CN104462448A - Group name classification method and device - Google Patents

Group name classification method and device Download PDF

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CN104462448A
CN104462448A CN201410779559.9A CN201410779559A CN104462448A CN 104462448 A CN104462448 A CN 104462448A CN 201410779559 A CN201410779559 A CN 201410779559A CN 104462448 A CN104462448 A CN 104462448A
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sorted
packet name
grouping
eigenwert
perpetual object
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CN104462448B (en
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李金奎
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Weimeng Chuangke Network Technology China Co Ltd
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Weimeng Chuangke Network Technology China Co Ltd
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    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/01—Social networking

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Abstract

The invention discloses a group name classification method and aims to solve the problem that the use of the prior grouping methods may lead to inaccurateness of information recommended to users. The method mainly includes: acquiring group names to be classified; according to features of followed objects included in groups indicated by the group names to be classified, determining feature values of the group names to be classified; according to the feature values of the group names to be classified, classifying the group names to be classified. The invention further discloses a group name classification device.

Description

A kind of packet name sorting technique and device
Technical field
The application relates to field of computer technology, particularly relates to a kind of packet name sorting technique and device.
Background technology
Packet name, generally refers to: the user in social networks according to the relation of oneself and perpetual object, or according to the reason that oneself is become interested to perpetual object, after perpetual object is divided into different grouping, is the title of dividing into groups to get.Because packet name often can embody hobby and the social networks of individual subscriber, therefore packet name generally can be divided into two classifications, be respectively " relation classification " and " category of interest ", packet name in these two classifications is respectively the packet name relevant with the social networks of user, and the packet name relevant with the hobby of user.
In prior art, in order to recommend the information relevant with the hobby of user or the information relevant with the social networks of user to user, first semantic by packet name, determine the packet name generic that user is arranged on social networks, and then according to this classification, recommend relevant information to user.The defect which exists is: such as the grouping of grouping " colleague " by name, if the perpetual object in this grouping is all video display star, if so only resolved with semanteme, " colleague " this packet name directly may be divided in relation classification, thus cause the information of recommending to user according to this classification inaccurate.
Summary of the invention
The embodiment of the present application provides a kind of packet name sorting technique, may cause the inaccurate problem of information of recommending to user in order to solution according to packet mode of the prior art.
The embodiment of the present application also provides a kind of packet name sorter, may cause the inaccurate problem of information of recommending to user in order to solution according to packet mode of the prior art.
The embodiment of the present application adopts following technical proposals:
A kind of packet name sorting technique, mainly comprises:
Obtain packet name to be sorted;
The feature of the perpetual object that the grouping represented according to described packet name to be sorted comprises, determines the eigenwert of described packet name to be sorted;
According to the eigenwert of described packet name to be sorted, described packet name to be sorted is classified.
A kind of packet name sorter, comprising:
Acquiring unit, for obtaining packet name to be sorted;
Determining unit, the feature of the perpetual object that the grouping for representing according to described packet name to be sorted comprises, determines the eigenwert of described packet name to be sorted;
Taxon, for the eigenwert according to described packet name to be sorted, classifies to described packet name to be sorted.
At least one technical scheme above-mentioned that the embodiment of the present application adopts can reach following beneficial effect:
Owing to being the feature of the perpetual object that the grouping represented according to packet name to be sorted comprises, determine the eigenwert of packet name to be sorted, and this eigenwert is treated classified packets name and is classified, thus classification results is matched with the feature of the perpetual object comprised that divides into groups, solve in prior art and determine packet name generic to be sorted with semanteme, the inaccurate problem of information of recommending to user can be caused.
Accompanying drawing explanation
Accompanying drawing described herein is used to provide further understanding of the present application, and form a application's part, the schematic description and description of the application, for explaining the application, does not form the improper restriction to the application.In the accompanying drawings:
The process flow diagram of a kind of packet name sorting technique that Fig. 1 provides for the embodiment of the present application;
The method flow diagram utilizing decision-tree model to treat classified packets name to carry out classifying that Fig. 2 provides for the embodiment of the present application;
The structured flowchart of a kind of packet name sorter that Fig. 3 provides for the embodiment of the present application.
Embodiment
For making the object of the application, technical scheme and advantage clearly, below in conjunction with the application's specific embodiment and corresponding accompanying drawing, technical scheme is clearly and completely described.Obviously, described embodiment is only some embodiments of the present application, instead of whole embodiments.Based on the embodiment in the application, those of ordinary skill in the art are not making the every other embodiment obtained under creative work prerequisite, all belong to the scope of the application's protection.
