CN104462448B - A kind of packet name classification method and device - Google Patents
A kind of packet name classification method and device Download PDFInfo
- Publication number
- CN104462448B CN104462448B CN201410779559.9A CN201410779559A CN104462448B CN 104462448 B CN104462448 B CN 104462448B CN 201410779559 A CN201410779559 A CN 201410779559A CN 104462448 B CN104462448 B CN 104462448B
- Authority
- CN
- China
- Prior art keywords
- packet name
- sorted
- packet
- name
- grouping
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/953—Querying, e.g. by the use of web search engines
- G06F16/9535—Search customisation based on user profiles and personalisation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/01—Social networking
Abstract
This application discloses a kind of packet name classification methods, may cause information inaccuracy recommended to the user according to packet mode in the prior art for solving the problems, such as.It specifically includes that and obtains packet name to be sorted；According to the feature for the perpetual object that the grouping that packet name to be sorted indicates is included, the characteristic value of packet name to be sorted is determined；According to the characteristic value of packet name to be sorted, treats classified packets name and classify.Also disclose a kind of packet name sorter.
Description
Technical field
This application involves field of computer technology more particularly to a kind of packet name classification method and devices.
Background technique
Packet name generally refers to: user in social networks according to oneself and perpetual object relationship, or it is right according to oneself
Perpetual object generates the reason of interest, after perpetual object is divided into different grouping, to be grouped the title taken.Since packet name is past
Toward the hobby and social networks that can embody individual subscriber, therefore packet name can be generally divided into two classifications, respectively
" relationship classification " and " category of interest ", the packet name in the two classifications are respectively grouping related with the social networks of user
Name, and packet name related with the hobby of user.
In the prior art, in order to user recommend related with the hobby of user information or with the social networks of user
Related information first has to determine the packet name generic that user is arranged on social networks, Jin Ergen by packet name semanteme
According to the category, recommend relevant information to user.Which has the disadvantage that for example for the grouping for being grouped entitled " colleague "
For, if the perpetual object in the grouping is all video display star, if that only with semanteme parse, may by " colleague " this
Packet name is directly divided into relationship classification, so as to cause according to category information inaccuracy recommended to the user.
Summary of the invention
The embodiment of the present application provides a kind of packet name classification method, to solve can according to packet mode in the prior art
It can lead to the problem of information inaccuracy recommended to the user.
The embodiment of the present application also provides a kind of packet name sorter, to solve according to packet mode in the prior art
It may cause the problem of information inaccuracy recommended to the user.
The embodiment of the present application adopts the following technical solutions:
A kind of packet name classification method, specifically includes that
Obtain packet name to be sorted；
According to the feature for the perpetual object that the grouping that the packet name to be sorted indicates is included, described to be sorted point is determined
The characteristic value of group name；
According to the characteristic value of the packet name to be sorted, classify to the packet name to be sorted.
A kind of packet name sorter, comprising:
Acquiring unit, for obtaining packet name to be sorted；
Determination unit, the feature for the perpetual object that the grouping for being indicated according to the packet name to be sorted is included, really
The characteristic value of the fixed packet name to be sorted；
Taxon classifies to the packet name to be sorted for the characteristic value according to the packet name to be sorted.
The embodiment of the present application use at least one above-mentioned technical solution can reach it is following the utility model has the advantages that
By the feature for the perpetual object that the grouping indicated thus according to packet name to be sorted is included, grouping to be sorted is determined
The characteristic value of name, and this feature value treats classified packets name and classifies, so that the pass that classification results and grouping are included
The feature of note object matches, and solves and determines packet name generic to be sorted with semanteme in the prior art, will lead to
The problem for the information inaccuracy that family is recommended.
Detailed description of the invention
The drawings described herein are used to provide a further understanding of the present application, constitutes part of this application, this Shen
Illustrative embodiments and their description please are not constituted an undue limitation on the present application for explaining the application.In the accompanying drawings:
Fig. 1 is a kind of flow chart of packet name classification method provided by the embodiments of the present application；
Fig. 2 treats the method flow that classified packets name is classified using decision-tree model to be provided by the embodiments of the present application
Figure；
Fig. 3 is a kind of structural block diagram of packet name sorter provided by the embodiments of the present application.
