CN109271518A - Method and apparatus for carrying out classification display to micro-blog information - Google Patents
Method and apparatus for carrying out classification display to micro-blog information Download PDFInfo
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Abstract
The invention discloses a kind of methods and apparatus for carrying out classification display to micro-blog information.The method for carrying out classification display to micro-blog information includes: to extract the centre word of micro-blog information；By calculating the degree of correlation of the centre word and predefined classification, to obtain the degree of correlation of the micro-blog information Yu the predefined classification；If the micro-blog information and the degree of correlation of the predefined classification are higher than the first threshold values, the micro-blog information is categorized into the predefined classification；And the micro-blog information that display is classified.Therefore, the present invention can carry out automatic clustering to the massive micro-blog information that microblogging publisher is issued, it allows users to be read according to classification only for certain a kind of micro-blog information interested to oneself, to provide the new user experience for reading massive micro-blog information.
Description
It is on April 28th, 2012 that the application, which is application No. is the 201210132513.9, applying date, entitled " is used for
The divisional application of the application for a patent for invention of the method and apparatus that classification display is carried out to micro-blog information ".
Technical field
The present invention relates to field of computer technology, more particularly it relates to a kind of for dividing micro-blog information
The method and apparatus that class is shown.
Background technique
The abbreviation of microblogging, i.e. micro-blog (MicroBlog) is a kind of to share brief real time information by concern mechanism
Broadcast type social network-i i-platform, it can carry out information sharing, propagation and acquisition based on customer relationship.In microblog
On, user can set up personal community by micro blog server, network and various clients, with the text of 140 words or so
And/or image releases news, and realizes the instant sharing of the information.
Microblog technology is just rapidly developed once release.By taking Sina weibo website as an example, the interior survey since in August, 2009
To in April, 2011, only 20 months time, the registration user of Sina weibo just has arrived at nearly 1.5 hundred million people, in Sina weibo
Average more than 50,000,000 micro-blog informations of publication daily of user.
However, along with the rapid growth that microblogging service uses, browsed brought by it, to massive micro-blog information
The problem of Shi Wufa automatic clustering, is also more prominent.Specifically, during using existing microblogging application program, user
It is all according to different account numbers, different microblogging type (such as commenting on) come the microblogging of the microblogging publisher of interest to the user
Information is filtered and sorts, and is will lead in this way when there are many micro-blog information of microblogging publisher, user does not know since what
It is browsed.
For example, a kind of situation through being commonly encountered is when user newly pays close attention to some microblogging publisher but microblogging publisher
When the microblogging issued has hundreds and thousands of, which understands in microblogging publisher is primarily upon without method at all
The type of appearance.
For another example as microblogging is using more and more common, user is sometimes it may be desirable that recall the account or of oneself
The account number of the other users of concern, but current microblogging application program is other than checking one by one, be not provided with it is any from
It is dynamic to sort out the method summarized, so that the user can not quickly find certain micro-blog information that oneself needs to look back.
This has resulted in user when browsing the micro-blog information of some microblogging publisher, needs to browse one by one manually, and
Whether the focus for artificially summarizing microblogging publisher is identical as oneself, to consume plenty of time and the energy of user.
Summary of the invention
In order to solve the above-mentioned technical problem, according to an aspect of the invention, there is provided it is a kind of for micro-blog information into
The method of row classification display, which is characterized in that the described method includes: extracting the centre word of micro-blog information；By calculating in described
The degree of correlation of heart word and predefined classification, to obtain the degree of correlation of the micro-blog information Yu the predefined classification；If
The micro-blog information and the degree of correlation of the predefined classification are higher than the first threshold values, then are categorized into the micro-blog information described
In predefined classification；And the micro-blog information that display is classified.
In addition, according to another aspect of the present invention, a kind of equipment for carrying out classification display to micro-blog information is provided,
It is characterized in that, the equipment includes: centre word extraction unit, for extracting the centre word of micro-blog information；The degree of correlation obtains single
Member, for the degree of correlation by calculating centre word the extraction unit extracted centre word and predefined classification, to obtain
The degree of correlation of the micro-blog information and the predefined classification；Taxon, if being used for the degree of correlation obtaining unit institute
The degree of correlation of the micro-blog information and the predefined classification that obtain is higher than the first threshold values, then is categorized into the micro-blog information
In the predefined classification；And display processing unit, the micro-blog information classified for showing the taxon.
In order to solve the above-mentioned technical problem, according to an aspect of the invention, there is provided a kind of classification display of micro-blog information
System, comprising: engine server and microblogging client, the engine server are in network-side, and for providing microblogging service
Micro blog server connection, the micro-blog information that microblogging publisher issues in time range can be downloaded from micro blog server,
And classified automatically to micro-blog information；Microblogging client is in user terminal and connect with the engine server, microblogging client
End includes: input information receiving unit, and automatic sorted micro-blog information is carried out on engine server for receiving；At display
Unit is managed, is shown to user.
In addition, according to another aspect of the present invention, providing a kind of engine server of micro-blog information classification display, packet
It includes: centre word extraction unit, degree of correlation obtaining unit, taxon and micro-blog information acquiring unit.Micro-blog information acquiring unit
During downloading micro-blog information, in addition to obtain the microblogging publisher itself in the time range issued it is all
Except micro-blog information, also obtains the micro-blog information that other microbloggings publisher issues the microblogging publisher itself and made
Return information.
In addition, according to another aspect of the invention, providing a kind of method of micro-blog information classification display, comprising: extract
Micro-blog information；Classified by calculating the degree of correlation of the micro-blog information and predefined classification to micro-blog information；According to institute
Micro-blog information number and the richness in predefined classification are stated, determines microblogging publisher for the concern of the predefined classification
Temperature.
Compared with prior art, it can be seen that, using according to the present invention for carrying out classification display to micro-blog information
Method and apparatus, can carry out Controlling UEP to micro-blog information, and by with the highly relevant micro-blog information of predefined classification
It is categorized into the predefined classification, to finally show sorted micro-blog information to user.Therefore, the present invention can be to microblogging
The massive micro-blog information that publisher is issued carries out automatic clustering, allows users to feel emerging only for oneself according to classification
A kind of micro-blog information of certain of interest is read, to provide the new user experience for reading massive micro-blog information.