Below in conjunction with accompanying drawing, describe the technical scheme that each embodiment of the application provides in detail.
Embodiment 1
In order to solve according to packet mode of the prior art may cause to user recommend the inaccurate problem of information, the application proposes a kind of packet name sorting technique, and the realization flow figure of the method as shown in Figure 1, mainly comprises the steps:
Step 11, obtain packet name to be sorted;
The feature of the perpetual object that step 12, the grouping represented according to packet name to be sorted comprise, determines the eigenwert of packet name to be sorted;
Step 13, eigenwert according to packet name to be sorted, treat classified packets name and classify.
The said method that theres is provided of the embodiment of the present application being provided, owing to being the feature according to getting the perpetual object that grouping that packet name to be sorted represents comprises, determining the eigenwert of packet name to be sorted; And then treat classified packets name according to the eigenwert of this packet name and classify, thus classification results is matched with the feature of the perpetual object comprised that divides into groups, solve in prior art and determine packet name generic to be sorted with semanteme, the inaccurate problem of information of recommending to user can be caused.
Below some optional embodiments of the embodiment of the present application are described in detail.
In one embodiment, in order to avoid the interference by character lack of standardization, before step 12, the packet name to be sorted obtained can be carried out pre-service.
Specifically, can obtain packet name to be sorted the frequency that uses by user; Then, the packet name to be sorted being greater than the default frequency by user institute frequency of usage is extracted; Finally, the packet name to be sorted extracted is carried out form normalization.Wherein, form normalization can be the complex form of Chinese characters is converted into simplified Chinese character, removal punctuation mark and/or upper case character to be converted to lowercase character etc.
In one embodiment, step 12 can be realized by following steps A 1-steps A 2:
Steps A 1, determine to possess correlation degree value corresponding at least one grouping of packet name to be sorted feature as perpetual object;
Steps A 2, according to correlation degree value, determine the eigenwert of packet name to be sorted.
Wherein, the correlation degree value that each grouping is corresponding represents the correlation degree between the perpetual object that current group comprises and the user arranging this grouping.
In the embodiment of the present application, steps A 2 can be, but not limited to following two kinds of implementations:
The first embodiment, steps A 2 can be illustrated by the mathematic(al) representation shown in formula [1]:
AVG f = Σ i = 1 N Count i N - - - [ 1 ]
Wherein, AVG frepresent the eigenwert of packet name to be sorted; N represents the total quantity of the user arranging this packet name to be sorted; I represents Customs Assigned Number, and i ∈ [1, N]; Count irepresent the correlation degree value being numbered the perpetual object that the user of i and the grouping possessing this packet name to be sorted set by this user comprise.
Illustrate further for formula [1]: suppose that grouping to be sorted is called " junior middle school good friend ", the user arranging this packet name has U1 and U2, wherein, there are 100 people by the perpetual object that U1 is divided in " junior middle school good friend " grouping, in this 100 people, have 50 people also to pay close attention to U1 simultaneously; The perpetual object that U2 divides into groups to comprise " junior middle school good friend " has 30 people, has 20 people also to pay close attention to U2 in this 30 people simultaneously.Then can be determined by above-mentioned formula [1]:
N=2, Count 1=50, Count 2=20; And then the eigenwert AVG of packet name to be sorted can be obtained by formula [1] f=35.
The second embodiment: steps A 2 can comprise: by first grouping number that possess to be sorted packet name corresponding according to the correlation degree value being greater than first threshold, and the second grouping number possessing packet name to be sorted that the correlation degree value being less than Second Threshold is corresponding, determine the eigenwert of packet name to be sorted.Wherein, first threshold is greater than Second Threshold.
Specifically, this embodiment can be illustrated by the mathematic(al) representation shown in formula [2]:
Sub = High - Low High × 100 % - - - [ 2 ]
Wherein, Sub represents the eigenwert of packet name to be sorted; High represents the first grouping number possessing packet name to be sorted that the correlation degree value that is greater than first threshold is corresponding; Low represents the second grouping number possessing packet name to be sorted that the correlation degree value that is less than Second Threshold is corresponding.