Specific embodiment
To keep the purposes, technical schemes and advantages of the application clearer, below in conjunction with the application specific embodiment and
Technical scheme is clearly and completely described in corresponding attached drawing.Obviously, described embodiment is only the application one
Section Example, instead of all the embodiments.Based on the embodiment in the application, those of ordinary skill in the art are not doing
Every other embodiment obtained under the premise of creative work out, shall fall in the protection scope of this application.
Below in conjunction with attached drawing, the technical scheme provided by various embodiments of the present application will be described in detail.
Embodiment 1
In order to solve the problems, such as to may cause information inaccuracy recommended to the user according to packet mode in the prior art,
The application proposes a kind of packet name classification method, and the implementation flow chart of this method is as shown in Figure 1, mainly include the following steps:
Step 11 obtains packet name to be sorted；
The feature of step 12, the perpetual object for being included according to the grouping that packet name to be sorted indicates, determines to be sorted point
The characteristic value of group name；
Step 13, according to the characteristic value of packet name to be sorted, treat classified packets name and classify.
Using the above method provided by the embodiments of the present application, by thus according to the grouping for getting packet name expression to be sorted
The feature for the perpetual object for being included determines the characteristic value of packet name to be sorted；And then according to the characteristic value pair of the packet name
Packet name to be sorted is classified, so that the feature for the perpetual object that classification results are included with grouping matches, is solved
Packet name generic to be sorted is determined with semanteme in the prior art, will lead to asking for information inaccuracy recommended to the user
Topic.
Optional embodiments some to the embodiment of the present application are described in detail below.
In one embodiment, in order to avoid before step 12, can will acquire by the interference of character lack of standardization
Packet name to be sorted is pre-processed.
Specifically, the frequency of available packet name to be sorted being used by a user；Then, extracting is made by user
It is greater than the packet name to be sorted of the default frequency with the frequency；Finally, the packet name to be sorted of extraction is carried out format normalization.Its
In, format normalization, can be by the complex form of Chinese characters be converted into simplified Chinese character, removal punctuation mark and/or upper case character be converted to small letter
Character etc..
In one embodiment, step 12 can be realized by following step A1- step A2:
Step A1, determine that at least one for having packet name to be sorted is grouped corresponding correlation degree value as perpetual object
Feature；
Step A2, according to correlation degree value, the characteristic value of packet name to be sorted is determined.
Wherein, each is grouped the perpetual object and this point is arranged that corresponding correlation degree value indicates that current group is included
Correlation degree between the user of group.
In the embodiment of the present application, step A2 can be, but not limited to following two implementation:
The first embodiment, step A2 can be illustrated by mathematic(al) representation shown in formula [1]:
Wherein, AVGfIndicate the characteristic value of packet name to be sorted；N indicates the sum that the user of the packet name to be sorted is arranged
Amount；I indicates Customs Assigned Number, and i ∈ [1, N]；CountiIt indicates to number and has this set by the user for being i and the user wait divide
The correlation degree value for the perpetual object that the grouping of class packet name includes.
It further illustrates for formula [1]: assuming that grouping entitled " junior middle school good friend " to be sorted, is arranged the user of the packet name
There are U1 and U2, wherein 100 people are had by the U1 perpetual object being divided into " junior middle school good friend " grouping, there are 50 people also same in this 100 people
When U1 is paid close attention to；U2, which is grouped included perpetual object " junior middle school good friend ", 30 people, has 20 people also same in this 30 people
When U2 is paid close attention to.It can then be determined by above-mentioned formula [1]:
N=2, Count1=50, Count2=20；And then the characteristic value of packet name to be sorted can be obtained by formula [1]
AVGf=35.
