CN104268265B - A kind of information search method and device - Google Patents
A kind of information search method and device Download PDFInfo
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- CN104268265B CN104268265B CN201410534745.6A CN201410534745A CN104268265B CN 104268265 B CN104268265 B CN 104268265B CN 201410534745 A CN201410534745 A CN 201410534745A CN 104268265 B CN104268265 B CN 104268265B
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/953—Querying, e.g. by the use of web search engines
- G06F16/9535—Search customisation based on user profiles and personalisation
Abstract
The application provides a kind of information search method and device, by receiving the information search request for carrying search term, specifying text set information and hunting zone information, generate all articles as corresponding to specifying text set information and expand search term the search word list formed, and the article comprising at least one element in search word list is obtained in all articles in the information of hunting zone as information search result.The application expands the search word list formed to search term by using all articles corresponding to specified text set information and realizes information seeking processes, prior art is avoided in information seeking processes are carried out, the search term of search user's input is carried out to expand generation search word list because being based only on historical search record and clicking on record, caused by the problem of deviation between the obtained information search result of information search and the true personalization preferences of user is larger is carried out using the search word list.
Description
Technical field
The application is related to information search technique field, more particularly to a kind of information search method and device.
Background technology
With the improvement of people ' s living standards and scientific and technological level progress, acquisition demand more and more higher of the people to information,
And people obtain information approach be not limited to books, and more turn on provide information faster, using more easily
In internet.
It is traditional when carrying out information search by internet, realize information search work(often through full-text search engine
Can, its process is mainly：Search term of the record to search user input is recorded and clicked on using the historical search for searching for user
Carry out expanding generation search word list, and then information search is carried out according to the search word list and obtains information search result.
Traditional information search method is because being based only on historical search record and clicking on record to search user's input
Search term is expanded so that the matching degree of the search word list and user individual preference of generation is not high enough, so as to cause profit
With the search word list carry out deviation between information search result that information search obtains and the true personalization preferences of user compared with
The problem of big.
The content of the invention
In view of this, the application provides a kind of information search method and device, to avoid prior art from searching entering row information
During rope, because being based only on, historical search records and click record carries out expansion generation to the search term of search user's input and searched
Rope word list, caused by using the search word list carry out the obtained information search result of information search and the true individual character of user
The problem of deviation between change preference is larger.
To achieve these goals, technical scheme provided in an embodiment of the present invention is as follows：
A kind of information search method, including：
Receive information searching request, wherein carrying search term, specifying text set information and hunting zone information；
Generate all articles as corresponding to the specified text set information and the search word list formed is expanded to search term；
Obtained in all articles in the hunting zone information comprising at least one member in the search word list
The article of element is as information search result.
Preferably, the generation all articles as corresponding to the specified text set information are searched to what search term expansion formed
Rope word list, including：
Obtain all articles for including the search term corresponding to the specified text set information；
The each label carried for the every article got, calculates first of the label in its affiliated article respectively
Weighted value；
Using each label of bookmark name identical as a kind of label, every class is calculated according to each first weighted value respectively
Label is directed to the second weighted value of the search term；
Generation includes all kinds of labels and respectively the search word list of the second weighted value corresponding with every class label.
Preferably, when each label that every article for getting carries, the label is calculated respectively in text belonging to it
During the first weighted value in chapter, calculated using equation below：
S(i)(Wk)=【Ssource(Wk)-Pos(Wk)*λ(Ssource(Wk))】*idf(Wk)*Sattributes(Wk), wherein, institute
State S(i)(Wk) for first weighted values of k-th of label W in this article in i-th article, the Ssource(Wk) it is label Wk's
Source parameter, the Pos (Wk) it is label WkLocation parameter, the λ (Ssource(Wk)) it is because of label WkPosition it is introduced
Punishment parameter, the idf (Wk) it is the label WkSignificance level in internet, the Sattributes(Wk) it is described
Label WkPart of speech parameter.
