CN105610640B - A kind of method and apparatus of internet information spreading path reduction - Google Patents
A kind of method and apparatus of internet information spreading path reduction Download PDFInfo
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- CN105610640B CN105610640B CN201510961957.7A CN201510961957A CN105610640B CN 105610640 B CN105610640 B CN 105610640B CN 201510961957 A CN201510961957 A CN 201510961957A CN 105610640 B CN105610640 B CN 105610640B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/10—Active monitoring, e.g. heartbeat, ping or trace-route
Abstract
The invention proposes a kind of method and apparatus of internet information spreading path reduction, the method for the internet information spreading path reduction includes: that whole sample attributes of sample data packet are carried out theme association, obtains theme relation integration；For theme relation integration, the theme association keyword for being unsatisfactory for the first setting condition to association probability is deleted, and the corresponding remaining theme association keyword of whole sample attributes of sample data packet and the sample attribute is formd core set；For all-network data packet collected in the period to be tested, the likelihood probability between each network packet and core set is calculated；The network packet for being unsatisfactory for the second setting condition to likelihood probability is deleted, and the network packet that likelihood probability meets the second setting condition is sequentially arranged and is shown.The present invention can help public security department to track down internet case, in clue collection and during tracing of information publisher, play a key effect.
Description
Technical field
A kind of method and dress restored the present invention relates to Internet technical field more particularly to internet information spreading path
It sets.
Background technique
With flourishing for internet, the fast propagation of the network information is expanding its influence power at an amazing speed.
Very different in numerous internet informations, many law-breakers are also by spreading network information disparate networks rumour and illegal
How information traces the route of transmission for restoring these flames, to grasp spreading network information approach and helps public security
Organ's locking suspicion account can play the role of vital.Currently, the method for solving the problems, such as such is concentrated mainly on and is based on
In two class method of probabilistic packet marking and data source tracing method in network packet.Above two method is more traditional, to internet
Information identification accuracy it is poor, discrimination is lower and recognition speed is slower, be not achieved it is rapid, accurately to an information carry out
The requirement that network is traced to the source.In addition, the above method also have the shortcomings that internet information can not be adapted to it is multifarious.
Summary of the invention
The technical problem to be solved by the present invention is to, a kind of method and apparatus of internet information spreading path reduction are provided,
It can quickly and accurately determine propagation path of the internet information in certain period of time, and show in chronological order.
The technical solution adopted by the present invention is that a kind of method of internet information spreading path reduction, comprising:
Step 1: whole sample attributes of sample data packet being subjected to theme association, obtain theme relation integration；The sample
Following four sample attribute: keyword, temporal information, information source and information publication account letter is included at least in notebook data packet
Breath；
Theme relation integration includes: each sample attribute pair of whole sample attributes of sample data packet, sample data packet
The theme association keyword and the corresponding keyword ID of theme association keyword and association probability answered；
Step 2: be directed to theme relation integration, to association probability be unsatisfactory for the first setting condition theme be associated with keyword into
Row is deleted, and the corresponding remaining theme of whole sample attributes of sample data packet and the sample attribute is associated with crucial morphology
At core set；
Step 3: for collected all-network data packet in the period to be tested, calculate each network packet with
Likelihood probability between core set；
Step 4: the network packet for being unsatisfactory for the second setting condition to likelihood probability is deleted, and likelihood probability is met
Second network packet to impose a condition is sequentially arranged and shows.
Further, the acquisition modes of the sample attribute of the sample data packet, specifically include:
Step A1: sample data packet is subjected to parcel decomposition；
Step A2: the sample data packet after parcel decomposes is subjected to restoring operation；
Step A3: by the data content of the sample data packet obtained after restoring operation according to different sample attribute classes
Type is divided, and each sample attribute of sample data packet is obtained.
Further, the step 1, specifically includes:
Step B1: theme library is loaded one by one, includes multiple themes association keyword, each theme association in a theme library
Keyword has corresponding keyword ID and association probability；Theme library and the sample attribute of sample data packet are matched, made
It is closed with sample attribute in the theme library that the meaning of theme association keyword and the meaning of sample attribute of winner's exam pool match
Connection；
Step B2: using the union in the theme library of each sample Attribute Association of sample data packet as theme relation integration.
Further, first setting condition includes: that the association probability of theme association keyword is greater than in advance in step 2
If association probability threshold value.
Further, the step 3, specifically includes:
Step C1: for collected all-network data packet in the period to be tested, all-network data packet is pressed into institute
The acquisition modes for stating the sample attribute of sample data packet obtain the attribute to be tested of each network packet；
Step C2: the attribute to be tested based on each network packet calculates each network packet and core set
Between likelihood probability.
Further, the step C2, specifically includes:
Step C21: by each sample attribute in each of network packet attribute to be tested and core set with
And the theme association keyword of each sample attribute is matched, if any sample category in the attribute to be tested and core set
Property or any sample attribute theme association Keywords matching on, then the attributes match to be tested success counts the network
The number of the attribute to be tested of successful match in data packet；
Step C22: the likelihood probability of the network packet is calculated according to following formula:
Sample in the number ÷ core set of the attribute to be tested of successful match in likelihood probability=network packet
The sum of attribute.
Further, second setting condition includes: the likelihood probability of network packet greater than preset in step 4
Likelihood probability threshold value.
The present invention also provides a kind of devices of internet information spreading path reduction, comprising:
Theme relating module obtains theme association for whole sample attributes of sample data packet to be carried out theme association
Set；Following four sample attribute: keyword, temporal information, information source and information is included at least in the sample data packet
Issue account information；Theme relation integration includes: each sample category of whole sample attributes of sample data packet, sample data packet
Property the corresponding theme association keyword and corresponding keyword ID of theme association keyword and association probability；
Core set forms module, for being directed to theme relation integration, is unsatisfactory for the first setting condition to association probability
Theme association keyword is deleted, and whole sample attributes of sample data packet and the sample attribute are corresponding remaining
Theme association keyword forms core set；
Likelihood probability computing module, for calculating for collected all-network data packet in the period to be tested
Likelihood probability between each network packet and core set；
Display module is filtered, the network packet for being unsatisfactory for the second setting condition to likelihood probability is deleted, will
Likelihood probability meets the network packet that second imposes a condition and is sequentially arranged and shows.
Further, the device of the internet information spreading path reduction, further includes:
Sample attribute obtains module, for sample data packet to be carried out parcel decomposition；By the sample after parcel decomposes
Data packet carries out restoring operation；By the data content of the sample data packet obtained after restoring operation according to different sample categories
Property type is divided, and each sample attribute of sample data packet is obtained.
By adopting the above technical scheme, the present invention at least has the advantage that
The method and apparatus of internet information spreading path reduction of the present invention, can be by internet sample number
It identifies according to the core attribute of packet, associated data of tracing to the source in the network packet of magnanimity packet, and by calculating likelihood probability, determines
The path of network packet.The present invention can be effectively solved the propagation path of internet information within a certain period of time, a side
Face can provide a kind of method that internet information is traced to the source, it is ensured that internet information spreading is traceable；On the other hand it can help
Internet case is tracked down by public security department, in clue collection and during tracing of information publisher, plays a key effect.
Detailed description of the invention
Fig. 1 is the internet information spreading path restoring method flow chart of first embodiment of the invention；
Fig. 2 is the flow chart of the step S1 of first embodiment of the invention；
Fig. 3 is the flow chart of the step S2 of first embodiment of the invention；
Fig. 4 is the flow chart of the step S3 of first embodiment of the invention；
Fig. 5 is the flow chart of the step S5 of first embodiment of the invention；
Fig. 6 is the composed structure schematic diagram of the internet information spreading path reduction apparatus of second embodiment of the invention.
Specific embodiment
Further to illustrate the present invention to reach the technical means and efficacy that predetermined purpose is taken, below in conjunction with attached drawing
And preferred embodiment, the present invention is described in detail as after.
First embodiment of the invention, a kind of method of internet information spreading path reduction, as shown in Figure 1, including following
Specific steps:
Step S1: user's input sample data packet will meet the sample category of the sample data packet of 1 basic demand of configuration file
Property is stored, and initial sample attribute set is formed；
Further, as shown in Fig. 2, the step S1 is specifically included:
Step S11: user's input sample data packet parses the sample data packet of input, obtains sample data packet
Sample attribute；
Further, the step S11 is specifically included:
Step S111: sample data packet is subjected to parcel decomposition；Preferably, sample data packet is subjected to 64 parcels point
Solution；
Step S112: the sample data packet after parcel decomposes is subjected to restoring operation；
Step S113: by the data content of the sample data packet obtained after restoring operation according to different sample attributes
Type is divided, and each sample attribute of sample data packet is obtained.
Step S12: configuration file 1 is read, the basic demand in configuration file 1 is loaded into memory storehouse；
Specifically, configuration file 1 requires to include necessary sample attribute in sample data packet；Necessity sample attribute packet
It includes: keyword, temporal information, information source type and information publication account information；
Step S13: judge whether the sample data packet meets the basic demand in configuration file 1:
If so, storing whole sample attributes of the sample data packet into tables of data A, initial sample attribute is formed
Set；
If it is not, then deleting the sample data packet, user inputs new sample data packet and re-execute the steps S1.
Step S2: the sample attribute in initial sample attribute set is subjected to theme association, obtains theme relation integration；It is main
Topic relation integration includes: whole sample attributes of initial sample attribute set, each sample category in initial sample attribute set
Property the corresponding theme association keyword and corresponding keyword ID of theme association keyword and association probability；
Further, as shown in figure 3, the step S2 is specifically included:
Step S21: the sample attribute in tables of data A is read into memory；
Step S22: theme library is loaded one by one, includes multiple themes association keyword, each theme pass in a theme library
Connection keyword has corresponding keyword ID and association probability；Theme library and the sample attribute of sample data packet are matched,
So that theme library and sample attribute that the meaning of theme association keyword and the meaning of sample attribute in theme library match carry out
Association；
Such as: this four themes of theme library Jingdone district Zhong You, Taobao, C2C and B2C are associated with keyword, a sample category
Property property content be online shopping, then the sample attribute and theme library are associated；
Step S23: it is closed the union in the theme library of each sample Attribute Association in initial sample attribute set as theme
Connection set, the content in theme relation integration is stored into tables of data B.
Step S3: the theme association keyword that association probability is unsatisfactory for 2 basic demand of configuration file is deleted, by sample
The corresponding remaining theme association keyword of the whole sample attributes and the sample attribute of notebook data packet forms core set；
Further, as shown in figure 4, the step S3 is specifically included:
Step S31: the corresponding keyword ID of each theme association keyword and the association probability in tables of data B are read；
Step S32: configuration file 2, preset association probability threshold value in loading configuration file 2 are read；
Step S33: judge whether the corresponding association probability of each theme association keyword in tables of data B is greater than configuration text
Preset association probability threshold value in part 2；
If so, retaining the theme association keyword；
If it is not, then being searched in tables of data B according to the keyword ID that the theme is associated with keyword, by the master
Topic association keyword carries out physics deletion；
Step S34: by tables of data B whole sample attributes and the associated remaining theme of the sample attribute close
Connection keyword is recorded in tables of data C, forms core set.
Step S4: for the all-network data packet in the period to be tested, each network packet and core are calculated
Likelihood probability between set；
Further, the step S4 is specifically included:
Step S41: the all-network data packet in the period to be tested is inputted, by all-network data packet according to step
The process of S11 is parsed, and the attribute to be tested of each network packet is obtained；
Step S42: the attribute to be tested based on each network packet calculates each network packet and core set
Between likelihood probability, and likelihood probability is recorded in sequence table, one sequence table of corresponding acquisition of a network packet.
Further, step S42 includes:
Step S421: by each sample attribute in each of network packet attribute to be tested and core set with
And the theme association keyword of each sample attribute is matched, if any sample category in the attribute to be tested and core set
Property or any sample attribute theme association Keywords matching on, then the attributes match to be tested success, and by the network
The ID of data packet and the Property ID to be tested of successful match are stored in tables of data D；In the network packet it is each matching at
The attribute to be tested of function will all form a tables of data D；
Step S422: total number of the tables of data formed in statistic procedure S421 matches in the as described network packet
The number of successful attribute to be tested, the ID of calculated result and the network packet is recorded in sequence table；
Step S423: calculating the likelihood probability of the network packet according to following formula, and by the network data
The likelihood probability of packet is recorded in the sequence table of step S422；
Sample in the number ÷ core set of the attribute to be tested of successful match in likelihood probability=network packet
The sum of attribute；
Step S5: the network packet that likelihood probability is unsatisfactory for 3 basic demand of configuration file is deleted, after deletion
Network packet be sequentially arranged and show.
Further, as shown in figure 5, the step S5 is specifically included:
Step S51: the sequence table of the all-network data packet in the period to be tested is read；
Step S52: configuration file 3, preset likelihood probability threshold value in loading configuration file 3 are read；
Step S53: likelihood probability in sequence table is greater than to the network data of preset likelihood probability threshold value in configuration file 3
The ID of packet is stored into tables of data E；
Step S54: corresponding network packet is found according to the ID of the network packet in tables of data E, according to the net
The temporal information of network data packet is ranked up, and loads different icons according to the information source type of the network packet,
Finally the icon of each network packet is shown in interface with the pattern of time shaft.
Second embodiment of the invention, the device for introducing a kind of internet information spreading path reduction corresponding with first, such as
Shown in Fig. 6, including consisting of part:
Sample attribute obtains module 101, for sample data packet to be carried out parcel decomposition；By the sample after parcel decomposes
Notebook data packet carries out restoring operation；By the data content of the sample data packet obtained after restoring operation according to different samples
Attribute type is divided, and each sample attribute of sample data packet is obtained.
Theme relating module 102 obtains theme pass for whole sample attributes of sample data packet to be carried out theme association
Connection set；Following four sample attribute: keyword, temporal information, information source and letter is included at least in the sample data packet
Breath publication account information；Theme relation integration includes: each sample of whole sample attributes of sample data packet, sample data packet
The corresponding theme association keyword of attribute and the corresponding keyword ID of theme association keyword and association probability；
Core set forms module 103, for being directed to theme relation integration, is unsatisfactory for the first setting condition to association probability
Theme association keyword deleted, by whole sample attributes of sample data packet and the corresponding residue of the sample attribute
Theme association keyword form core set；
Likelihood probability computing module 104, for calculating for collected all-network data packet in the period to be tested
Likelihood probability between each network packet and core set out；
Display module 105 is filtered, the network packet for being unsatisfactory for the second setting condition to likelihood probability is deleted,
The network packet that likelihood probability meets the second setting condition is sequentially arranged and is shown.
The method and apparatus for the internet information spreading path reduction introduced in the embodiment of the present invention, by sample attribute
The property content of sample attribute has been expanded in relating subject library, and matched accuracy can be improved.It, will in first embodiment of the invention
The calculated result of each step carries out individually storage into specified data table, convenient for the later period to the calling and calculating of data, shortens
Runing time.The likelihood probability calculation method used in the embodiment of the present invention, reduces calculation amount, shortens runing time.
The embodiment of the present invention can be effectively solved the propagation path of internet information within a certain period of time, on the one hand can provide one
The method that kind internet information is traced to the source, it is ensured that internet information spreading is traceable；On the other hand public security department can be helped to track down
Internet case plays a key effect in clue collection and during tracing of information publisher.
By the explanation of specific embodiment, the present invention can should be reached technological means that predetermined purpose is taken and
Effect is able to more deeply and specifically understand, however appended diagram is only to provide reference and description and is used, and is not used to this
Invention limits.
Claims (7)
1. a kind of method of internet information spreading path reduction characterized by comprising
Step 1: whole sample attributes of sample data packet being subjected to theme association, obtain theme relation integration；The sample number
According to including at least following four sample attribute in packet: keyword, temporal information, information source and information issue account information；
Theme relation integration includes: that whole sample attributes of sample data packet, each sample attribute of sample data packet are corresponding
Theme is associated with keyword and the corresponding keyword ID of theme association keyword and association probability；
Step 2: being directed to theme relation integration, the theme to association probability no more than preset association probability threshold value is associated with keyword
It is deleted, the corresponding remaining theme of whole sample attributes of sample data packet and the sample attribute is associated with keyword
Form core set；
Step 3: for collected all-network data packet in the period to be tested, calculating each network packet and core
Likelihood probability between set；
Step 4: the network packet to likelihood probability no more than preset likelihood probability threshold value is deleted, and likelihood probability is big
It is sequentially arranged and shows in the network packet of preset likelihood probability threshold value.
2. the method for internet information spreading path reduction according to claim 1, which is characterized in that the sample data
The acquisition modes of the sample attribute of packet, specifically include:
Step A1: sample data packet is subjected to parcel decomposition；
Step A2: the sample data packet after parcel decomposes is subjected to restoring operation；
Step A3: by the data content of the sample data packet obtained after restoring operation according to different sample attribute types into
Row divides, and obtains each sample attribute of sample data packet.
3. the method for internet information spreading path reduction according to claim 1, which is characterized in that the step 1, tool
Body includes:
Step B1: theme library is loaded one by one, includes multiple themes association keyword, each theme association key in a theme library
Word has corresponding keyword ID and association probability；Theme library and the sample attribute of sample data packet are matched, winner is made
The theme library that the meaning of theme association keyword and the meaning of sample attribute of exam pool match is associated with sample attribute；
Step B2: using the union in the theme library of each sample Attribute Association of sample data packet as theme relation integration.
4. the method for internet information spreading path reduction according to claim 2, which is characterized in that the step 3, tool
Body includes:
Step C1: for collected all-network data packet in the period to be tested, all-network data packet is pressed into the sample
The acquisition modes of the sample attribute of notebook data packet obtain the attribute to be tested of each network packet；
Step C2: the attribute to be tested based on each network packet calculates between each network packet and core set
Likelihood probability.
5. the method for internet information spreading path reduction according to claim 4, which is characterized in that the step C2,
It specifically includes:
Step C21: by each sample attribute in each of network packet attribute to be tested and core set and respectively
The theme association keyword of sample attribute is matched, if any sample attribute in the attribute to be tested and core set or
On the theme association Keywords matching of any sample attribute, then the attributes match success to be tested, counts the network data
The number of the attribute to be tested of successful match in packet；
Step C22: the likelihood probability of the network packet is calculated according to following formula:
Sample attribute in the number ÷ core set of the attribute to be tested of successful match in likelihood probability=network packet
Sum.
6. a kind of device of internet information spreading path reduction characterized by comprising
Theme relating module obtains theme relation integration for whole sample attributes of sample data packet to be carried out theme association；
Following four sample attribute is included at least in the sample data packet: keyword, temporal information, information source and information issue account
Family information；Theme relation integration includes: each sample attribute correspondence of whole sample attributes of sample data packet, sample data packet
Theme association keyword and the theme corresponding keyword ID of association keyword and association probability；
Core set forms module, for being directed to theme relation integration, is not more than preset association probability threshold value to association probability
Theme association keyword deleted, by whole sample attributes of sample data packet and the corresponding residue of the sample attribute
Theme association keyword form core set；
Likelihood probability computing module, for calculating each for collected all-network data packet in the period to be tested
Likelihood probability between network packet and core set；
Display module is filtered, is deleted for the network packet to likelihood probability no more than preset likelihood probability threshold value,
The network packet that likelihood probability is greater than preset likelihood probability threshold value is sequentially arranged and is shown.
7. the device of internet information spreading path reduction according to claim 6, which is characterized in that described device, also
Include:
Sample attribute obtains module, for sample data packet to be carried out parcel decomposition；By the sample data after parcel decomposes
Packet carries out restoring operation；By the data content of the sample data packet obtained after restoring operation according to different sample attribute classes
Type is divided, and each sample attribute of sample data packet is obtained.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101231641A (en) * | 2007-01-22 | 2008-07-30 | 北大方正集团有限公司 | Method and system for automatic analysis of hotspot subject propagation process in the internet |
| US8880521B2 (en) * | 2004-09-15 | 2014-11-04 | 3Degrees Llc | Collections of linked databases |
| CN104809253A (en) * | 2015-05-20 | 2015-07-29 | 成都布林特信息技术有限公司 | Internet data analysis system |
| CN104954236A (en) * | 2015-06-19 | 2015-09-30 | 百度在线网络技术（北京）有限公司 | Method and device for generating information of propagation path for theme event |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9276892B2 (en) * | 2011-11-29 | 2016-03-01 | Liquid Girds | Social dialogue listening, analytics, and engagement system and method |
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Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8880521B2 (en) * | 2004-09-15 | 2014-11-04 | 3Degrees Llc | Collections of linked databases |
| CN101231641A (en) * | 2007-01-22 | 2008-07-30 | 北大方正集团有限公司 | Method and system for automatic analysis of hotspot subject propagation process in the internet |
| CN104809253A (en) * | 2015-05-20 | 2015-07-29 | 成都布林特信息技术有限公司 | Internet data analysis system |
| CN104954236A (en) * | 2015-06-19 | 2015-09-30 | 百度在线网络技术（北京）有限公司 | Method and device for generating information of propagation path for theme event |
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