Other features and advantages of the present invention will be illustrated in the following description, also, partly becomes from specification
It obtains it is clear that understand through the implementation of the invention.The objectives and other advantages of the invention can be by specification, right
Specifically noted structure is achieved and obtained in claim and attached drawing.
Detailed description of the invention
Attached drawing is used to provide further understanding of the present invention, and constitutes part of specification, with reality of the invention
It applies example to be used to explain the present invention together, not be construed as limiting the invention.In the accompanying drawings:
Fig. 1 illustrates the methods according to the present invention for carrying out classification display to micro-blog information.
Fig. 2 illustrates the equipment according to the present invention for carrying out classification display to micro-blog information.
Fig. 3 illustrates the method according to an embodiment of the present invention for carrying out classification display to micro-blog information.
Fig. 4 illustrates according to an embodiment of the present invention for carrying out the categorizing system and microblogging of classification display to micro-blog information
Server.
Fig. 5 illustrates the flow chart of off-line data training stage according to an embodiment of the present invention.
Fig. 6 A to 6C illustrates the degree of correlation for the centre word and predefined classification being calculated according to embodiments of the present invention
Example.
Fig. 7 illustrates the preview display interface according to an embodiment of the present invention shown in microblogging client.
Fig. 8 illustrates the classification display interface according to an embodiment of the present invention shown in microblogging client.
Specific embodiment
It will be described in detail with reference to the accompanying drawings each embodiment according to the present invention.Here it is to be noted that it in the accompanying drawings,
It assigns identical appended drawing reference to component part substantially with same or like structure and function, and will omit about it
Repeated description.
Hereinafter, the side of the display according to the present invention that is used to carry out micro-blog information to classify will be described with reference to Fig. 1 and 2
Method and equipment.
Fig. 1 illustrates the methods according to the present invention for carrying out classification display to micro-blog information.This method comprises:
In step s 110, the centre word of micro-blog information is extracted；
In the step s 120, by calculating the degree of correlation of the centre word and predefined classification, to obtain the microblogging
The degree of correlation of information and the predefined classification；
In step s 130, if the micro-blog information and the degree of correlation of the predefined classification are higher than the first threshold values,
Then the micro-blog information is categorized into the predefined classification；And
In step S140, classified micro-blog information is shown.
Fig. 2 illustrates according to the present invention for carrying out the equipment 200 of classification display to micro-blog information.The equipment 200 packet
It includes:
Centre word extraction unit 210, for extracting the centre word of micro-blog information；
Degree of correlation obtaining unit 220, for by the calculating extracted centre word of the centre word extraction unit 210 and in advance
The degree of correlation of the classification of definition, to obtain the degree of correlation of the micro-blog information Yu the predefined classification；
Taxon 230, if for the degree of correlation obtaining unit 220 micro-blog information obtained with it is described pre-
The degree of correlation of defining classification is higher than the first threshold values, then the micro-blog information is categorized into the predefined classification；And
Display processing unit 240, the micro-blog information classified for showing the taxon 230.
It can be seen that using the method and apparatus according to the present invention for carrying out classification display to micro-blog information, it can be with
Controlling UEP is carried out to micro-blog information, and the micro-blog information highly relevant with predefined classification is categorized into this predefined point
In class, to finally show sorted micro-blog information to user.Therefore, the present invention can be to the sea that microblogging publisher is issued
It measures micro-blog information and carries out automatic clustering, allow users to be believed according to classification only for certain a kind of microblogging interested to oneself
Breath is read, to provide the new user experience for reading massive micro-blog information.
Hereinafter, it will describe according to an embodiment of the present invention to be used to classify to micro-blog information with reference to Fig. 3 and Fig. 4
The method and apparatus of display.It in an embodiment of the present invention, will include the categorizing system work of engine server and microblogging client
Example for the equipment for carrying out classification display to micro-blog information is illustrated.
It should be noted that although here by the method and apparatus application that will be used to carry out micro-blog information classification display
Illustrate the present invention in categorizing system, still, it will be appreciated to those of skill in the art that the invention is not limited thereto.But also
The present invention can be applied in stand-alone device.For example, each component units of the categorizing system can be realized in a certain list
In machine equipment, which is, for example, personal computer, notebook computer, tablet computer, multimedia player or individual
Digital assistants etc..
Fig. 3 illustrates the method according to an embodiment of the present invention for carrying out classification display to micro-blog information, and Fig. 4 is illustrated
It is according to an embodiment of the present invention for carrying out the categorizing system and micro blog server of classification display to micro-blog information.
The illustrated method according to an embodiment of the present invention for carrying out classification display to micro-blog information of Fig. 3 can be applied
In the illustrated categorizing system 400 of Fig. 4.As illustrated in figure 4, the categorizing system for being used to carry out micro-blog information classification display
400 include: engine server 410 and microblogging client 450.
The engine server 410 is in network-side (cloud), connects with the micro blog server 300 for providing microblogging service
It connects, the micro-blog information that any microblogging publisher issues within the scope of any time can be downloaded from micro blog server 300, and
Classified automatically to micro-blog information.The microblogging client 450 is in user terminal (local side) and the engine server 410 connects
It connects, and carries out automatic sorted micro-blog information on engine server 410 for receiving, and show to user.
Obviously, in place of the advantage of automatic sort operation that micro-blog information is realized on the engine server 410 in cloud
It is: a large amount of arithmetic operations in local end user equipment (microblogging client 450) can be reduced, to reduces for the user
The requirement of equipment operational capability, so that simple, inexpensive user equipment can be used to realize massive micro-blog information in user
Classified browse.
The engine server 410 include: centre word extraction unit 210, degree of correlation obtaining unit 220, taxon 230,
With micro-blog information acquiring unit 250.
The microblogging client 450 includes: input information receiving unit 260 and display processing unit 240.
As illustrated in fig. 3, the method according to an embodiment of the present invention for carrying out classification display to micro-blog information includes:
In step S300, all micro-blog informations that microblogging publisher is issued in a time range are obtained.