Preferably, it is described using each label of bookmark name identical as a kind of label, according to each first weighted value
The second weighted value that the search term is directed to per class label is calculated respectively, including：
Using each label of bookmark name identical as a kind of label, for except bookmark name and the search term identical it is each
Every class label outside label classification belonging to individual label, each label for belonging to such label is obtained, and for each label point
The first power of the first weighted value and bookmark name in the affiliated article of the label and search term identical label of the label is not calculated
The product of weight values, and using each product and as such label be directed to the search term the second weighted value；
Obtain the weighted value of maximum second in each second weighted value；
Corresponding with the affiliated label classification of each label of search term identical the second weighted value of bookmark name is set to be
More than the arbitrary value in maximum second weighted value.
Preferably, in addition to：Each second weighted value for the threshold value for meeting to pre-set is obtained, then the generation includes each
The class label and search word list of the second weighted value corresponding with every class label is respectively：Generation includes meeting the threshold pre-set
Each second weighted value of value and each other search word list of tag class corresponding with second weighted value.
Preferably, in addition to：The 3rd weighted value of each piece article in described information search result is calculated, and according to the 3rd power
The order of weight values from high to low shows article corresponding with the 3rd weighted value.
A kind of information retrieval device, including：
Receiving unit, for receive information searching request, wherein carrying search term, specifying text set information and hunting zone
Information；
Generation unit, what is formed is expanded to search term for generating all articles as corresponding to the specified text set information
Search for word list；
As a result determining unit, arranged for being obtained in all articles in the hunting zone information comprising the search term
The article of at least one element in table is as information search result.
Preferably, the generation unit includes：
Acquiring unit, for obtaining all articles for including the search term corresponding to the specified text set information；
First weighted value computing unit, each label carried for every article for getting, calculating respectively should
First weighted value of the label in its affiliated article；
Second weighted value computing unit, for using each label of bookmark name identical as a kind of label, according to each institute
State the first weighted value and calculate the second weighted value that every class label is directed to the search term respectively；
Subelement is generated, includes all kinds of labels and the respectively search of the second weighted value corresponding with every class label for generating
Word list.
Preferably, the second weighted value computing unit includes：
First computing unit, for using each label of bookmark name identical as a kind of label, for except bookmark name with
Every class label outside label classification belonging to each label of search term identical, obtain each mark for belonging to such label
Label, and the first weighted value of the label and bookmark name and search term in the affiliated article of the label are calculated respectively for each label
The product of first weighted value of identical label, and using each product and as such label for the search term
Second weighted value；
Maximum second weighted value acquiring unit, for obtaining the weighted value of maximum second in each second weighted value；
Second computing unit, for setting bookmark name and the affiliated label classification pair of each label of search term identical
The second weighted value answered is more than the arbitrary value in maximum second weighted value.
Preferably, in addition to：
Display unit, for calculating the 3rd weighted value of each piece article in described information search result, and according to the 3rd power
The order of weight values from high to low shows article corresponding with the 3rd weighted value.
The application provides a kind of information search method and device, by receive carry search term, specify text set information and
The information search request of hunting zone information, generate all articles as corresponding to specifying text set information and search term expansion is formed
Search word list, and in all articles in the information of hunting zone obtain comprising search word list at least one element
Article as information search result.The application expands search term by using all articles corresponding to specified text set information
The search word list formed realizes information seeking processes, avoids prior art in information seeking processes are carried out, because of only base
Record is recorded and clicks in historical search the search term of search user's input is carried out to expand generation search word list, caused by
Deviation between the information search result and the true personalization preferences of user that are obtained using search word list progress information search
The problem of larger.
Brief description of the drawings
In order to illustrate more clearly about the embodiment of the present invention or technical scheme of the prior art, below will be to embodiment or existing
There is the required accompanying drawing used in technology description to be briefly described, it should be apparent that, drawings in the following description are only this
The embodiment of invention, for those of ordinary skill in the art, on the premise of not paying creative work, can also basis
The accompanying drawing of offer obtains other accompanying drawings.