Second of embodiment: step A2 may include: by corresponding according to the correlation degree value for being greater than first threshold
Have the first grouping number of packet name to be sorted, and corresponding less than the correlation degree value of second threshold has to be sorted point
The second packet number of group name, determines the characteristic value of packet name to be sorted.Wherein, first threshold is greater than second threshold.
Specifically, the embodiment can shown in formula [2] mathematic(al) representation illustrate:
Wherein, Sub indicates the characteristic value of packet name to be sorted；High indicates that the correlation degree value for being greater than first threshold is corresponding
The first grouping number for having packet name to be sorted；Low represent less than second threshold correlation degree value it is corresponding have to
The second packet number of classified packets name.
For formula [2], further following citings are assumed:
Grouping entitled " six classes of the junior three " to be sorted, " machine learning " and " video display artist "；
Have the total number packets mesh of group name to be sorted as shown in following table one:
Table one:
| Packet name to be sorted | The total number packets mesh for having packet name to be sorted |
| Six classes of the junior three | 110 |
| Machine learning | 837 |
| Video display artist | 204 |
Further, it is assumed that correlation degree value is mutual powder rate；In addition, having " six classes of the junior three " this packet name to be sorted
In 110 groupings, mutual powder rate distribution is as shown in Table 2:
Table two:
Similarly, grouping entitled " machine learning " to be sorted as mutual powder rate distributional class shown in also available and table two
The mutual powder rate of " video display artist " is distributed, and the application does not repeat one by one herein.
Further, if assuming, first threshold is 60%, second threshold 30%, then by data in the right column of table two
Statistics, available: packet name " six classes of the junior three " to be sorted corresponding High=99, Low=0, and then can be according to formula
[2], Sub=100% is calculated.Similarly, other available packet names " machine learning " to be sorted and " video display artist "
Sub value.
Based on the Sub value determined, a kind of embodiment of step 13 may include:
According to Sub value, and the Sub threshold value of setting, packet name generic to be sorted is determined.
In one embodiment, which can be arranged according to sample packet name gathered in advance.For example assume:
To be grouped entitled " six classes of the junior three ", " friend relative ", " siblings " and " machine learning ", " video display are related ", " video display artist "
For the sample packet set constituted, if " six classes of the junior three " in the sample packet set, " friend relative ", " siblings "
Relation belonging to classification, and obtain " six classes of the junior three ", " friend relative ", " siblings " total number packets in grouping set
Accounting is 39.67%；" machine learning ", " video display are related " in the sample packet set, " video display artist " belong to category of interest,
And it obtains the accounting of " machine learning ", " video display correlation ", the total number packets of " video display artist " in grouping set and is
60.33%；So, it by the training of the sample packet name set, can determine when the Sub threshold value=20%, Neng Gouda
To best classifying quality.
Above-mentioned hypothesis content is specifically see following table three:
Table three:
Based on above-mentioned table three, after determining the Sub value of packet name to be sorted, if Sub > 20%, it is determined that be sorted
It is grouped entitled relation group, if Sub≤20%, it is determined that the entitled interest grouping of grouping to be sorted.
In one embodiment, step 12 can be realized by following step B1- step B3:
Step B1, the quantity of the user using packet name to be sorted is determined；
Step B2, feature of the quantity as packet name to be sorted that the perpetual object of the grouping is divided by user is obtained；
Step B3, according to the quantity of the quantity of user and perpetual object, the characteristic value of packet name to be sorted is determined.
In the embodiment of the present application, step B3 can be, but not limited to following two implementation:
The first implementation: step B3 can be illustrated by mathematic(al) representation shown in formula [3]:
Wherein, AVGuIndicate the characteristic value of packet name to be sorted；N indicates the sum that the user of the packet name to be sorted is arranged
Amount；J indicates Customs Assigned Number, and j ∈ [1, N]；CountjIndicate that the user for being numbered as j is divided into represented by packet name to be sorted
Grouping in perpetual object quantity.