For the further following citing hypothesis of formula [2]:
Grouping to be sorted is called " junior three six classes ", " machine learning " and " video display artist ";
Possess the total number packets order of group name to be sorted as shown in following table one:
Table one:
Packet name to be sorted Possesses the total number packets order of packet name to be sorted
The junior three six classes 110
Machine learning 837
Video display artist 204
Further, suppose that correlation degree value is mutual powder rate; In addition, possess in 110 groupings of " junior three six classes " this packet name to be sorted, mutual powder rate distributes as shown in Table 2:
Table two:
Similarly, also can obtain distributing with the mutual powder rate of grouping to be sorted like the mutual powder rate distributional class shown in table two " machine learning " and " video display artist " by name, not repeat one by one in this application.
Further, if hypothesis first threshold is 60%, Second Threshold is 30%, then by the statistics of data in the right row of his-and-hers watches two, can obtain: the High=99 that packet name to be sorted " junior three six classes " is corresponding, Low=0, and then according to formula [2], Sub=100% can be calculated.Similarly, the Sub value of other packet name to be sorted " machine learning " and " video display artist " can be obtained.
Based on the Sub value determined, a kind of embodiment of step 13 can comprise:
According to Sub value, and the Sub threshold value of setting, determine packet name generic to be sorted.
In one embodiment, according to the sample packet name gathered in advance, this Sub threshold value can be set.Such as suppose: be called " junior three six classes ", " friend relative " to divide into groups, sample packet set that " siblings " are formed with " machine learning ", " video display are relevant ", " video display artist ", " junior three six classes " if in this sample packet set, " friend relative ", " siblings " relation belonging to classification, and obtain " junior three six classes ", " friend relative ", the accounting of total number packets in grouping set of " siblings " be 39.67%; " machine learning " in this sample packet set, " video display be correlated with ", " video display artist " belong to category of interest, and obtain " machine learning ", " video display are correlated with ", the accounting of total number packets in grouping set of " video display artist " be 60.33%; So, by the training of this sample packet name set, can determine when this Sub threshold value=20%, best classifying quality can be reached.
Above-mentioned hypothesis content specifically please see the following form three:
Table three:
Based on above-mentioned table three, after determining the Sub value of packet name to be sorted, if this Sub>20%, then determine that grouping to be sorted is called relation group, if this Sub≤20%, then determine that grouping to be sorted is called interest grouping.
In one embodiment, step 12 can be realized by following step B1-step B3:
Step B1, determine the quantity of the user using packet name to be sorted;
Step B2, obtain the feature of quantity as packet name to be sorted being divided into the perpetual object of this grouping by user;
Step B3, according to the quantity of user and the quantity of perpetual object, determine the eigenwert of packet name to be sorted.
In the embodiment of the present application, step B3 can be, but not limited to following two kinds of implementations:
The first implementation: step B3 can be illustrated by the mathematic(al) representation shown in formula [3]:
AVG u = Σ j = 1 N Count j N - - - [ 3 ]
Wherein, AVG urepresent the eigenwert of packet name to be sorted; N represents the total quantity of the user arranging this packet name to be sorted; J represents Customs Assigned Number, and j ∈ [1, N]; Count jrepresent the quantity of the perpetual object in the grouping that the user being numbered as j is divided into represented by packet name to be sorted.
Illustrate further for formula [3]: suppose that grouping to be sorted is called " famous person star ", the user arranging this packet name has U1, U2, U3, by U1 be divided into " famous person star " grouping in perpetual object have 100 people, be divided into by U2 " famous person star " grouping in perpetual object have 50 and by U3 be divided into " famous person star " grouping in perpetual object have 30.Then can be determined by above-mentioned formula [3]:
N=3, Count 1=100, Count 2=50, Count 3=30, and then the eigenwert AVG that can be obtained packet name to be sorted by formula [3] u=60.
The second embodiment: step B3 can comprise: by obtaining the quantity of perpetual object that be divided into this grouping by user, that possess specific identifier as grouping feature to be sorted.
Specifically, if user U1 and U2 is the user with specific identifier, then can obtain:
N=2, Count 1=100, Count 2=50, and then can AVG be obtained by formula [3] u=50.
Based on the AVG determined uvalue, a kind of embodiment of step 13 can comprise:
According to AVG uvalue, and the AVG of setting uthreshold value, determines packet name generic to be sorted.