Fig. 1 is a kind of information search method flow chart that the embodiment of the present application one provides；
Fig. 2 be a kind of generation that the embodiment of the present application two provides as corresponding to specifying text set information all articles to search
Word expands the method flow diagram of the search word list formed；
Fig. 3 is a kind of information search method flow chart that the embodiment of the present application three provides；
Fig. 4 is a kind of structural representation for information retrieval device that the embodiment of the present application four provides.
Embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clear, complete
Site preparation describes, it is clear that described embodiment is only part of the embodiment of the present invention, rather than whole embodiments.It is based on
Embodiment in the present invention, those of ordinary skill in the art are obtained every other under the premise of creative work is not made
Embodiment, belong to the scope of protection of the invention.
Embodiment one：
Fig. 1 is a kind of information search method flow chart that the embodiment of the present application one provides.
As shown in figure 1, this method includes：
S101, receive information searching request, wherein carrying search term, specifying text set information and hunting zone information.
In the embodiment of the present application, it is preferred that receive search user input carrying search term, specify text set information and
The information search request of hunting zone information, wherein, text set information is specified to search for the information search knot to be known of user
The related text set information of fruit, such as when user A input information search requests, it is desirable to obtained search result and text set B phases
Guan Shi, this specifies the information that text set information is text set B.
S102, generation all articles as corresponding to specifying text set information expand the search word list formed to search term.
In the embodiment of the present application, it is preferred that after information search request is received, need to obtain and the information search first
All articles corresponding to the specified text set information carried in request, and then search term is expanded using the article got
Generation search word list.
In the embodiment of the present application, it is preferred that this specifies the corresponding at least article of text set information.
Obtained in S103, all articles in the information of hunting zone comprising at least one element in search word list
Article is as information search result.
In the embodiment of the present application, it is preferred that after word list is searched in generation, need to obtain first and taken in information search request
All articles in the hunting zone information of band, and then obtain and included in search word list at least in all articles got
The article of one element is as search result.
The application provides a kind of information search method, carries search term by receiving, specifies text set information and searches for model
The information search request of information is enclosed, all articles as corresponding to specifying text set information is generated and the search formed is expanded to search term
Word list, and the article for including at least one element in search word list is obtained in all articles in the information of hunting zone
As information search result.The application expands what is formed by using all articles corresponding to specified text set information to search term
Search word list realizes information seeking processes, prior art is avoided in information seeking processes are carried out, because being based only on history
Search record and click on record to search user input search term carry out expand generation search word list, caused by using should
Deviation between information search result and the true personalization preferences of user that search word list progress information search obtains is larger
Problem.
Embodiment two：
Fig. 2 be a kind of generation that the embodiment of the present application two provides as corresponding to specifying text set information all articles to search
Word expands the method flow diagram of the search word list formed.
S201, obtain all articles specified and include search term corresponding to text set information.
In the embodiment of the present application, it is preferred that generation as specify text set information corresponding to all articles to search term
During expanding the search word list formed, need to obtain owning comprising search term corresponding with specified text set information first
Article.Specifically the process is：All articles corresponding with specified text set information are obtained, and then are obtained each in all articles
A piece includes the article of search term.
S202, each label carried for the every article got, calculate the label in its affiliated article respectively
The first weighted value.
In the embodiment of the present application, it is preferred that at least one label is carried in every article, the source of the label can
Be article generation when it is user-defined (such as：It is that its one label of setting is " sweet apple " when preserving certain article),
Can also be by word segmentation processing obtain (such as：User-defined label " sweet apple " is passed through into word segmentation processing, generation
Two labels " banana " and " apple "/when preserving article, using the more word of occurrence number in article as participle label).
In the embodiment of the present application, search term is included in the article got, it is preferred, therefore, that every got
Comprising title and search term title identical label in article.