Specifically, when user wishes to browse a certain microblogging publisher by way of automatic clustering in a certain period of time
When the micro-blog information of publication, which activates microblogging client 450 (for example, mobile phone).At this point, the microblogging client 450
In display processing unit 240 in the display screen (not shown) being located on micro-blog family end 450 (for example, mobile phone is aobvious
Show device) on prompt the user with input be desired with classified browse microblogging publisher account and time range.Microblogging client
End 450 receives the upper of user's input by input information receiving unit 260 (for example, touch screen or keyboard of mobile phone)
Information is stated, and then, by wired or wirelessly transfer them to engine server 410.
In engine server 410, micro-blog information acquiring unit 250 is according to the microblogging received from microblogging client 450
Corresponding micro-blog information is downloaded to engine server from micro blog server 300 by the account and time range of publisher
410, to carry out subsequent Processing automatically by sort.
For example, when user wishes all micro- in 1 day to 2012 January in 2012 this period on March 31, to Yao Chen
When rich progress classified browse, then micro-blog information acquiring unit 250 can be obtained according to the microblogging account of Yao Chen and above-mentioned period
All microbloggings that she is issued are taken, and these microbloggings are stored in engine server 410.
Preferably, in order to more accurately be classified automatically to the micro-blog information downloaded, micro-blog information acquiring unit 250
During downloading, in addition to obtaining all micro-blog informations that the microblogging publisher itself is issued in the time range
Except, also obtain the reply letter that the micro-blog information that other microbloggings publisher issues the microblogging publisher itself is made
Breath, to realize short essay for the short text feature (number of words of a general micro-blog information is no more than 140 words) of micro-blog information
The long text of this micro-blog information, to enrich the content that every micro-blog information is included.
Optionally, in addition, if engine server 410 finds the user with the interactive process of micro blog server 300
It is not concerned with above-mentioned microblogging publisher, then engine server 410 can pass through the display processing unit in microblogging client 450
240 prompt the user with the concern added for microblogging publisher, and after user has added concern, the engine server
410 continue the down operation.
In step s310, the centre word of micro-blog information is extracted.
Specifically, in engine server 410, centre word extraction unit 210 receives micro-blog information acquiring unit 250 from micro-
The user obtained in rich server 300 wishes whole micro-blog informations of classified browse, and using in off-line data training rank
Two-dimensional grammar (Gram) model generated in section to carry out real time data parsing to these microblog passages.
In the following, being described with reference to Figure 5 the off-line data training stage according to an embodiment of the present invention.
Fig. 5 illustrates the flow chart of off-line data training stage according to an embodiment of the present invention.Using engine server
Before the stage of 410 progress real time data parsings, it is necessary to carry out engine server 410 first against the characteristics of microblogging text
Offline data training.
Specifically, and commenting property content ratio more there are short sentence is compared with plain text due to microblogging text and is greater than narration
Property content the characteristics of, so to engine server 410 carry out off-line training when, can using condition random field (CRF) carry out,
The CRF model is obtained using the dedicated training of microblogging.
As illustrated in fig. 5, which includes:
In step S510, application programming interfaces (API) (for example, from Sina weibo) are disclosed from network and randomly select one
A little true micro-blog informations, and by their bulk transfers into engine server 410, the engine server 410 for example can be with
It is Sony's natural language engine server.
In step S520, engine server 410 is automatically parsed using a dedicated corpus of initial microblogging, for example,
The initial dedicated corpus of microblogging can be by being artificially generated, and wherein at least include: the word segmented, the word
The classification that part of speech (for example, noun, verb, pronoun, preposition etc.) and the word may belong to.
Specifically, this automatically parses each for operating and comprising the steps of: in the multiple micro-blog informations that will be randomly selected
Micro-blog information cutting is at least one natural sentences；Each natural sentences after cutting are subdivided into multiple words；After subdivision
Each word carries out part-of-speech tagging；On the basis of the part-of-speech tagging, syntax parsing is carried out to the natural sentences after cutting；And root
Candidate centre word is found according to the result and microblogging core word dictionary of syntax parsing.
In step S530, judge whether the deviation of the dedicated corpus of the microblogging is less than scheduled threshold value.
For example, in the engine server 410 by the initial dedicated corpus of microblogging to the micro-blog information randomly selected
After being automatically parsed, the operator of engine server 410 judges what obtained centre word and operator were artificially judged
Whether the centre word in the micro-blog information is consistent.
If the deviation of the dedicated corpus of the microblogging is greater than scheduled threshold value, for example, if the engine server 410 passes through
Centre word obtained from the initial dedicated corpus of microblogging exists a large amount of inconsistent with the centre word that operator artificially judges
Place (for example, 50%), then operator carries out drift correction to the dedicated corpus of the microblogging according to the result artificially judged, simultaneously
To in the dedicated corpus of the microblogging emerging word add the classification information that the word may belong to, thus after obtaining update
The dedicated corpus of microblogging.
Then, the initial dedicated corpus of microblogging is replaced using the updated dedicated corpus of microblogging, and is returned
Step S510 is executed, to carry out further correction and more to the dedicated corpus of microblogging using other true micro-blog informations
Newly.Step S510 to S530 so is repeatedly carried out, until the deviation of the dedicated corpus of the microblogging is less than scheduled threshold value.
In step S540, engine server 410 carries out binary Gram's according to the dedicated corpus of the microblogging ultimately generated
Modeling.
For example, engine server 410 is established according to the participle and annotation results that are obtained by CRF model for solving in real time
The binary Gram model of microblog data is analysed, to improve the accuracy classified automatically.
It should be noted that although illustrating here by condition random field (CRF) according to an embodiment of the present invention offline
The data training stage, still, it will be appreciated to those of skill in the art that the invention is not limited thereto.But it can also use all
It is realized such as other random fields of Markov random field (MRF), gibbs random field (GRF) or Gaussian random field etc
State the off-line data training stage.