It further illustrates for formula [3]: assuming that grouping entitled " famous person star " to be sorted, is arranged the user of the packet name
There are U1, U2, U3,100 people are had by the U1 perpetual object being divided into " famous person star " grouping, are divided into " famous person star " by U2 point
Perpetual object in group has 50 and has 30 by the U3 perpetual object being divided into " famous person star " grouping.Then by above-mentioned formula [3]
It can determine:
N=3, Count1=100, Count2=50, Count3=30, and then grouping to be sorted can be obtained by formula [3]
The characteristic value AVG of nameu=60.
Second of embodiment: step B3 may include: by obtain by user be divided into the grouping, have specific mark
The quantity of the perpetual object of knowledge is as grouping feature to be sorted.
Specifically, can be obtained if user U1 and U2 are the users with specific identifier:
N=2, Count1=100, Count2=50, and then by formula [3] available AVGu=50.
Based on the AVG determineduValue, a kind of embodiment of step 13 may include:
According to AVGuValue, and the AVG of settinguThreshold value determines packet name generic to be sorted.
In one embodiment, which can be arranged according to sample packet name gathered in advanceuThreshold value.Such as it is false
If: to be grouped entitled " information muffler ", " shop automobile 4s ", " law court colleague ", " which father goes ", " investment in gold " and " university
For the sample packet set that classmate " is constituted, if " information muffler " in the sample packet set, " shop automobile 4s ", " law court is same
Row " belong to category of interest, and obtain " information muffler ", " shop automobile 4s ", " law court colleague " total number packets in grouping set
Middle accounting is 38.25%, " which father goes ", " investment in gold " and " university classmate " relation belonging to class in the sample packet set
Not, it and obtains accounting of the total number packets of " which father goes ", " investment in gold " and " university classmate " in grouping set and is
61.75%, then, by the training of the sample packet name set, it can determine the AVGuThreshold value=1.
Above-mentioned hypothesis content is specifically see following table four:
Table four:
Based on above-mentioned table four, work as AVGuWhen > 1, determine that the entitled category of interest of grouping to be sorted i.e. accounting is 38.25%, when
AVGuWhen≤1, determine that i.e. accounting is not 61.75% to the entitled relation object of grouping to be sorted, but since formula [3] is not examined
Consider correlation degree between user and perpetual object, so formula [3] is not high to the fine granularity for obtaining packet name to be sorted, because
This, can by formula [3] obtained characteristic value in such a way that formula [2] obtained characteristic value is used in combination come to be sorted
The characteristic value of packet name is classified.
Described above is the several ways of the characteristic value of determining packet name to be sorted, introduced below a kind of according to determining
The method that characteristic value is classified:
Firstly, setting respectively obtains the feature of packet name to be sorted " colleague ", " famous person star " in the way of formula [2]
Value 10%, 60%, respectively as the First Eigenvalue of " colleague ", " famous person star "；It is arranged and is obtained respectively in the way of formula [3]
To the characteristic value 10,4 of packet name to be sorted, respectively as the Second Eigenvalue of " colleague ", " famous person star "；Setting utilizes formula
[1] mode respectively obtains the characteristic value 100,70 of packet name to be sorted, special respectively as the third of " colleague ", " famous person star "
Value indicative.
Then, it performs the following operations:
Using decision-tree model as shown in Figure 2, treats classified packets name and classify.Detailed process are as follows:
Whether the First Eigenvalue of judgement " colleague " is greater than 20%；After obtaining the judging result of "No", the second spy is judged
Whether value indicative is greater than 20；After the judging result for obtaining " Second Eigenvalue of colleague is not more than 20 ", judge that " colleague " belongs to
Relationship classification.
Whether the First Eigenvalue of judgement " famous person star " is greater than 20%；After obtaining the judging result of "Yes", is judged
[0,5) whether two characteristic values are in；After the judging result for obtaining " Second Eigenvalue be in [0,5) ", third feature value is judged
Whether in [0,90), after the judging result for obtaining " the third feature value of famous person star be in [0,90) ", judge " famous person
Star " belongs to category of interest.
