of repeated characters of the search word and the description information of any one first search object, and the second character number is the total number of characters left after the repeated characters are removed from the search word and the description information of any one first search object.
For example, assuming that the search word is "potato", the description information of a certain first search object based on "potato" is "about 1 kg of fresh vegetables of potato of the netherlands", the number of repeated characters included in the search word and the description information of the first search object thereof is 2, the total number of characters left after the repeated characters are removed is 12, the number of the first characters is 2, and the number of the second characters is 12.
In some embodiments, all purchased objects within a location area over a period of time make up the set of objects for that location area.
Assuming that there are 100 objects in the object set, two of the objects are the first search object based on the search word q1, the relevance of the search word q1 to the two first search objects is 0.9 and 0.1, respectively, and the relevance of the search word q1 to the other objects is 0, and assuming that the two first search objects are the first object and the third object of the 100 objects, the corresponding vector of the search word q1 is [0.9,0,0.1,0,0, …,0], and 0.1 is then 0, and the dimension of the vector is 100 dimensions.
Step 440, determining the search terms related to each other according to the similarity of different vectors of the same or different position areas.
And determining the search words corresponding to the different vectors with the similarity higher than the preset condition in the same position area as the correlated search words.
And determining the search words corresponding to the different vectors with the similarity higher than the preset condition in the different position areas as the correlated search words.
The calculation formula of the similarity of different vectors is as follows:
wherein cos (X, Y) represents the similarity of vector X and vector Y, X represents the vector corresponding to a certain search term, Y represents the vector corresponding to another search term, X represents the similarity of vector X and vector Y, andirepresenting the i-th element, Y, in the vector XiRepresenting the ith element in vector Y, the total number of elements in vector X is d, the total number of elements in vector Y is d, and | represents the modulus of the vector.
For example, if the similarity between the vector corresponding to "potato" and the vector corresponding to "potato" is relatively high, the "potato" and the "potato" can be determined as related search words. Optionally, a step of manual review may also be performed, and after the review is passed, the search term corresponding to the vector with the higher similarity is determined as the related search term. The manual examination finds that the dialect of the Guizhou "potato" refers to a potato, so that some users of the Guizhou search for the "potato" and actually purchase the commodity of the "potato", and other users (which may or may not be the users of the Guizhou) search for the "potato" and actually purchase the commodity of the "potato", so that the similarity between the vector corresponding to the "potato" and the vector corresponding to the "potato" is higher based on the user behaviors, and the search words related to the "potato" and the "potato" are finally determined through a big data mining technology.
And searching information by using the method of the embodiment shown in the figures 1-3 based on the mined related search words.
Fig. 5 is a schematic diagram of some embodiments of the disclosed information search apparatus.
As shown in fig. 5, the apparatus of this embodiment includes:
a memory 510; and
a processor 520 coupled to the memory, the processor configured to perform the information search method of any of the foregoing embodiments based on instructions stored in the memory.
Memory 510 may include, for example, system memory, fixed non-volatile storage media, and the like. The system memory stores, for example, an operating system, an application program, a Boot Loader (Boot Loader), and other programs.
Fig. 6 is a schematic diagram of some embodiments of the disclosed information search apparatus.
As shown in fig. 6, the apparatus of this embodiment includes:
a receiving unit 610 configured to receive a search request of a user;
a converting unit 620 configured to convert a first search word requesting a search into a second search word correlated with the first search word;
a searching unit 630 configured to perform a search based on the converted second search term.
In some embodiments, the apparatus of this embodiment further comprises: the first determining unit 640 is configured to determine whether the location area where the user requesting the search is located at an effective location where the first search term requesting the search is located, and if the location area where the user requesting the search is located at the effective location where the first search term requesting the search is located, then perform the step of converting the search terms in the converting unit 620.
In some embodiments, the apparatus of this embodiment further comprises: a second judging unit 650 configured to judge whether the first search word requested to be searched satisfies a preset validation condition; in case that a preset validation condition is satisfied, the conversion step of the search term in the conversion unit 620 is performed again.
In some embodiments, the apparatus of this embodiment further comprises: the determining unit 660 is configured to determine the search terms that are associated with each other, and specifically includes: the method comprises the steps of obtaining search information of each user in at least one position area, wherein the search information comprises a search word and a first search object based on the search word, and the first search object is a search object which is subjected to preset user behaviors in the search objects obtained based on the search word; for each location area: determining the correlation degree between the search word of the position area and each first search object based on the search word according to the search information of each user of the position area, wherein the correlation degree between the search word of the position area and each object in the object set forms a corresponding vector of the search word, the object set comprises each first search object based on the search word and other objects, and the correlation degree between the search word and the other objects is configured to be a preset value; and determining the search words which are mutually related according to the similarity of different vectors of the same or different position areas.
In some embodiments, the relevance between the search term of the location area and any one of the first search objects based on the search term is based on: and determining at least one of a ratio information of the number of the any one first search object based on the search word to the number of all first search objects based on the search word, and a similarity between the search word and the description information of the any one first search object.
In some embodiments, the ratio information is: a ratio of the number of the any one first search object based on the search term to the number of all first search objects based on the search term; or a ratio of a first number to a second number, the first number being based on a sum of the number of the any one first search object of the search term and a first smoothing factor, the second number being based on a sum of the number of all first search objects of the search term and a second smoothing factor.
In some embodiments, the similarity between the search term and the description information of the arbitrary one of the first search objects is:
the ratio of the first number of words to the second number of words,
wherein the content of the first and second substances,
the first number of characters is the number of repeated characters possessed by the search word and the description information of the arbitrary one of the first search objects,
the second number of characters is the total number of characters remaining after the repeated characters are removed from the search word and the description information of the arbitrary one of the first search objects.
In some embodiments, each user of at least one location area: the method comprises the steps of clustering users based on the geographic position information of the users, wherein the users in the same class are located in the same position area.
In some embodiments, search terms corresponding to different vectors with similarity higher than a preset condition in the same position area are determined as the search terms related to each other.
In some embodiments, search terms corresponding to different vectors with similarity higher than a preset condition in different position areas are determined as the search terms related to each other.
FIG. 7 is a schematic diagram of some embodiments of the disclosed information handling system.
As shown in fig. 7, the system of this embodiment includes: a client 710 and an information search device 720. Wherein:
the client 710 is used for providing an input interface of a search request for the user and displaying the search result returned by the information search device 720.
The information searching device 720 is configured to execute the information searching method in any of the foregoing embodiments based on a search request input by a user through the client 710, and return a search result to the client 710.
In some embodiments, the information searching apparatus 720 may be, for example, the information searching apparatus in the embodiment corresponding to fig. 5 or fig. 6. In some embodiments, the information search device 720 may be, for example, a server capable of performing information searches.
As will be appreciated by one skilled in the art, embodiments of the present disclosure may be provided as a method, system, or computer program product. Accordingly, the present disclosure may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present disclosure may take the form of a computer program product embodied on one or more computer-usable non-transitory storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein. Fig. 8 schematically shows an optical storage 810.
The above description is only exemplary of the present disclosure and is not intended to limit the present disclosure, so that any modification, equivalent replacement, or improvement made within the spirit and principle of the present disclosure should be included in the scope of the present disclosure.
Claims (12)
1. An information search method, comprising:
receiving a search request of a user;
converting a first search word requesting a search into a second search word correlated with the first search word;
and searching based on the converted second search word.
2. The method of claim 1, further comprising:
judging whether the position area of the user requesting the search is positioned at the effective position of the first search word requesting the search,
and under the condition that the position area of the user requesting the search is positioned at the effective position of the first search word requesting the search, executing the conversion step of the search word.
3. The method of claim 1, further comprising:
judging whether the first search word requested to be searched meets a preset effective condition or not;
and under the condition of meeting the preset effective condition, executing the conversion step of the search terms.
4. The method of claim 1, further comprising: the determination step of the correlated search words comprises the following steps:
the method comprises the steps of obtaining search information of each user in at least one position area, wherein the search information comprises a search word and a first search object based on the search word, and the first search object is a search object which is subjected to preset user behaviors in the search objects obtained based on the search word;
for each location area: determining the correlation degree between the search word of the position area and each first search object based on the search word according to the search information of each user of the position area, wherein the correlation degree between the search word of the position area and each object in the object set forms a corresponding vector of the search word, the object set comprises each first search object based on the search word and other objects, and the correlation degree between the search word and the other objects is configured to be a preset value;
and determining the search words which are mutually related according to the similarity of different vectors of the same or different position areas.
5. The method of claim 4,
the degree of correlation between the search term of the location area and any one of the first search objects based on the search term is according to: and determining at least one of a ratio information of the number of the any one first search object based on the search word to the number of all first search objects based on the search word, and a similarity between the search word and the description information of the any one first search object.