In the embodiment of the present application, it is preferred that the formula for calculating first weighted value of the label in its affiliated article is：
S(i)(Wk)=【Ssource(Wk)-Pos(Wk)*λ(Ssource(Wk))】*idf(Wk)*Sattributes(Wk), wherein, S(i)
(Wk) it is k-th of label W in i-th articlekThe first weighted value in this article, Ssource(Wk) it is label WkSource ginseng
Number, Pos (Wk) it is label WkLocation parameter, λ (Ssource(Wk)) it is because of label WkThe introduced punishment parameter in position, idf
(Wk) it is label WkSignificance level in internet, Sattributes(Wk) it is label WkPart of speech parameter.
In the embodiment of the present application, it is preferred that Ssource(Wk) it is label WkSource parameter, wherein, the source of label refers to
It is customized label/participle label to show the label, and preferably, pre-sets the S when label is customized labelsource(Wk)
Value for participle label when 8~20 times.
In the embodiment of the present application, it is preferred that Pos (Wk) it is label WkLocation parameter, wherein, the position instruction of label
The position in each label of source identical in article of the label belonging to it, and preferably, text of the label belonging to it
Which position, the Pos (W of the label are arranged in each label of source identical in chapterk) value is several, such as：When carrying 5 in some article
Individual label, wherein 3 are participle label, this 3 participle labels are followed successively by " banana ", " apple ", " pear ", then, label " duck
Pos (the W of pears "k) value be 3.
In the embodiment of the present application, it is preferred that λ (Ssource(Wk)) it is because of label WkThe introduced punishment parameter in position,
Wherein, punishment parameter is different because the source of label is different, it is preferred that the λ (S pre-setsource(Wk)) value 0.08~
Between 0.11, and Ssource(Wk)-Pos(Wk)*λ(Ssource(Wk)) value be more than or equal to 0.5.
In the embodiment of the present application, it is preferred that idf (Wk) it is label WkSignificance level in internet, wherein, calculate
The process of the significance level of some label is prior art, refers to prior art, is not described in detail herein.
In the embodiment of the present application, it is preferred that Sattributes(Wk) it is label WkPart of speech parameter, wherein, it is preferred that mark
The part of speech of label be proper noun, noun, verb, adjective, adverbial word, and when part of speech be proper noun, noun, verb, adjective,
During adverbial word, S is followed successively byattributes(Wk) it is entered as 10,9,5,4,4.
S203, using each label of bookmark name identical as a kind of label, calculated respectively often according to each first weighted value
Class label is directed to the second weighted value of search term.
In the embodiment of the present application, it is preferred that using each label of bookmark name identical as a kind of label, according to each
One weighted value calculates every class label respectively：
1st, using each label of bookmark name identical as a kind of label, for except bookmark name and search term identical it is each
Every class label outside label classification belonging to label, each label for belonging to such label is obtained, and distinguished for each label
Calculate the first weight of the first weighted value and bookmark name in the affiliated article of the label and search term identical label of the label
The product of value, and using each product and as such label be directed to search term the second weighted value.
In the embodiment of the present application, it is preferred that using each label of bookmark name identical as a kind of label, and such label
(i.e.：Class label) title it is identical with the bookmark name of label in such label.
2nd, the weighted value of maximum second in each second weighted value is obtained.
3rd, it is big to set bookmark name the second weighted value corresponding with the affiliated label classification of each label of search term identical
Arbitrary value in maximum second weighted value.
S204, generation include all kinds of labels and respectively the search word list of the second weighted value corresponding with every class label.
Further, the one kind provided in the embodiment of the present application generates all articles pair as corresponding to specifying text set information
Search term expands in the method for the search word list formed, in addition to：Obtain each second power for the threshold value for meeting to pre-set
Weight values.
In the embodiment of the present application, it is preferred that after each second weighted value for the threshold value for meeting to pre-set is got,
Above-mentioned steps S204 is：Generation includes each second weighted value of threshold value that satisfaction pre-sets and corresponding with second weighted value
The other search word list of each tag class.
The embodiment of the present application provide a kind of generation all articles as corresponding to specifying text set information search term is expanded and
Into search word list method so that the more clear process that search listing is generated according to search term of those skilled in the art,
So that the information search method of the application offer is clearer, readily appreciates.
Embodiment three：
Fig. 3 is a kind of information search method flow chart that the embodiment of the present application three provides.