It in one embodiment, can grouping determining packet name generic and then to classification is had determined that
Name carries out planningization processing.Concrete norm mode can be with are as follows: in such a way that part of speech filters, will determine the packet name of classification
It is divided into two parts, respectively planningization packet name and packet name to be modified.
Specifically, due to the packet name in category of interest, usually by relatively common noun, verb, adjective etc.
Composition, therefore white list mechanism can be used；And the other packet name of relation object, usually part of speech are inherently very complicated changeable, because
We use blacklist mechanism for this.Filtering rule can be as shown in following table three:
After completing the planningization processing of packet name, for each packet name to be modified, it can execute respectively: from planning
Change in packet name, determines that the feature of corresponding perpetual object is identical as the feature of the corresponding perpetual object of packet name to be modified
Planningization packet name, and then the packet name to be modified is revised as to the planningization packet name determined.
It should be noted that the executing subject of each step of 1 providing method of embodiment may each be same equipment, or
Person, this method is also by distinct device as executing subject.For example, the executing subject of step 11 and step 12 can be equipment 1, step
Rapid 13 executing subject can be equipment 2；For another example, the executing subject of step 11 can be equipment 1, step 12 and step 13
Executing subject can be equipment 2；Etc..
Embodiment 2
In order to solve the problems, such as to may cause information inaccuracy recommended to the user according to packet mode in the prior art,
The application proposes a kind of packet name sorter, the implementation flow chart of this method as shown in figure 3, specifically include that acquiring unit 31,
Determination unit 32 and taxon 33, specific as follows:
Acquiring unit 31, for obtaining packet name to be sorted；
Determination unit 32, the feature for the perpetual object that the grouping for being indicated according to packet name to be sorted is included determine
The characteristic value of the packet name to be sorted；
Taxon 33 treats classified packets name and classifies for the characteristic value according to packet name to be sorted.
In one embodiment, determination unit 32 are determined at least one point for having packet name to be sorted
The corresponding correlation degree value of group is as the feature；Wherein, each, which is grouped corresponding correlation degree value, indicates current group institute
Correlation degree between the perpetual object for including and the user that the grouping is set；According to correlation degree value, to be sorted point is determined
The characteristic value of group name.
In a kind of embodiment, determination unit 32 can be used for corresponding according to the correlation degree value for being greater than first threshold
First grouping number, and second packet number corresponding less than the correlation degree value of second threshold, determine grouping to be sorted
The characteristic value of name；Wherein, first threshold is greater than second threshold.
In one embodiment, determination unit 32 can be also used for the number for determining the user using packet name to be sorted
Amount；Obtain by user be divided into grouping perpetual object quantity as this feature；According to the quantity of user and perpetual object
Quantity determines the characteristic value of packet name to be sorted.
In one embodiment, determination unit 32, can be used for obtaining by user be divided into grouping, have specific mark
Feature of the quantity of the perpetual object of knowledge as packet name to be sorted.
Using device provided by above-described embodiment 2, by thus according to the grouping institute for getting packet name expression to be sorted
The feature for the perpetual object for including determines the characteristic value of packet name to be sorted；And then it is treated according to the characteristic value of the packet name
Classified packets name is classified.So that the feature for the perpetual object that classification results are included with grouping matches, and then solve
Packet mode in the prior art of having determined may cause the problem of information inaccuracy recommended to the user.
It should be understood by those skilled in the art that, the embodiment of the present invention can provide as method, system or computer program
Product.Therefore, complete hardware embodiment, complete software embodiment or reality combining software and hardware aspects can be used in the present invention
Apply the form of example.Moreover, it wherein includes the computer of computer usable program code that the present invention, which can be used in one or more,
The computer program implemented in usable storage medium (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.) produces
The form of product.
The present invention be referring to according to the method for the embodiment of the present invention, the process of equipment (system) and computer program product
Figure and/or block diagram describe.It should be understood that every one stream in flowchart and/or the block diagram can be realized by computer program instructions
The combination of process and/or box in journey and/or box and flowchart and/or the block diagram.It can provide these computer programs
Instruct the processor of general purpose computer, special purpose computer, Embedded Processor or other programmable data processing devices to produce
A raw machine, so that being generated by the instruction that computer or the processor of other programmable data processing devices execute for real
The device for the function of being specified in present one or more flows of the flowchart and/or one or more blocks of the block diagram.