6. The method of claim 4, wherein the scale information is:
a ratio of the number of the any one first search object based on the search term to the number of all first search objects based on the search term;
alternatively, the first and second electrodes may be,
a ratio of a first number to a second number, the first number being based on a sum of the number of the any one first search object of the search term and a first smoothing factor, the second number being based on a sum of the number of all first search objects of the search term and a second smoothing factor.
7. The method of claim 4, wherein the similarity between the search term and the description information of the arbitrary one of the first search objects is:
the ratio of the first number of words to the second number of words,
wherein the content of the first and second substances,
the first number of characters is the number of repeated characters possessed by the search word and the description information of the arbitrary one of the first search objects,
the second number of characters is the total number of characters remaining after the repeated characters are removed from the search word and the description information of the arbitrary one of the first search objects.
8. The method of claim 4, wherein each user of at least one location area:
the method comprises the steps of clustering users based on the geographic position information of the users, wherein the users in the same class are located in the same position area.
9. The method of claim 4,
determining search words corresponding to different vectors with the similarity higher than a preset condition in the same position area as related search words;
alternatively, the first and second electrodes may be,
and determining the search words corresponding to the different vectors with the similarity higher than the preset condition in the different position areas as the correlated search words.
10. An information search apparatus, comprising:
a memory; and
a processor coupled to the memory, the processor configured to perform the information search method of any of claims 1-9 based on instructions stored in the memory.
11. A computer-readable storage medium on which a computer program is stored which, when executed by a processor, implements the information search method of any one of claims 1 to 9.
12. An information search apparatus, comprising:
a receiving unit configured to receive a search request of a user;
a conversion unit configured to convert a first search word requesting a search into a second search word correlated with the first search word;
a search unit configured to perform a search based on the converted second search word.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114547064A (en) * | 2021-12-31 | 2022-05-27 | 广州盖盟达工业品有限公司 | Product searching method, system, computer equipment and readable storage medium |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20060061604A (en) * | 2004-12-02 | 2006-06-08 | 주식회사 팬택 | Method and apparatus for providing conversion service of short message in mobile communication device |
| KR20110094562A (en) * | 2010-02-17 | 2011-08-24 | 주식회사 티앤엘아이앤티 | Efficient internet search method using related keywords diagram |
| KR20130026040A (en) * | 2011-09-05 | 2013-03-13 | 주식회사 다음커뮤니케이션 | System and method for providing search service |
| KR20130046297A (en) * | 2011-10-27 | 2013-05-07 | 주식회사 다음커뮤니케이션 | Device and method for providing search services |
| CN103942712A (en) * | 2014-05-09 | 2014-07-23 | 北京联时空网络通信设备有限公司 | Product similarity based e-commerce recommendation system and method thereof |
| CN104102633A (en) * | 2013-04-01 | 2014-10-15 | 百度在线网络技术（北京）有限公司 | Method and method for digging non-recalled type error correction word of searching engine |
| CN105700701A (en) * | 2012-03-21 | 2016-06-22 | 上海触乐信息科技有限公司 | System and method for carrying out input information expansion on the basis of input candidate box on electronic equipment |
-
2019
- 2019-02-20 CN CN201910124629.XA patent/CN111597294A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20060061604A (en) * | 2004-12-02 | 2006-06-08 | 주식회사 팬택 | Method and apparatus for providing conversion service of short message in mobile communication device |
| KR20110094562A (en) * | 2010-02-17 | 2011-08-24 | 주식회사 티앤엘아이앤티 | Efficient internet search method using related keywords diagram |
| KR20130026040A (en) * | 2011-09-05 | 2013-03-13 | 주식회사 다음커뮤니케이션 | System and method for providing search service |
| KR20130046297A (en) * | 2011-10-27 | 2013-05-07 | 주식회사 다음커뮤니케이션 | Device and method for providing search services |
| CN105700701A (en) * | 2012-03-21 | 2016-06-22 | 上海触乐信息科技有限公司 | System and method for carrying out input information expansion on the basis of input candidate box on electronic equipment |
| CN104102633A (en) * | 2013-04-01 | 2014-10-15 | 百度在线网络技术（北京）有限公司 | Method and method for digging non-recalled type error correction word of searching engine |
| CN103942712A (en) * | 2014-05-09 | 2014-07-23 | 北京联时空网络通信设备有限公司 | Product similarity based e-commerce recommendation system and method thereof |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114547064A (en) * | 2021-12-31 | 2022-05-27 | 广州盖盟达工业品有限公司 | Product searching method, system, computer equipment and readable storage medium |
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