Referring back to the step S310 of Fig. 3, centre word extraction unit 210 in the off-line data training stage according to generating
Two-dimensional grammar (Gram) model, micro-blog information acquiring unit 250 is obtained from the micro blog server 300, user wish
Each of the specific user of classified browse in whole micro-blog informations (preferably, including return information) in special time period
Micro-blog information cutting is at least one natural sentences；Each natural sentences after cutting are subdivided into multiple words；After subdivision
Each word part of speech is labeled；According to the word and its part of speech, syntax tree is established to the natural sentences；And oneself is extracted at this
The word of dominance relation, the centre word as the natural sentences in the micro-blog information are in the syntax tree of right sentence.
For example, in the syntax tree of the natural sentences in dominance relation word can be subject-predicate phrase, dynamic guest's phrase and/or
Noun adverbial modifier's phrase.It is apparent that can also be extracted according to other rules (e.g., selecting subject, predicate or object etc.) to extract
The word of dominance relation is in the syntax tree of the natural sentences.
In the following, step S310 is described in detail by an example.
For example, five micro-blog informations that micro-blog information acquiring unit 250 is got in step S300, wherein first is micro-
The content of rich information be " today has eaten an authentic walking chicken in Mount Huang tourist hotel, be really it is too delicious, feel well！".
At this point, centre word extraction unit 210 is with reference to two-dimensional grammar (Gram) mould generated in the off-line data training stage
Type to carry out natural sentences cutting to first micro-blog information first.It is that " today exists the first natural sentences by the micro-blog information cutting
Eaten an authentic walking chicken in Mount Huang tourist hotel ", the second nature sentence " being really too delicious " and Third Nature sentence " refreshing " three
A natural sentences.
Next, continuing to explain by taking the first natural sentences as an example, centre word extraction unit 210 is come using context-free grammar
First natural sentences are subdivided into eight words " today ", " ", " Mount Huang tourist hotel ", " eating ", " ", " one ", " orthodox school
" and " walking chicken ".Then, centre word extraction unit 210 carries out part-of-speech tagging to above-mentioned eight words in the first natural sentences,
It is labeled as verb for example, " will eat ", " walking chicken " is labeled as noun etc..Then, centre word extraction unit 210 is according to above-mentioned
The word and its part of speech segmented establishes syntax tree to first natural sentences.By analyzing the syntax tree, Ke Yizhi
The V-O construction that word of the road in the syntax tree in dominance relation is made of verb and noun, that is to say, that can obtain
Mastery phrase to the first natural sentences is as the phrase " eating " of V-O construction and " walking chicken ".Therefore, centre word extracts single
This is moved guest's Phrase extraction as the centre word of the first natural sentences in the micro-blog information by member 210.
Similarly, centre word extraction unit 210 carries out second in first micro-blog information with Third Nature sentence similar
Processing.Wherein, since Third Nature sentence only includes a word, it is clear that it is known that the structure of its syntax tree is incomplete.
It is therefore preferred that the Third Nature sentence is filtered out from first micro-blog information, so as to by it is too short, can not wrap
Some " patches of pouring water " (for example, "top", " laughing a great ho-ho " etc.) containing any centre word filters out in this stage, to mitigate engine clothes
Data analysis load of the business device 410 when the subsequent degree of correlation matches.
After completing to extract the centre word that all natural sentences in first micro-blog information carry out, similarly, center
Word extraction unit 210 then starts to carry out similar centre word extraction process to subsequent Article 2 to Article 5 micro-blog information,
To obtain the correlating center word of all five micro-blog informations.
It should be noted that although establishing syntax tree here by context-free grammar is used and will be in syntax tree
Mastery phrase be determined as the mode of centre word to illustrate step S310, still, it will be appreciated to those of skill in the art that
The invention is not limited thereto.But it can also use for example by that will segment obtained word and include multiple predefined centre words
Core word dictionary be compared to determine in the micro-blog information with the presence or absence of by the predefined centre word of operator method
To realize step S310.
In step s 320, by calculating the degree of correlation of the centre word and predefined classification, to obtain the microblogging
The degree of correlation of information and the predefined classification.
Specifically, in engine server 410, degree of correlation obtaining unit 220 is received from centre word extraction unit 210 upper
State one or more centre words that obtained each micro-blog information by filtering is extracted in step S310.Moreover, the correlation
Degree obtaining unit 220 extracts multiple predefined classification from the memory (not shown) of engine server 410, and this predefined point
Class is artificial defined, and for carrying out automatic clustering to each micro-blog information according to them.
Next, the centre word degree of correlation probability library that degree of correlation obtaining unit 220 is obtained using preparatory training, for each
A predefined classification, to establish the space vector of the classification, each of described space vector element respectively refers to show
The degree of correlation of each of centre word centre word and the predefined classification.The centre word degree of correlation probability library is by operating
Member's training in advance obtains, it includes each pre-set centre word of operator phase with each predefined classification respectively
Guan Du, the degree of correlation are a kind of probability values, for showing centre word probability relevant to the predefined classification, value range
It is from 0 to 1, wherein 0 is completely uncorrelated, and 1 is perfectly correlated.
In the following, describing relatedness computation step S320 according to an embodiment of the present invention with reference to Fig. 6 A to 6C.
Fig. 6 A to 6C illustrates the degree of correlation for the centre word and predefined classification being calculated according to embodiments of the present invention
Example.Where it is assumed that in including in a certain micro-blog information that centre word extraction unit 210 extracts in step s310
Heart word is " eating ", " walking chicken ", " taking pictures ", " tour pal " this four centre words, and is assumed predefined in engine server 410
Classification include " photography ", " cuisines " and " travelling " these three classify.
At this point, degree of correlation obtaining unit 220 calculates separately aforementioned four center using the centre word degree of correlation probability library
The degree of correlation of each of each of word centre word and above three classification classification.
For the first predefined classification " photography ", it is obtained by calculation, the degree of correlation of the first centre word " eating " and the classification
It is very low, only 0.1；Second centre word " walking chicken " is still very low with the degree of correlation of the classification, and only 0.1；Third centre word " is clapped
According to " high with the degree of correlation of the classification, both to indicate perfectly correlated 1；4th centre word " tour pal " is related to the classification
Degree is 0.3.