These computer program instructions, which may also be stored in, is able to guide computer or other programmable data processing devices with spy
Determine in the computer-readable memory that mode works, so that it includes referring to that instruction stored in the computer readable memory, which generates,
Enable the manufacture of device, the command device realize in one box of one or more flows of the flowchart and/or block diagram or
The function of being specified in multiple boxes.
These computer program instructions also can be loaded onto a computer or other programmable data processing device, so that counting
Series of operation steps are executed on calculation machine or other programmable devices to generate computer implemented processing, thus in computer or
The instruction executed on other programmable devices is provided for realizing in one or more flows of the flowchart and/or block diagram one
The step of function of being specified in a box or multiple boxes.
In a typical configuration, calculating equipment includes one or more processors (CPU), input/output interface, net
Network interface and memory.
Memory may include the non-volatile memory in computer-readable medium, random access memory (RAM) and/or
The forms such as Nonvolatile memory, such as read-only memory (ROM) or flash memory (flash RAM).Memory is computer-readable medium
Example.
Computer-readable medium includes permanent and non-permanent, removable and non-removable media can be by any method
Or technology come realize information store.Information can be computer readable instructions, data structure, the module of program or other data.
The example of the storage medium of computer includes, but are not limited to phase change memory (PRAM), static random access memory (SRAM), moves
State random access memory (DRAM), other kinds of random access memory (RAM), read-only memory (ROM), electric erasable
Programmable read only memory (EEPROM), flash memory or other memory techniques, read-only disc read only memory (CD-ROM) (CD-ROM),
Digital versatile disc (DVD) or other optical storage, magnetic cassettes, tape magnetic disk storage or other magnetic storage devices
Or any other non-transmission medium, can be used for storage can be accessed by a computing device information.As defined in this article, it calculates
Machine readable medium does not include temporary computer readable media (transitory media), such as the data-signal and carrier wave of modulation.
It should also be noted that, the terms "include", "comprise" or its any other variant are intended to nonexcludability
It include so that the process, method, commodity or the equipment that include a series of elements not only include those elements, but also to wrap
Include other elements that are not explicitly listed, or further include for this process, method, commodity or equipment intrinsic want
Element.In the absence of more restrictions, the element limited by sentence "including a ...", it is not excluded that including described want
There is also other identical elements in the process, method of element, commodity or equipment.
It will be understood by those skilled in the art that embodiments herein can provide as method, system or computer program product.
Therefore, complete hardware embodiment, complete software embodiment or embodiment combining software and hardware aspects can be used in the application
Form.It is deposited moreover, the application can be used to can be used in the computer that one or more wherein includes computer usable program code
The shape for the computer program product implemented on storage media (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.)
Formula.
The above description is only an example of the present application, is not intended to limit this application.For those skilled in the art
For, various changes and changes are possible in this application.All any modifications made within the spirit and principles of the present application are equal
Replacement, improvement etc., should be included within the scope of the claims of this application.
Claims (10)
1. a kind of packet name classification method characterized by comprising
Obtain packet name to be sorted；
Acquired packet name to be sorted is pre-processed；
According to the feature for the perpetual object that the grouping that the packet name to be sorted indicates is included, the packet name to be sorted is determined
Characteristic value；
According to the characteristic value of the packet name to be sorted, classify to the packet name to be sorted；
To the packet name progress standardization processing for having determined that classification, the standardization processing includes: the side filtered by part of speech
The packet name for determining classification is divided into two parts by formula, respectively standardization packet name and packet name to be modified；
The packet name to be modified is executed: from the standardization packet name, determine corresponding perpetual object feature and
The identical standardization packet name of feature of the corresponding perpetual object of the packet name to be modified, and then by point to be modified
Group name is revised as the standardization packet name determined.