In one embodiment, according to the sample packet name gathered in advance, this AVG can be set uthreshold value.Such as suppose: be called to divide into groups " information muffler ", " automobile 4s shop ", " law court colleague ", " which father goes ", the sample packet set that " investment in gold " and " university classmate " is formed is example, " information muffler " if in this sample packet set, " automobile 4s shop ", " law court colleague " belongs to category of interest, and obtain " information muffler ", " automobile 4s shop ", total number packets accounting in grouping set of " law court colleague " is 38.25%, in this sample packet set " which father goes ", " investment in gold " and " university classmate " relation belonging to classification, and obtain " which father goes ", the accounting of total number packets in grouping set of " investment in gold " and " university classmate " is 61.75%, so, by the training of this sample packet name set, this AVG can be determined uthreshold value=1.
Above-mentioned hypothesis content specifically please see the following form four:
Table four:
Based on above-mentioned table four, work as AVG uduring >1, determine that grouping to be sorted is called category of interest and accounting is 38.25%, work as AVG uwhen≤1, determining that grouping to be sorted is called relation object Ji accounting be not 61.75%, but because formula [3] does not consider correlation degree between user and perpetual object, with the formula [3] not high to obtaining fine granularity of packet name to be sorted, therefore, the mode that the eigenwert that the eigenwert that formula [3] can be utilized to obtain and formula [2] obtain is combined is classified to the eigenwert treating classified packets name.
What more than introduce is several modes of the eigenwert determining packet name to be sorted, below introduces a kind of method that eigenwert according to determining carries out classifying:
First, the eigenwert 10%, 60% utilizing the mode of formula [2] to obtain packet name to be sorted " colleague ", " famous person star " is respectively set, respectively as the First Eigenvalue of " colleague ", " famous person star "; The eigenwert 10,4 utilizing the mode of formula [3] to obtain packet name to be sorted is respectively set, respectively as the Second Eigenvalue of " colleague ", " famous person star "; The eigenwert 100,70 utilizing the mode of formula [1] to obtain packet name to be sorted is respectively set, respectively as the third feature value of " colleague ", " famous person star ".
Then, operation is as follows performed:
Utilize decision-tree model as shown in Figure 2, treat classified packets name and classify.Detailed process is:
Judge whether the First Eigenvalue of " colleague " is greater than 20%; After obtaining the judged result of "No", judge whether Second Eigenvalue is greater than 20; After the judged result obtaining " Second Eigenvalue of colleague is not more than 20 ", judge " colleague " relation belonging to classification.
Judge whether the First Eigenvalue of " famous person star " is greater than 20%; After obtaining the judged result of "Yes", judge whether Second Eigenvalue is in [0,5); Obtaining " Second Eigenvalue is in [0,5) " judged result after, judge whether third feature value is in [0,90), obtaining " the third feature value of famous person star is in [0,90) " judged result after, judge that " famous person star " belongs to category of interest.
In one embodiment, can after determining packet name generic, then to determining that the packet name of classification carries out planningization process.Concrete norm mode can be: the mode of being filtered by part of speech, will determine that the packet name of classification is divided into two parts, is respectively planningization packet name and packet name to be modified.
Specifically, due to the packet name in category of interest, be normally made up of more common noun, verb, adjective etc., therefore can adopt white list mechanism; And other packet name of relation object, normally part of speech is inherently very complicated and changeable, and therefore we adopt blacklist mechanism.Filtering rule can as shown in following table three:
After the planning process completing packet name, for the packet name that each is to be modified, can perform respectively: from planningization packet name, determine the planning packet name that the feature of the perpetual object that the feature of corresponding perpetual object is corresponding with this packet name to be modified is identical, and then this packet name to be modified is revised as this planning packet name determined.
It should be noted that, the executive agent of each step of embodiment 1 supplying method can be all same equipment, or, the method also by distinct device as executive agent.Such as, the executive agent of step 11 and step 12 can be equipment 1, and the executive agent of step 13 can be equipment 2; Again such as, the executive agent of step 11 can be equipment 1, and the executive agent of step 12 and step 13 can be equipment 2; Etc..
Embodiment 2
In order to solve according to packet mode of the prior art may cause to user recommend the inaccurate problem of information, the application proposes a kind of packet name sorter, the realization flow figure of the method as shown in Figure 3, mainly comprise: acquiring unit 31, determining unit 32 and taxon 33, specific as follows:
Acquiring unit 31, for obtaining packet name to be sorted;
Determining unit 32, the feature of the perpetual object that the grouping for representing according to packet name to be sorted comprises, determines the eigenwert of described packet name to be sorted;
Taxon 33, for the eigenwert according to packet name to be sorted, treats classified packets name and classifies.
In one embodiment, determining unit 32, may be used for the correlation degree value of at least one the grouping correspondence determining to possess packet name to be sorted as described feature; Wherein, the correlation degree value that each grouping is corresponding represents the correlation degree between the perpetual object that current group comprises and the user arranging this grouping; According to correlation degree value, determine the eigenwert of packet name to be sorted.
At a kind of embodiment, determining unit 32, may be used for first grouping number corresponding according to the correlation degree value being greater than first threshold, and the second grouping number that the correlation degree value being less than Second Threshold is corresponding, determines the eigenwert of packet name to be sorted; Wherein, first threshold is greater than Second Threshold.
In one embodiment, determining unit 32, can also be used for the quantity determining the user using packet name to be sorted; Obtain and be divided into the quantity of the perpetual object of grouping as this feature by user; According to the quantity of user and the quantity of perpetual object, determine the eigenwert of packet name to be sorted.
In one embodiment, determining unit 32, may be used for the feature of quantity as packet name to be sorted of perpetual object that acquisition is divided into grouping by user, that possess specific identifier.
The device that theres is provided of above-described embodiment 2 being provided, owing to being the feature according to getting the perpetual object that grouping that packet name to be sorted represents comprises, determining the eigenwert of packet name to be sorted; And then treat classified packets name according to the eigenwert of this packet name and classify.Thus classification results is matched with the feature of perpetual object of dividing into groups to comprise, and then solve the inaccurate problem of information that packet mode of the prior art may cause recommending to user.
Those skilled in the art should understand, embodiments of the invention can be provided as method, system or computer program.Therefore, the present invention can adopt the form of complete hardware embodiment, completely software implementation or the embodiment in conjunction with software and hardware aspect.And the present invention can adopt in one or more form wherein including the upper computer program implemented of computer-usable storage medium (including but not limited to magnetic disk memory, CD-ROM, optical memory etc.) of computer usable program code.
The present invention describes with reference to according to the process flow diagram of the method for the embodiment of the present invention, equipment (system) and computer program and/or block scheme.Should understand can by the combination of the flow process in each flow process in computer program instructions realization flow figure and/or block scheme and/or square frame and process flow diagram and/or block scheme and/or square frame.These computer program instructions can being provided to the processor of multi-purpose computer, special purpose computer, Embedded Processor or other programmable data processing device to produce a machine, making the instruction performed by the processor of computing machine or other programmable data processing device produce device for realizing the function of specifying in process flow diagram flow process or multiple flow process and/or block scheme square frame or multiple square frame.
These computer program instructions also can be stored in can in the computer-readable memory that works in a specific way of vectoring computer or other programmable data processing device, the instruction making to be stored in this computer-readable memory produces the manufacture comprising command device, and this command device realizes the function of specifying in process flow diagram flow process or multiple flow process and/or block scheme square frame or multiple square frame.
These computer program instructions also can be loaded in computing machine or other programmable data processing device, make on computing machine or other programmable devices, to perform sequence of operations step to produce computer implemented process, thus the instruction performed on computing machine or other programmable devices is provided for the step realizing the function of specifying in process flow diagram flow process or multiple flow process and/or block scheme square frame or multiple square frame.
In one typically configuration, computing equipment comprises one or more processor (CPU), input/output interface, network interface and internal memory.
Internal memory may comprise the volatile memory in computer-readable medium, and the forms such as random access memory (RAM) and/or Nonvolatile memory, as ROM (read-only memory) (ROM) or flash memory (flash RAM).Internal memory is the example of computer-readable medium.
Computer-readable medium comprises permanent and impermanency, removable and non-removable media can be stored to realize information by any method or technology.Information can be computer-readable instruction, data structure, the module of program or other data.The example of the storage medium of computing machine comprises, but be not limited to phase transition internal memory (PRAM), static RAM (SRAM), dynamic RAM (DRAM), the random access memory (RAM) of other types, ROM (read-only memory) (ROM), Electrically Erasable Read Only Memory (EEPROM), fast flash memory bank or other memory techniques, read-only optical disc ROM (read-only memory) (CD-ROM), digital versatile disc (DVD) or other optical memory, magnetic magnetic tape cassette, tape magnetic rigid disk stores or other magnetic storage apparatus or any other non-transmitting medium, can be used for storing the information can accessed by computing equipment.According to defining herein, computer-readable medium does not comprise temporary computer readable media (transitory media), as data-signal and the carrier wave of modulation.
Also it should be noted that, term " comprises ", " comprising " or its any other variant are intended to contain comprising of nonexcludability, thus make to comprise the process of a series of key element, method, commodity or equipment and not only comprise those key elements, but also comprise other key elements clearly do not listed, or also comprise by the intrinsic key element of this process, method, commodity or equipment.When not more restrictions, the key element limited by statement " comprising ... ", and be not precluded within process, method, commodity or the equipment comprising described key element and also there is other identical element.
It will be understood by those skilled in the art that the embodiment of the application can be provided as method, system or computer program.Therefore, the application can adopt the form of complete hardware embodiment, completely software implementation or the embodiment in conjunction with software and hardware aspect.And the application can adopt in one or more form wherein including the upper computer program implemented of computer-usable storage medium (including but not limited to magnetic disk memory, CD-ROM, optical memory etc.) of computer usable program code.
The foregoing is only the embodiment of the application, be not limited to the application.To those skilled in the art, the application can have various modifications and variations.Any amendment done within all spirit in the application and principle, equivalent replacement, improvement etc., within the right that all should be included in the application.

Claims (10)

1. a packet name sorting technique, is characterized in that, comprising:
Obtain packet name to be sorted;
The feature of the perpetual object that the grouping represented according to described packet name to be sorted comprises, determines the eigenwert of described packet name to be sorted;
According to the eigenwert of described packet name to be sorted, described packet name to be sorted is classified.
2. the method for claim 1, is characterized in that, the feature of the perpetual object that the grouping represented according to described packet name to be sorted comprises, and determines the eigenwert of described packet name to be sorted, comprising:
Determine that the correlation degree value of at least one the grouping correspondence possessing described packet name to be sorted is as described feature; Wherein, the correlation degree value that each grouping is corresponding represents the correlation degree between the perpetual object that current group comprises and the user arranging this grouping;
According to described correlation degree value, determine the eigenwert of packet name to be sorted.
3. method as claimed in claim 2, is characterized in that, according to described correlation degree value, determine the eigenwert of packet name to be sorted, specifically comprise:
First grouping number corresponding according to the correlation degree value being greater than first threshold, and the second grouping number that the correlation degree value being less than Second Threshold is corresponding, determine the eigenwert of packet name to be sorted;
Wherein, first threshold is greater than Second Threshold.
4. the method for claim 1, is characterized in that, the feature of the perpetual object that the grouping represented according to described packet name to be sorted comprises, and determines the eigenwert of described packet name to be sorted, comprising:
Determine the quantity of the user using described packet name to be sorted;
Obtain and be divided into the quantity of the perpetual object of described grouping as described feature by described user;
According to the quantity of described user and the quantity of described perpetual object, determine the eigenwert of packet name to be sorted.
5. method as claimed in claim 4, is characterized in that, obtain and be divided into the quantity of the perpetual object of described grouping as described feature by described user, comprising:
Obtain the quantity of perpetual object that be divided into described grouping by described user, that possess specific identifier as described feature.
6. a packet name sorter, is characterized in that, comprising:
Acquiring unit, for obtaining packet name to be sorted;
Determining unit, the feature of the perpetual object that the grouping for representing according to described packet name to be sorted comprises, determines the eigenwert of described packet name to be sorted;
Taxon, for the eigenwert according to described packet name to be sorted, classifies to described packet name to be sorted.
7. device as claimed in claim 6, is characterized in that, described determining unit, specifically for:
Determine that the correlation degree value of at least one the grouping correspondence possessing described packet name to be sorted is as described feature; Wherein, the correlation degree value that each grouping is corresponding represents the correlation degree between the perpetual object that current group comprises and the user arranging this grouping;
According to described correlation degree value, determine the eigenwert of packet name to be sorted.
8. device as claimed in claim 7, is characterized in that, described determining unit, specifically for:
First grouping number corresponding according to the correlation degree value being greater than first threshold, and the second grouping number that the correlation degree value being less than Second Threshold is corresponding, determine the eigenwert of packet name to be sorted;
Wherein, first threshold is greater than Second Threshold.
9. device as claimed in claim 6, is characterized in that, described determining unit, specifically for:
Determine the quantity of the user using described packet name to be sorted;
Obtain and be divided into the quantity of the perpetual object of described grouping as described feature by described user;
According to the quantity of described user and the quantity of described perpetual object, determine the eigenwert of packet name to be sorted.
10. device as claimed in claim 9, is characterized in that, described determining unit, specifically for:
Obtain the quantity of perpetual object that be divided into described grouping by described user, that possess specific identifier as described feature.
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