For the second predefined classification " cuisines ", it is obtained by calculation, the degree of correlation of the first centre word " eating " and the classification
It is very high, it is 0.9；Second centre word " walking chicken " and the degree of correlation of the classification are 0.8；Third centre word " taking pictures " and the classification
The degree of correlation is very low, and only 0.1；4th centre word " tour pal " and the degree of correlation of the classification are 0.3.
For the predefined classification " travelling " of third, it is obtained by calculation, the degree of correlation of the first centre word " eating " and the classification
It is 0.3；Second centre word " walking chicken " is very low with the degree of correlation of the classification, is 0.1；Third centre word " taking pictures " and the classification
The degree of correlation is 0.6；The degree of correlation very a height of 0.9 of 4th centre word " tour pal " and the classification.
As a result, through the above steps, degree of correlation obtaining unit 220 can use centre word degree of correlation probability Ku Lai get
Out: the space vector of micro-blog information classification " photography " predefined for first is t1={ 0.1,0.1,1,0.3 }；It is described micro-
The space vector of rich information classification " cuisines " predefined for second is t2={ 0.9,0.8,0.1,0.3 }；The micro-blog information
The space vector of classification " travelling " predefined for third is t3={ 0.3,0.1,0.6,0.9 }, to establish each center
The degree of correlation probability distribution space of word and predefined classification.
Finally, degree of correlation obtaining unit 220 is by by the sum of the degree of correlation of each centre word and a certain predefined classification,
The degree of correlation as the micro-blog information and the predefined classification.
For example, the micro-blog information and the degree of correlation of the first predefined classification are 0.1+0.1+1+0.3=1.5；It is described micro-
Rich information and the degree of correlation of the second predefined classification are 0.9+0.8+0.1+0.3=2.1；The micro-blog information and third are predefined
The degree of correlation of classification is 0.3+0.1+0.6+0.9=1.9.
It is apparent that when certain micro-blog information only exists a centre word, the centre word and a certain predefined classification
The degree of correlation is the degree of correlation of the micro-blog information Yu the predefined classification.
Referring back to Fig. 3, in step S330, the micro-blog information is categorized into the predefined classification.
In engine server 410, taxon 230 receives each item being calculated from degree of correlation obtaining unit 220
The degree of correlation of micro-blog information and each predefined classification, by the degree of correlation and first of the micro-blog information and the predefined classification
Threshold value is compared.If the degree of correlation of the micro-blog information and the predefined classification is higher than the first threshold values, from being higher than
The maximum degree of correlation is selected in the degree of correlation of first threshold, and the micro-blog information is categorized into and the maximum relation degree pair
In the predefined classification answered.And if the micro-blog information and the degree of correlation of the predefined classification are lower than the first threshold values,
The micro-blog information is not categorized into the predefined classification then.
Specifically, each micro-blog information that degree of correlation obtaining unit 220 is calculated taxon 230 with it is each pre-
The degree of correlation and first threshold of defining classification are compared.Here, for convenience of explanation, which is assumed to be 1.8.
Referring still to Fig. 6 A to 6C illustrated example, taxon 230, which receives the centre word for including, to be " eating ", " walks
Ground chicken ", " taking pictures ", this micro-blog information of " tour pal " this four centre words and the first predefined degree of correlation for classifying " photography " are
1.5；The degree of correlation with the second predefined classification " cuisines " is 2.1；The degree of correlation with the predefined classification " travelling " of third is 1.9.
Then, which is compared these three degrees of correlation and first threshold 1.8.It can be found that this is micro-
Rich information and the degree of correlation of second and the predefined classification of third are all larger than first threshold, and related to the second predefined classification
Degree 2.1 is greater than the degree of correlation 1.9 with the predefined classification of third, therefore, the taxon 230 by the micro-blog information be categorized into
In the predefined classification " cuisines " of maximum relation degree 2.1 corresponding second.
In another example, if certain micro-blog information and the degree of correlation of first to the predefined classification of third are respectively less than first
Threshold value 1.8, then this micro-blog information is not categorized into any one of described predefined classification by the taxon 230.And
And step S330 at the end of, i.e., after completing sort operation of each micro-blog information to all predefined classification, this
All micro-blog informations not being categorized into the predefined classification are categorized into one or more newly-built points by taxon 230
In class.
For example, the taxon 230 can will be respectively less than the institute of first threshold with the degree of correlation of each predefined classification
There is micro-blog information to be referred to one to be known as in the classification of " other " or " miscellaneous ", is then looking to have classified to avoid user
When each micro-blog information, it can not view and believe to by the predefined less related or not related certain microbloggings of classifying of operator
Breath.
Alternatively, which can also be preferably more related (for example, center by centre word wherein included
Word " piano " and centre word " electronic organ " and centre word " accordion ") a plurality of micro-blog information be referred to a newly-built classification
In, and with the nearest centre word of the geometric center point of the centre word apart from all micro-blog informations (for example, centre word " piano ")
Title as the newly-built classification.
In step S340, it is iterated cluster.
In engine server 410, after micro-blog information being categorized into each predefined classification, taxon
230 are compared the number of all classification with second threshold.If the number of the classification is greater than the second threshold, make
With the method for space clustering, continue iteration cluster, until the number of classification is less than or equal to the second threshold.And if
The number of the classification is less than or equal to the second threshold, then executes subsequent step S350.
Specifically, each micro-blog information is completed to all classification behaviour in the predefined classification and/or newly-built classification
After work, which is compared the number of classification existing at present with a second threshold.For example, this second
Threshold value is set by the user, and allows on the display interface of the microblogging client of user while showing for representing
The number for the classification shown.
For example, if after first time sort operation, presently, there are classification number be 8, and the second threshold is 5
A, then the taxon 230 is determined to need to be iterated the operation of cluster, and the number that will classify tapers into 5.
In one example, which can delete wherein in all predefined classification with minimum
The predefined classification of the first of purpose micro-blog information；For the micro-blog information in the described first predefined classification, again through calculating
The centre word of the micro-blog information in all predefined classification other than the described first predefined classification other are predetermined
The degree of correlation of justice classification, to obtain the degree of correlation of the micro-blog information Yu other predefined classification；And it is if described micro-
Rich information and the degree of correlation of other predefined classification are higher than the first threshold values, then reclassify the micro-blog information described
In one of other predefined classification.