2. the method as described in claim 1, which is characterized in that included according to the grouping that the packet name to be sorted indicates
The feature of perpetual object determines the characteristic value of the packet name to be sorted, comprising:
Determine that at least one for having the packet name to be sorted is grouped corresponding correlation degree value as the feature；Wherein,
Each is grouped corresponding correlation degree value and indicates between the current group perpetual object for being included and the user that the grouping is arranged
Correlation degree；
According to the correlation degree value, the characteristic value of packet name to be sorted is determined.
3. method according to claim 2, which is characterized in that according to the correlation degree value, determine packet name to be sorted
Characteristic value, specifically include:
According to corresponding first grouping number of correlation degree value for being greater than first threshold, and the correlation degree less than second threshold
It is worth corresponding second packet number, determines the characteristic value of packet name to be sorted；
Wherein, first threshold is greater than second threshold.
4. the method as described in claim 1, which is characterized in that included according to the grouping that the packet name to be sorted indicates
The feature of perpetual object determines the characteristic value of the packet name to be sorted, comprising:
Determine the quantity of the user using the packet name to be sorted；
Obtain by the user be divided into the grouping perpetual object quantity as the feature；
According to the quantity of the quantity of the user and the perpetual object, the characteristic value of packet name to be sorted is determined.
5. method as claimed in claim 4, which is characterized in that obtain the perpetual object for being divided into the grouping by the user
Quantity as the feature, comprising:
The quantity of perpetual object that the grouping is divided by the user, having specific identifier is obtained as the feature.
6. a kind of packet name sorter characterized by comprising
Acquiring unit, for obtaining packet name to be sorted；
Determination unit, the feature for the perpetual object that the grouping for being indicated according to the packet name to be sorted is included, determines institute
State the characteristic value of packet name to be sorted；
Taxon classifies to the packet name to be sorted for the characteristic value according to the packet name to be sorted；
Wherein, the determination unit is also used to the concern for being included in the grouping indicated according to the packet name to be sorted
The feature of object before the characteristic value for determining the packet name to be sorted, pre-processes acquired packet name to be sorted；
The taxon is also used to the packet name progress standardization processing for having determined that classification, the standardization processing packet
Include: part of speech filter by way of, the packet name for determining classification is divided into two parts, respectively standardization packet name and
Packet name to be modified, and the packet name to be modified is executed: from the standardization packet name, determine corresponding pass
The identical standardization packet name of feature of the feature perpetual object corresponding with the packet name to be modified of object is infused, and then will
The packet name to be modified is revised as the standardization packet name determined.
7. device as claimed in claim 6, which is characterized in that the determination unit is specifically used for:
Determine that at least one for having the packet name to be sorted is grouped corresponding correlation degree value as the feature；Wherein,
Each is grouped corresponding correlation degree value and indicates between the current group perpetual object for being included and the user that the grouping is arranged
Correlation degree；
According to the correlation degree value, the characteristic value of packet name to be sorted is determined.
8. device as claimed in claim 7, which is characterized in that the determination unit is specifically used for:
According to corresponding first grouping number of correlation degree value for being greater than first threshold, and the correlation degree less than second threshold
It is worth corresponding second packet number, determines the characteristic value of packet name to be sorted；
Wherein, first threshold is greater than second threshold.
9. device as claimed in claim 6, which is characterized in that the determination unit is specifically used for:
Determine the quantity of the user using the packet name to be sorted；
Obtain by the user be divided into the grouping perpetual object quantity as the feature；
According to the quantity of the quantity of the user and the perpetual object, the characteristic value of packet name to be sorted is determined.