As shown in figure 3, this method includes：
S301, receive information searching request, wherein carrying search term, specifying text set information and hunting zone information.
S302, generation all articles as corresponding to specifying text set information expand the search word list formed to search term.
Obtained in S303, all articles in the information of hunting zone comprising at least one element in search word list
Article is as information search result.
In the embodiment of the present application, it is preferred that the step that step S301-S303 implementation procedure provides with above-described embodiment one
Rapid S101-S103 implementation procedure is identical, refers to above-mentioned steps S101-S103 description, is not described in detail herein.
S304, the 3rd weighted value for calculating each piece article in information search result, and according to the 3rd weighted value from high to low
Order show article corresponding with the 3rd weighted value.
In the embodiment of the present application, it is preferred that the mistake of its 3rd weighted value is calculated for every article in search result
Cheng Wei：Calculate respectively the first weighted value in this article of each label in this article and in full-text search engine
Four weighted values, calculate the first weighted value of each label and the product of the 4th weighted value, and by each product being calculated
With the 3rd weighted value as this article, shown according to order of the 3rd weighted value as height on earth corresponding with the 3rd weighted value
Article.
In the embodiment of the present application, it is preferred that the process for calculating weighted value of the label in full-text search engine is existing
Technology, prior art is referred to, is not described in detail herein.
The embodiment of the present application provides a kind of information search method, the information search method that this method provides in above-described embodiment
On the basis of further comprise calculate information search result in every article the 3rd weighted value, and according to the 3rd weighted value by
High order on earth is shown so that the search result that the information search method that the embodiment of the present application provides provides more meets
Search for the demand of user.
Example IV：
Fig. 4 is a kind of structural representation for information retrieval device that the embodiment of the present application four provides.
As shown in figure 4, the device includes：Receiving unit 1, generation unit 2 and the result determining unit 3 being sequentially connected, its
In：
Receiving unit 1, for receive information searching request, wherein carrying search term, specifying text set information and search model
Enclose information.
Generation unit 2, searched for generating all articles as corresponding to specifying text set information to what search term expansion formed
Rope word list.
In the embodiment of the present application, it is preferred that generation unit 2 includes acquiring unit, the first weighted value meter being sequentially connected
Unit, the second weighted value computing unit and generation subelement are calculated, wherein：
Acquiring unit, all articles of search term are included corresponding to specified text set information for obtaining；First weighted value
Computing unit, each label carried for every article for getting, calculates the label in its affiliated article respectively
The first weighted value；Second weighted value computing unit, for using each label of bookmark name identical as a kind of label, according to each
Individual first weighted value calculates the second weighted value that every class label is directed to search term respectively；Subelement is generated, is included respectively for generating
Class label and respectively the search word list of the second weighted value corresponding with every class label.
In the embodiment of the present application, it is preferred that the second weighted value computing unit includes：First be sequentially connected calculates single
Member, maximum second weighted value acquiring unit and the second computing unit, wherein：
First computing unit, for using each label of bookmark name identical as a kind of label, for except bookmark name with
Every class label outside label classification belonging to each label of search term identical, each label for belonging to such label is obtained, and
For each label calculate respectively the label the first weighted value and bookmark name in the affiliated article of the label it is identical with search term
Label the first weighted value product, and using each product and as such label be directed to search term the second weighted value；
Maximum second weighted value acquiring unit, for obtaining the weighted value of maximum second in each second weighted value；Second computing unit,
It is more than maximum for setting bookmark name the second weighted value corresponding with the affiliated label classification of each label of search term identical
Arbitrary value in second weighted value.
As a result determining unit 3, for being obtained in all articles in the information of hunting zone comprising in search word list
The article of at least one element is as information search result.
Further, in a kind of information retrieval device that the embodiment of the present application provides, in addition to：Display unit, it is used for
The 3rd weighted value of each piece article in information search result is calculated, and show according to the order of the 3rd weighted value from high to low and the
Article corresponding to three weighted values.
The application provides a kind of information retrieval device, the device by receive carry search term, specify text set information and
The information search request of hunting zone information, generate all articles as corresponding to specifying text set information and search term expansion is formed
Search word list, and in all articles in the information of hunting zone obtain comprising search word list at least one element
Article as information search result.The application expands search term by using all articles corresponding to specified text set information
The search word list formed realizes information seeking processes, avoids prior art in information seeking processes are carried out, because of only base
Record is recorded and clicks in historical search the search term of search user's input is carried out to expand generation search word list, caused by
Deviation between the information search result and the true personalization preferences of user that are obtained using search word list progress information search
The problem of larger.
Each embodiment is described by the way of progressive in this specification, what each embodiment stressed be and other
The difference of embodiment, between each embodiment identical similar portion mutually referring to.For device disclosed in embodiment
For, because it is corresponded to the method disclosed in Example, so description is fairly simple, related part is said referring to method part
It is bright.
It the above is only the preferred embodiment of the application, make skilled artisans appreciate that or realizing the application.It is right
A variety of modifications of these embodiments will be apparent to one skilled in the art, as defined herein general former
Reason can be realized in other embodiments in the case where not departing from spirit herein or scope.Therefore, the application will not
Be intended to be limited to the embodiments shown herein, and be to fit to it is consistent with principles disclosed herein and features of novelty most
Wide scope.
Claims (7)
- A kind of 1. information search method, it is characterised in that including：Receive information searching request, wherein carrying search term, specifying text set information and hunting zone information；Generate all articles as corresponding to the specified text set information and the search word list formed is expanded to search term；Obtained in all articles in the hunting zone information comprising at least one element in the search word list Article is as information search result；Wherein, the generation all articles as corresponding to the specified text set information expand search term the search term formed and arranged Table, including：Obtain all articles for including the search term corresponding to the specified text set information；For every got Each label that article carries, calculates first weighted value of the label in its affiliated article respectively；With bookmark name identical Each label is a kind of label, and every class label is calculated respectively for the second of the search term according to each first weighted value Weighted value；Generation includes all kinds of labels and respectively the search word list of the second weighted value corresponding with every class label；When each label that every article for getting carries, first power of the label in its affiliated article is calculated respectively During weight values, calculated using equation below：S(i)(Wk)=【Ssource(Wk)-Pos(Wk)*λ(Ssource(Wk))】*idf(Wk)*Sattributes(Wk), wherein, the S(i) (Wk) it is k-th of label W in i-th articlekThe first weighted value in this article, the Ssource(Wk) it is label WkSource Parameter, the Pos (Wk) it is label WkLocation parameter, the λ (Ssource(Wk)) it is because of label WkPosition introduced punish Penalty parameter, the idf (Wk) it is the label WkSignificance level in internet, the Sattributes(Wk) it is the label Wk Part of speech parameter.
- 2. according to the method for claim 1, it is characterised in that described using each label of bookmark name identical as a category Label, second weighted value of every class label for the search term is calculated according to each first weighted value respectively, including：Using each label of bookmark name identical as a kind of label, for except bookmark name and each mark of search term identical Every class label outside label classification belonging to label, obtains each label for belonging to such label, and count respectively for each label Calculate the first weighted value of the first weighted value and bookmark name in the affiliated article of the label and search term identical label of the label Product, and using each product and as such label be directed to the search term the second weighted value；Obtain the weighted value of maximum second in each second weighted value；Set corresponding with the affiliated label classification of each label of search term identical the second weighted value of bookmark name for more than Arbitrary value in maximum second weighted value.
- 3. according to the method for claim 2, it is characterised in that also include：Obtain each of the threshold value that satisfaction is pre-set Second weighted value, the then generation include all kinds of labels and respectively the search word list of the second weighted value corresponding with every class label For：Generation includes each second weighted value for the threshold value that satisfaction is pre-set and each tag class corresponding with second weighted value Other search word list.
- 4. according to the method for claim 1, it is characterised in that also include：Calculate each piece text in described information search result 3rd weighted value of chapter, and show article corresponding with the 3rd weighted value according to the order of the 3rd weighted value from high to low.
- A kind of 5. information retrieval device, it is characterised in that including：Receiving unit, for receive information searching request, wherein carrying search term, specifying text set information and hunting zone letter Breath；Generation unit, the search formed is expanded to search term for generating all articles as corresponding to the specified text set information Word list；As a result determining unit, for being obtained in all articles in the hunting zone information comprising in the search word list At least one element article as information search result；Wherein, the generation unit includes：Acquiring unit, searched for obtaining corresponding to the specified text set information comprising described All articles of rope word；First weighted value computing unit, each label carried for every article for getting, respectively Calculate first weighted value of the label in its affiliated article；Second weighted value computing unit, for bookmark name identical Each label is a kind of label, and every class label is calculated respectively for the second of the search term according to each first weighted value Weighted value；Subelement is generated, includes all kinds of labels and the respectively search of the second weighted value corresponding with every class label for generating Word list；When each label that every article for getting carries, first power of the label in its affiliated article is calculated respectively During weight values, calculated using equation below：S(i)(Wk)=【Ssource(Wk)-Pos(Wk)*λ(Ssource(Wk))】*idf(Wk)*Sattributes(Wk), wherein, the S(i) (Wk) it is k-th of label W in i-th articlekThe first weighted value in this article, the Ssource(Wk) it is label WkSource Parameter, the Pos (Wk) it is label WkLocation parameter, the λ (Ssource(Wk)) it is because of label WkPosition introduced punish Penalty parameter, the idf (Wk) it is the label WkSignificance level in internet, the Sattributes(Wk) it is the label Wk Part of speech parameter.
- 6. device according to claim 5, it is characterised in that the second weighted value computing unit includes：First computing unit, for using each label of bookmark name identical as a kind of label, for except bookmark name with it is described Every class label outside label classification belonging to each label of search term identical, each label for belonging to such label is obtained, and For each label calculate respectively the label the first weighted value and bookmark name in the affiliated article of the label it is identical with search term Label the first weighted value product, and using each product and as such label be directed to the search term second Weighted value；Maximum second weighted value acquiring unit, for obtaining the weighted value of maximum second in each second weighted value；Second computing unit, for setting bookmark name corresponding with the affiliated label classification of each label of search term identical Second weighted value is more than the arbitrary value in maximum second weighted value.
- 7. device according to claim 5, it is characterised in that also include：Display unit, for calculating the 3rd weighted value of each piece article in described information search result, and according to the 3rd weighted value Order from high to low shows article corresponding with the 3rd weighted value.
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| CN201410534745.6A CN104268265B (en) | 2014-10-11 | 2014-10-11 | A kind of information search method and device |
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| CN102110126A (en) * | 2009-12-29 | 2011-06-29 | 潘晓梅 | Information retrieval method and device |
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| CN103106282A (en) * | 2013-02-27 | 2013-05-15 | 王义东 | Method for search and display of webpage |
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| CN103984740A (en) * | 2014-05-23 | 2014-08-13 | 合一网络技术(北京)有限公司 | Combination label based search page display method and system |
| CN104035927A (en) * | 2013-03-05 | 2014-09-10 | 百度在线网络技术（北京）有限公司 | User behavior-based search method and system |
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| TW200729003A (en) * | 2006-01-25 | 2007-08-01 | Bridgewell Inc | Conceptual keyword function generation method, adjustment method, system, search engine, and calculation method for keyword related value |
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| CN102110126A (en) * | 2009-12-29 | 2011-06-29 | 潘晓梅 | Information retrieval method and device |
| CN102402619A (en) * | 2011-12-23 | 2012-04-04 | 广东威创视讯科技股份有限公司 | Search method and device |
| CN103810198A (en) * | 2012-11-09 | 2014-05-21 | 阿里巴巴集团控股有限公司 | Method and device for searching commodity information |
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| CN104035927A (en) * | 2013-03-05 | 2014-09-10 | 百度在线网络技术（北京）有限公司 | User behavior-based search method and system |
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