For example, it is assumed that having 1 micro-blog information in the first predefined classification at this time, there are 2 in the second predefined classification
Micro-blog information ... ..., and there are 8 articles of micro-blog informations in the 8th predefined classification.So, which can delete this
First predefined classification, and the centre word in this micro-blog information in the first predefined classification is re-read out,
And return to step S320 and S330.For instance, it is preferred that can not be by each centre word of all micro-blog informations in step
It deletes, but is stored in a temporary storage (not shown) from engine server 410 after S330, until complete
It is purged again after ingredient generic operation.
That is, the degree of correlation obtaining unit 220 recalculates one or more centre words and second of this micro-blog information in advance
Defining classification to the 8th predefined classification the degree of correlation, to obtain the phase of the micro-blog information with other 7 predefined classification
Guan Du.As described above, the taxon 230 further judges the degree of correlation of the micro-blog information Yu other 7 predefined classification
Whether the first threshold values is higher than.If being higher than first threshold, which selects from the degree of correlation for being higher than first threshold
The maximum degree of correlation, and the micro-blog information is categorized into predefined classification corresponding with the maximum relation degree.Such as
Fruit is lower than first threshold, then this microblogging is categorized into the classification of for example entitled " other " by the taxon 230.
At this point, number of the taxon 230 again by all classification is compared with second threshold.Due to current classification
Number 7 are still greater than second threshold 5, so taxon 230 repeats step S340, it will include 2 micro-blog informations
The second classified deletion, and so on.In this way, the method for 230 use space of taxon cluster, by similar micro-blog information
It is classified as one kind, until the classification number of classification is less equal than preset number.
In another example, which can also calculate any two in each classification according to preset criterion
It is the distance between a, and a classification will be merged into apart from the smallest two classification between the two, will directly to sort out
To 8 classification taper into preset number.
In step S350, the abstract and concern temperature of classification are determined.
In engine server 410, specifically, whole micro-blog informations is all referred to present count in taxon 230
After in purpose classification, it is preferable that it can also be directed to each predefined classification, select related to the predefined classification
Spend maximum micro-blog information, and by using in selected micro-blog information picture and/or centre word as thumbnail and/or
Abstract is to show the predefined classification, and except the title except through classification, user can also pass through the classification
Thumbnail and/or abstract clearly understand the theme of the micro-blog information for including in this classification.
Moreover it is preferred that the taxon 230 can also by micro-blog information number in the predefined classification and
Richness, to determine microblogging publisher for the concern temperature of the predefined classification.
For example, the taxon 230 by the quantity of the sentence with complete syntax tree and the product comprising word number come
Determine that temperature is paid close attention in the classification.Assuming that including 2 micro-blog informations in a certain predefined classification, first micro-blog information includes 1
Sentence with complete syntax tree, number of words is 30 words, and Article 2 micro-blog information includes 2 sentences with complete syntax tree
Son, number of words are respectively 10 words and 20 words.Then, which can be calculated as 1 × 30 for the concern temperature of the classification
+ 1 × 10+1 × 20=60.
To which user can understand microblogging publisher for this classification scheme according to the concern temperature of some classification
Interest level, so that user is best understood from the hobby of microblogging publisher.
In step S360, classified micro-blog information is shown.
Specifically, in categorizing system 400, after engine server 410 is completed for the sort operation of micro-blog information,
The engine server 410 can push each micro-blog information and the classification belonging to them to microblogging client 450.
For example, the display processing unit 240 in microblogging client 450 connects from the taxon 230 in engine server 410
Sorted micro-blog information is received, and is preset according to user or the layout information Automatic Typesetting of system default and adjustment connect
The micro-blog information received, and the micro-blog information is shown to user according to different classification and period.
In the following, describing micro-blog information according to an embodiment of the present invention with reference to Fig. 7 and Fig. 8 shows step S360.
Fig. 7 illustrates the preview display interface according to an embodiment of the present invention shown in microblogging client 450, and Fig. 8
Illustrate the classification display interface according to an embodiment of the present invention shown in microblogging client 450.
As illustrated in figure 7, some user Edwin may wish to oneself Yao Chen of interest, day surprise, small s et al.
In micro-blog information in different time periods, then the user uses categorizing system 400 according to an embodiment of the present invention in advance, above-mentioned
The micro-blog information of above-mentioned each microblogging publisher is grabbed and classified in step S300 to S350.
Then, user jumps to classification microblogging interface from traditional microblogging browser interface.It is pre- in classification microblogging interface
It lookes in display interface, the account number of user people of interest can be shown one by one, wherein opening the account for having update so far away from last time
It number can highlight to show.For example, the display processing unit 240 in microblogging client 450 (for example, mobile phone) is being located at
A display screen display preview display interface in microblogging client 450, as illustrated in figure 7.Including the user oneself
User name Edwin and the user name of microbloggings publisher such as head portrait and odd, the small s in user Yao Chen of interest, day and corresponding
Head portrait.
Thereafter, user selects to want the account number (for example, small s) of the microblogging publisher of classified browse, so that microblogging client
Display processing unit 240 in 450 is in display screen display classification display interface.As illustrated in figure 8, categorizing system 400 has been
It will be classified automatically according to the degree of correlation to micro-blog information all in microblogging publisher's account number, and mark out popular degree, and
And it sorts according to the sequence in year.In fig. 8, account micro-blog information in 2010 is classified as 5 classes, respectively " photography ", " dynamic
Object ", " life ", " travelling ", " cuisines ", wherein " photography " hot topic degree highest, hot value is up to 345.
Then, which can choose the reading that detailed microblogging is carried out into some specific classification (for example, photography)；
Or the user also can choose " 2010 " in the upper right corner below arrow " " " or pull to the left, to be shown in 2010
Thinner one layer classification as unit of the moon, the same user also can choose the arrow of the right intermediate " 2009 " below
" " " or pull to the left, to be shown in 2009 the thinner one layer classification as unit of the moon.
It can be seen that user can pass through the degree of correlation point of each content of microblog to designated time period, specified publisher
Analysis, the high microblogging of the degree of correlation classify with the classification (or classification of automatic sorting) of predefined and temporally or phase automatically
Degree sequence in pass sorts, and sorted information extraction is represented into picture and microblogging text after Automatic Typesetting show.In this way, when using
When family faces a large amount of micro-blog information, which can both carry out preview central theme in a manner of guide look, while also can be into sense
The theme of interest is further read, to provide the new user experience for reading massive micro-blog.
Therefore, using the present invention, user can directly select the object to be paid close attention to and period, intuitively enter interested
Certain a kind of microblogging；The representational picture of each classification and abstract can be seen in initial preview page；It can be with side
Just mode, which jumps, looks back previous micro-blog information；And user can be facilitated quick after sorting out and calculating popular degree
Find most popular classification scheme.
In conclusion the present invention changes the mode of microblogging reading traditional at present, it is changed into fastly from information reading one by one
The new experience of oneself interested content is only read after fast browse themes, and the present invention can easily pass through software or hard
The form of part is readily applied on all kinds of consumer electronics products, to be effectively improved the microblogging viewing experience of user.
Each embodiment of the invention has been described in detail above.However, it should be appreciated by those skilled in the art that not taking off
In the case where from the principle and spirit of the invention, these embodiments can be carry out various modifications, combination or sub-portfolio, and in this way
Modification should fall within the scope of the present invention.
Claims (8)
1. a kind of system of micro-blog information classification display, comprising:
Engine server and microblogging client,
The engine server is in network-side, connect with the micro blog server for providing microblogging service, can be from microblogging service
The micro-blog information that microblogging publisher issues in time range is downloaded on device, and is classified automatically to micro-blog information；
Microblogging client is in user terminal and connect with the engine server,
The microblogging client includes: input information receiving unit, automatic sorted for receiving the progress on engine server
Micro-blog information；Display processing unit is shown to user.
2. a kind of engine server of micro-blog information classification display, comprising: centre word extraction unit, divides at degree of correlation obtaining unit
Class unit and micro-blog information acquiring unit.
Micro-blog information acquiring unit is during downloading micro-blog information, in addition to obtaining the microblogging hair in the time range
Except all micro-blog informations that cloth people itself is issued, other microbloggings publisher is also obtained for microblogging publisher itself institute
The return information that the micro-blog information of publication is made.
3. engine server as claimed in claim 2, which is characterized in that if it find that user is not concerned with microblogging publisher, then lead to
The display processing unit crossed in microblogging client prompts the user with the concern added for microblogging publisher.
4. engine server as claimed in claim 3, which is characterized in that after user has added concern, engine server continues
It is downloaded operation.
5. engine server as claimed in claim 2, which is characterized in that
Degree of correlation obtaining unit is obtained using the centre word degree of correlation probability library: predefined for difference point of the micro-blog information
The space vector of class, to establish the degree of correlation of each centre word Yu predefined classification.
6. engine server as claimed in claim 2, which is characterized in that
The training in centre word degree of correlation probability library, including each pre-set centre word respectively with each predefined classification
The degree of correlation.
7. a kind of microblogging client, which is characterized in that require the corresponding operating of 1-6 for perform claim.
8. a kind of method of micro-blog information classification display, comprising:
Extract micro-blog information；
Classified by calculating the degree of correlation of the micro-blog information and predefined classification to micro-blog information；
According to the micro-blog information number and richness in the predefined classification, determine microblogging publisher for described predefined
The concern temperature of classification.
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| CN201811157427.7A CN109271518B (en) | 2012-04-28 | 2012-04-28 | Method and equipment for classified display of microblog information |
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| CN201811157427.7A CN109271518B (en) | 2012-04-28 | 2012-04-28 | Method and equipment for classified display of microblog information |
| CN201210132513.9A CN103377258B (en) | 2012-04-28 | 2012-04-28 | Method and apparatus for carrying out classification display to micro-blog information |
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Families Citing this family (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104636394A (en) * | 2013-11-15 | 2015-05-20 | 腾讯科技（北京）有限公司 | Displaying method, system and device for user generated content information |
| CN103580997B (en) * | 2013-11-19 | 2017-09-29 | 湖南蚁坊软件有限公司 | The extracting method and its device of a kind of popular microblogging in vertical field |
| CN104778184A (en) * | 2014-01-15 | 2015-07-15 | 腾讯科技（深圳）有限公司 | Feedback keyword determining method and device |
| CN104809109B (en) * | 2014-01-23 | 2019-12-10 | 腾讯科技（深圳）有限公司 | social information display method and device and server |
| CN105653533B (en) * | 2014-11-13 | 2019-10-25 | 腾讯数码（深圳）有限公司 | A kind of method and apparatus updating classification associated set of words |
| CN105187291B (en) * | 2015-07-17 | 2019-04-26 | 天脉聚源（北京）科技有限公司 | The method and apparatus for showing release information |
| CN105119808A (en) * | 2015-07-17 | 2015-12-02 | 天脉聚源（北京）科技有限公司 | Method and device for displaying published information |
| CN105162877A (en) * | 2015-09-24 | 2015-12-16 | 西安未来国际信息股份有限公司 | Enterprise internal information interaction method |
| CN105447142B (en) * | 2015-11-23 | 2019-03-26 | 中国农业大学 | A kind of double mode agricultural science and technology achievement classification method and system |
| CN106202032B (en) * | 2016-06-24 | 2018-08-28 | 广州数说故事信息科技有限公司 | A kind of sentiment analysis method and its system towards microblogging short text |
| CN106249989B (en) * | 2016-07-20 | 2020-03-31 | 努比亚技术有限公司 | Method for arranging social application program icons during content sharing and mobile terminal |
| CN106599155B (en) * | 2016-12-07 | 2020-05-26 | 北京亚鸿世纪科技发展有限公司 | Webpage classification method and system |
| CN106777324A (en) * | 2017-01-09 | 2017-05-31 | 北京奇虎科技有限公司 | The cluster display methods of social networking application platform resource, device and mobile terminal |
| CN107104882A (en) * | 2017-04-20 | 2017-08-29 | 奇酷互联网络科技（深圳）有限公司 | The method, device and mobile terminal of good friend's speech information are shown in social software |
| CN107656958B (en) * | 2017-06-09 | 2019-07-19 | 平安科技（深圳）有限公司 | A kind of classifying method and server of multi-data source data |
| CN107590130B (en) * | 2017-09-30 | 2019-06-14 | 北京三快在线科技有限公司 | Scene determines method and device, storage medium and electronic equipment |
| CN110020159B (en) * | 2017-12-11 | 2021-05-07 | 网智天元科技集团股份有限公司 | Public opinion analysis method and system based on data characteristics |
Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101071424A (en) * | 2006-06-23 | 2007-11-14 | 腾讯科技（深圳）有限公司 | Personalized information push system and method |
| CN101071443A (en) * | 2007-06-26 | 2007-11-14 | 腾讯科技（深圳）有限公司 | Content-related advertising identifying method and content-related advertising server |
| US20080091684A1 (en) * | 2006-10-16 | 2008-04-17 | Jeffrey Ellis | Internet-based bibliographic database and discussion forum |
| CN101299769A (en) * | 2008-05-14 | 2008-11-05 | 天津华永无线科技有限公司 | Micro blog system based on geographical position and construction method thereof |
| CN101808152A (en) * | 2009-02-13 | 2010-08-18 | 宏达国际电子股份有限公司 | Method and device for prompting and browsing coordinator relevant information and computer program product |
| CN101855612A (en) * | 2007-06-21 | 2010-10-06 | 概要软件有限责任公司 | System and method for compending blogs |
| CN101917456A (en) * | 2010-07-06 | 2010-12-15 | 杭州热点信息技术有限公司 | Content-aggregated wireless issuing system |
| CN101980497A (en) * | 2010-10-20 | 2011-02-23 | 北京开心人信息技术有限公司 | Method and system for displaying friend trends in classified way |
| CN102073707A (en) * | 2010-12-22 | 2011-05-25 | 百度在线网络技术（北京）有限公司 | Method and device for identifying short text category information in real time, and computer equipment |
| CN102194012A (en) * | 2011-06-17 | 2011-09-21 | 清华大学 | Microblog topic detecting method and system |
| CN102214220A (en) * | 2011-06-09 | 2011-10-12 | 深圳市多易得信息技术有限公司 | System and method for propagating proper information from proper propagator to proper audience |
| US20120005224A1 (en) * | 2010-07-01 | 2012-01-05 | Spencer Greg Ahrens | Facilitating Interaction Among Users of a Social Network |
| CN102402378A (en) * | 2010-09-17 | 2012-04-04 | 腾讯科技（深圳）有限公司 | Method and device for displaying message |
| CN102420779A (en) * | 2011-11-16 | 2012-04-18 | 何劲 | Method for transmitting micro-blog information for follower account |
Family Cites Families (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20080126319A1 (en) * | 2006-08-25 | 2008-05-29 | Ohad Lisral Bukai | Automated short free-text scoring method and system |
| CN101458713A (en) * | 2008-12-29 | 2009-06-17 | 北京搜狗科技发展有限公司 | Website classifying method and system |
| CN102323923B (en) * | 2011-05-18 | 2013-07-24 | 北京百纳威尔科技有限公司 | Method for processing historical record and equipment |
| CN102194013A (en) * | 2011-06-23 | 2011-09-21 | 上海毕佳数据有限公司 | Domain-knowledge-based short text classification method and text classification system |
| CN102279890A (en) * | 2011-09-02 | 2011-12-14 | 苏州大学 | Sentiment word extracting and collecting method based on micro blog |
-
2012
- 2012-04-28 CN CN201811157427.7A patent/CN109271518B/en not_active Expired - Fee Related
- 2012-04-28 CN CN201210132513.9A patent/CN103377258B/en not_active Expired - Fee Related
Patent Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101071424A (en) * | 2006-06-23 | 2007-11-14 | 腾讯科技（深圳）有限公司 | Personalized information push system and method |
| US20080091684A1 (en) * | 2006-10-16 | 2008-04-17 | Jeffrey Ellis | Internet-based bibliographic database and discussion forum |
| CN101855612A (en) * | 2007-06-21 | 2010-10-06 | 概要软件有限责任公司 | System and method for compending blogs |
| CN101071443A (en) * | 2007-06-26 | 2007-11-14 | 腾讯科技（深圳）有限公司 | Content-related advertising identifying method and content-related advertising server |
| CN101299769A (en) * | 2008-05-14 | 2008-11-05 | 天津华永无线科技有限公司 | Micro blog system based on geographical position and construction method thereof |
| CN101808152A (en) * | 2009-02-13 | 2010-08-18 | 宏达国际电子股份有限公司 | Method and device for prompting and browsing coordinator relevant information and computer program product |
| US20120005224A1 (en) * | 2010-07-01 | 2012-01-05 | Spencer Greg Ahrens | Facilitating Interaction Among Users of a Social Network |
| CN101917456A (en) * | 2010-07-06 | 2010-12-15 | 杭州热点信息技术有限公司 | Content-aggregated wireless issuing system |
| CN102402378A (en) * | 2010-09-17 | 2012-04-04 | 腾讯科技（深圳）有限公司 | Method and device for displaying message |
| CN101980497A (en) * | 2010-10-20 | 2011-02-23 | 北京开心人信息技术有限公司 | Method and system for displaying friend trends in classified way |
| CN102073707A (en) * | 2010-12-22 | 2011-05-25 | 百度在线网络技术（北京）有限公司 | Method and device for identifying short text category information in real time, and computer equipment |
| CN102214220A (en) * | 2011-06-09 | 2011-10-12 | 深圳市多易得信息技术有限公司 | System and method for propagating proper information from proper propagator to proper audience |
| CN102194012A (en) * | 2011-06-17 | 2011-09-21 | 清华大学 | Microblog topic detecting method and system |
| CN102420779A (en) * | 2011-11-16 | 2012-04-18 | 何劲 | Method for transmitting micro-blog information for follower account |
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| Publication number | Publication date |
|---|---|
| CN109271518B (en) | 2021-12-07 |
| CN103377258A (en) | 2013-10-30 |
| CN103377258B (en) | 2018-11-02 |
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