10. device as claimed in claim 9, which is characterized in that the determination unit is specifically used for:
The quantity of perpetual object that the grouping is divided by the user, having specific identifier is obtained as the feature.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410779559.9A CN104462448B (en) | 2014-12-15 | 2014-12-15 | A kind of packet name classification method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410779559.9A CN104462448B (en) | 2014-12-15 | 2014-12-15 | A kind of packet name classification method and device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN104462448A CN104462448A (en) | 2015-03-25 |
| CN104462448B true CN104462448B (en) | 2019-03-12 |
Family
ID=52908483
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201410779559.9A Active CN104462448B (en) | 2014-12-15 | 2014-12-15 | A kind of packet name classification method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN104462448B (en) |
Families Citing this family (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106354719B (en) * | 2015-07-13 | 2019-09-13 | 阿里巴巴集团控股有限公司 | POI service providing method, POI data processing method and processing device |
| CN107256231B (en) * | 2017-05-04 | 2022-04-22 | 腾讯科技（深圳）有限公司 | Team member identification device, method and system |
| JP2019159553A (en) * | 2018-03-09 | 2019-09-19 | 株式会社東芝 | Information processing apparatus, information processing method, and program |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101090346A (en) * | 2006-06-16 | 2007-12-19 | 腾讯科技（深圳）有限公司 | Group management method based on immediate communication and immediate communication customer end |
| CN102968430A (en) * | 2011-09-01 | 2013-03-13 | 三星电子株式会社 | Method and apparatus for automatically generating and managing groups in address book |
| CN103365947A (en) * | 2012-03-30 | 2013-10-23 | 卡西欧计算机株式会社 | Social network service system and image display method |
-
2014
- 2014-12-15 CN CN201410779559.9A patent/CN104462448B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101090346A (en) * | 2006-06-16 | 2007-12-19 | 腾讯科技（深圳）有限公司 | Group management method based on immediate communication and immediate communication customer end |
| CN102968430A (en) * | 2011-09-01 | 2013-03-13 | 三星电子株式会社 | Method and apparatus for automatically generating and managing groups in address book |
| CN103365947A (en) * | 2012-03-30 | 2013-10-23 | 卡西欧计算机株式会社 | Social network service system and image display method |
Non-Patent Citations (1)
| Title |
|---|
| 《可怕的圈子》;何菲;《IT经理世界》;20120420(第338期);30－32 |
Also Published As
| Publication number | Publication date |
|---|---|
| CN104462448A (en) | 2015-03-25 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105183731B (en) | Recommendation information generation method, device and system | |
| CN104035968B (en) | The construction method and device of training corpus collection based on social networks | |
| CN105095179B (en) | The method and device that user's evaluation is handled | |
| CN106951571A (en) | A kind of method and apparatus for giving application mark label | |
| CN108833139B (en) | OSSEC alarm data aggregation method based on category attribute division | |
| CN106803039B (en) | A kind of homologous determination method and device of malicious file | |
| CN110287313A (en) | A kind of the determination method and server of risk subject | |
| CN110134792A (en) | Text recognition method, device, electronic equipment and storage medium | |
| CN104462448B (en) | A kind of packet name classification method and device | |
| CN106598999A (en) | Method and device for calculating text theme membership degree | |
| CN106960040A (en) | A kind of URL classification determines method and device | |
| CN107679069A (en) | Method is found based on a kind of special group of news data and related commentary information | |
| CN104536663B (en) | A kind of page turning method | |
| CN108304509A (en) | A kind of comment spam filter method for indicating mutually to learn based on the multidirectional amount of text | |
| CN106897282B (en) | User group classification method and device | |
| CN104102662B (en) | A kind of user interest preference similarity determines method and device | |
| CN109918658A (en) | A kind of method and system obtaining target vocabulary from text | |
| CN103870541A (en) | Social network user interest mining method and system | |
| CN109902157A (en) | A kind of training sample validation checking method and device | |
| CN110263817B (en) | Risk grade classification method and device based on user account | |
| CN106897267A (en) | Article breviary text meaning generation method, device and server | |
| CN110472742A (en) | A kind of model variable determines method, device and equipment | |
| CN106844748A (en) | Text Clustering Method, device and electronic equipment | |
| CN108804676A (en) | A kind of model sort method, device, equipment and computer readable storage medium | |
| CN108076032B (en) | Abnormal behavior user identification method and device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |