CN103166930B - The method and system of pushing network information - Google Patents
The method and system of pushing network information Download PDFInfo
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- CN103166930B CN103166930B CN201110421190.0A CN201110421190A CN103166930B CN 103166930 B CN103166930 B CN 103166930B CN 201110421190 A CN201110421190 A CN 201110421190A CN 103166930 B CN103166930 B CN 103166930B
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Abstract
A method for pushing network information, comprises the following steps: obtain the good friend in the friend relation chain of user and friend relation chain; Obtain the cohesion between described user and good friend; Obtain the business likability of the good friend of described user; The expectation likability of described user to Network is calculated according to described cohesion and described business likability; The network information relevant to described Network is pushed to described user according to described expectation likability.The method of above-mentioned pushing network information, can the potential demand of effective digging user, can improve the probability that user accepts the Network that the network information is recommended, thus improve the success rate of network information recommendation network business.A kind of system of pushing network information is provided in addition.
Description
[technical field]
The present invention relates to networking technology area, relate to a kind of method and system of pushing network information especially.
[background technology]
Along with the development of network technology and the growth of user's request, various Network emerges in an endless stream, and business development business pushes the network information relevant to Network by the Internet to user, propagates and promote Network with this.
The method of traditional pushing network information, when Network promoted by needs, then push the relevant network information of this Network with certain information format to the all-network user in certain territorial scope, and upgrade according to the cycle of presetting or frequency the network information pushed.
The method of traditional pushing network information, owing to pushing the relevant network information of Network according to regular time, fixing mode to user, its poor effect received, the probability that user accepts the Network that the network information is recommended is not high, and namely the success rate of network information recommendation network business is not high yet.
[summary of the invention]
Based on this, be necessary that providing a kind of can improve the method that the pushing network information of success rate is recommended in Network.
A method for pushing network information, comprises the following steps:
Obtain the good friend in the friend relation chain of user and friend relation chain;
Obtain the cohesion between described user and good friend;
Obtain the business likability of the good friend of described user;
The expectation likability of described user to Network is calculated according to described cohesion and described business likability;
The network information relevant to described Network is pushed to described user according to described expectation likability.
Preferably, the step of the cohesion between the described user of described acquisition and good friend comprises:
Obtain the network interaction record between user and good friend and/or personal information;
The cohesion between described user and good friend is calculated according to described network interaction record and/or personal information.
Preferably, the step of the business likability of the good friend of described acquisition user comprises:
Obtain the good friend of user to the operation note of Network;
The business likability of the good friend of user is calculated according to described operation note.
Preferably, described operation note comprises the combination of one or more in log-on message, read-write record, evaluation information.
Preferably, the described step pushing the network information relevant to described Network to described user according to described expectation likability comprises:
Network is sorted to the expectation likability order from high to low of Network according to described user;
The network information relevant to the Network of the forward predetermined number that sorts is pushed to described user.
Preferably, described method also comprises:
Obtain the feedback information of described user to the network information pushed;
Resequence according to the Network to be recommended of described feedback information to described user.
Based on this, there is a need to provide a kind of and can improve the system that the pushing network information of success rate is recommended in Network.
A system for pushing network information, comprising:
Good friend's acquisition module, the good friend in the friend relation chain that obtains user and friend relation chain;
Cohesion acquisition module, for obtaining the cohesion between described user and good friend;
Likability acquisition module, for obtaining the business likability of the good friend of described user;
Expect likability computing module, for calculating the expectation likability of described user to Network according to described cohesion and described business likability;
Info push module, for pushing the network information relevant to described Network according to described expectation likability to described user.
Preferably, described cohesion acquisition module comprises:
Cohesion relevant information acquisition module, for obtaining network interaction record between user and good friend and/or personal information;
Cohesion computing module, for calculating the cohesion between described user and good friend according to described network interaction record and/or personal information.
Preferably, described likability acquisition module comprises:
Operation note acquisition module, for obtaining the operation note of good friend to Network of user;
Likability computing module, for calculating the good friend of user to the likability of Network according to described operation note.
Preferably, described operation note comprises the combination of one or more in log-on message, read-write record, evaluation information.
Preferably, described info push module comprises:
Order module, for sorting Network to the expectation likability order from high to low of Network according to described user;
Pushing module, pushes the network information relevant to the Network of the forward predetermined number that sorts to described user.
Preferably, described system also comprises:
Feedback information acquisition module, for obtaining the feedback information of described user to the network information pushed;
Described order module is also for resequencing according to the Network to be recommended of described feedback information to described user.
The method and system of above-mentioned pushing network information, according to the business likability of the good friend of the cohesion between user and good friend and user, obtain the expectation likability of user to Network, and expect that likability pushes the network information relevant to Network to user according to this.Because the hobby between the user that cohesion is high is likely similar, if user good friend buddy-buddy is very high to the likability of certain Network, then this user also may be interested in this Network, so adopt aforesaid way to push the relevant network information of the interested Network of its good friend to user, can the potential demand of effective digging user, the probability that user accepts the Network that the network information is recommended can be improved, thus improve the success rate of network information recommendation network business.
[accompanying drawing explanation]
Fig. 1 is the schematic flow sheet of the method for pushing network information in an embodiment;
Fig. 2 is the schematic flow sheet of acquisition user in an embodiment and the cohesion between good friend;
Fig. 3 is the schematic flow sheet of the business likability of the good friend of acquisition user in an embodiment;
Fig. 4 is the schematic flow sheet pushing the network information relevant to Network according to expectation likability to user in an embodiment;
Fig. 5 is the interface schematic diagram of the network information to user's propelling movement in an embodiment;
Fig. 6 is the structural representation of the system of pushing network information in an embodiment;
Fig. 7 is the structural representation of the cohesion acquisition module in an embodiment;
Fig. 8 is the structural representation of the likability acquisition module in an embodiment;
Fig. 9 is the structural representation of the info push module in an embodiment;
Figure 10 is the structural representation of the system of pushed information in another embodiment.
[embodiment]
As shown in Figure 1, in one embodiment, a kind of method of pushing network information, comprises the following steps:
Step S10, obtains the good friend in the friend relation chain of user and friend relation chain.
In Web Community, user can set up friend relation with other users one or more, and namely other users being friend relation with user form the friend relation chain of user.The friend relation chain of user stores in a database with the form of the buddy list corresponding with user ID.In the present embodiment, the buddy list of user can be obtained by the friend relation chain obtaining user, obtain the good friend in the friend relation chain of user further.It should be noted that user and good friend are relative relations, the good friend of user is also user in Web Community.
Step S20, obtains the cohesion between user and good friend.
As shown in Figure 2, in one embodiment, step S20 comprises the following steps:
Step S202, obtains the network interaction record between user and good friend and/or personal information.
Concrete, network interaction record comprises the access of the instant messaging record of the request of the network information between user and good friend and response record, voice or word, intercommunication mail record and the network information and review record etc.Preferably, personal information comprises the information such as age, school, educational background, specialty, address, hobby of user.
Step S204, calculates the cohesion between user and good friend according to network interaction record and/or personal information.
In one embodiment, can according to the cohesion between the network interaction record calculating user between user and good friend and good friend.Concrete, can the network interaction frequency between counting user and good friend, mutual duration etc., and the cohesion arranged between user and good friend is the increasing function of its network interaction frequency and duration, the numerical value of the network interaction frequency namely between user and good friend, mutual duration is larger, then the cohesion between user and good friend is higher.
In one embodiment, cohesion between user and good friend can be calculated according to the personal information of the personal information of user and good friend.Concrete, can similarity between the personal information of counting user and the personal information of good friend, and the cohesion arranged between user and good friend is the increasing function of the similarity of the personal information of user and good friend.
In another embodiment, cohesion between user and good friend can be calculated according to the personal information of the personal information of the network interaction record between user and good friend and user and good friend.Concrete, can similarity between the personal information of the network interaction frequency between comprehensive statistics user and good friend and duration and user and the personal information of good friend, and the cohesion arranged between user and good friend is the increasing function of the network interaction frequency, duration and personal information similarity.
Preferably, in one embodiment, relation chain storehouse can be pre-set, after calculating the cohesion between user and good friend, this cohesion is stored in relation chain storehouse, and can relation chain storehouse be upgraded timing.
Step S30, obtains the business likability of the good friend of user.Concrete, the business likability of the good friend of user and the good friend of user are to the likability of Network.
As shown in Figure 3, in one embodiment, step S30 comprises the following steps:
Step S302, obtains the good friend of user to the operation note of Network.
Concrete, the operation of user to Network comprises registration operation, read operation and write operation.Such as, registration is operating as the operation that user registers some Networks, as submitted registration request to, filling registration information etc.; Read operation is the operation that the network information such as daily record, photograph album that user checks its good friend and delivers is carried out; Write operation then submits the operation of the network informations such as daily record, photograph album, comment to for user.Further, the good friend of user is obtained to the number of operations of Network and/or operation duration.
Step S304, calculates the business likability of the good friend of user according to aforesaid operations record.
Concrete, can according to the good friend of user to the good friend of the number of operations of Network and/or operation duration recording user to the likability of Network.Accordingly, if the good friend of user to the number of operations of Network and/or operation duration larger, then the business likability that can arrange the good friend of user is higher.
Preferably, in one embodiment, customer service storehouse can be pre-set, the business likability of the good friend of the user calculated is stored in customer service storehouse.As mentioned above, because user and good friend are relative relations, customer service storehouse actual storage be the business likability of all users.
Step S40, calculates user to the expectation likability of Network according to the business likability of the good friend of the cohesion between user and good friend and user.
Concrete, expect that likability is to the prediction index of user to the potential likability of Network.Because the hobby between more intimate good friend may be more similar, therefore, the expectation likability of user to Network can be calculated according to the business likability of user and the cohesion of good friend and the good friend of user; The business likability of good friend to Network of user is higher and user and this good friend cohesion is higher, then the expectation likability of user to this Network is higher.
Preferably, in one embodiment, the expectation likability of user to Network is calculated as follows:
Wherein, ExpectF
arepresent that user is to the expectation likability of Network a, friendNum represents good friend's number of user, C
irepresent the cohesion between user and its i-th good friend, F
airepresent that this i-th good friend is to the business likability of Network a.
In one embodiment, the user calculated can be stored to customer service storehouse, to upgrade customer service storehouse, and for calculating the expectation likability of user to Network next time to the expectation likability of Network as the business likability of user.
Step S50, pushes the network information relevant to Network according to above-mentioned expectation likability to user.
As shown in Figure 4, in one embodiment, step S50 comprises the following steps:
Step S502, sorts Network to the expectation likability order from high to low of Network according to user.
Step S504, pushes the network information relevant to the Network of the forward predetermined number of sequence to user.
In one embodiment, preset the network information relevant to Network, during pushing network information, then direct by the network information push that presets to user.In another embodiment, go back dynamic and the network information is set, the personal information of the good friend of user is joined in the network information and is pushed to user together.Such as, as shown in Figure 5, name Andy, Ben of the good friend of user are joined in the network information pushed to user.In the present embodiment, because the personal information of the good friend by user also joins in the network information, the attention rate of user can be improved further, thus improve the success rate that user accepts the Network that the network information is recommended further.
In one embodiment, in the network information relevant to Network of user's propelling movement, also can comprise the link information (as shown in Figure 5) of this Network.User directly clicks the page that this link just can enter into this Network, user friendly operation.
In an example, the method for above-mentioned pushing network information also comprises step: obtain the feedback information of user to the network information pushed, resequence according to the Network to be recommended of feedback information to user.
Concrete, the broadcasting frequency of the network information, user can be obtained to the clicking rate of the network information, and user is to the operation note of the Network that the network information is correlated with, if user is to the registration, login record, Visitor Logs, write operation record etc. of Network.
In one embodiment, if the broadcasting frequency of the network information exceedes default threshold value, the Network then this network information can be correlated with is discharged in the Network queue to be recommended of user backward, because if continue again to push the relevant network information of this Network to user, then may cause invasion to user.Accordingly, if the Network that user is relevant to the network information pushed adds operation note, as registration, login or access etc., then also this Network can be discharged in the Network queue to be recommended of user backward, because the Network that the network information pushed successfully has made user receive this network information recommends, then the relevant information of this Network can push to user after some cycles again.
The method of above-mentioned pushing network information, by according to user to the feedback information of the network information pushed, resequence to user's Network to be recommended, the renewable network information relevant to Network pushed to user, thus can further improve the success rate pushing the Network relevant to the network information, and reduce the invasion to user.
As shown in Figure 6, a kind of system of pushing network information, comprises good friend's acquisition module 100, cohesion acquisition module 200, likability acquisition module 300, expects likability computing module 400, info push module 500, wherein:
Good friend's acquisition module 100, the good friend in the friend relation chain that obtains user and friend relation chain.
In Web Community, user can set up friend relation with other users one or more, and namely other users being friend relation with user form the friend relation chain of user.The friend relation chain of user stores in a database with the form of the buddy list corresponding with user ID.In the present embodiment, good friend's acquisition module 100 can obtain the buddy list of user for the friend relation chain by obtaining user, obtains the good friend in the friend relation chain of user further.It should be noted that user and good friend are relative relations, the good friend of user is also user in Web Community.
Cohesion acquisition module 200, for obtaining the cohesion between user and good friend.
As shown in Figure 7, in one embodiment, cohesion acquisition module 200 comprises cohesion relevant information acquisition module 202, cohesion computing module 204, wherein:
Cohesion relevant information acquisition module 202, for obtaining network interaction record between user and good friend and/or personal information.
Concrete, network interaction record comprises the access of the instant messaging record of the request of the network information between user and good friend and response record, voice or word, intercommunication mail record and the network information and review record etc.Preferably, personal information comprises the information such as age, school, educational background, specialty, address, hobby of user.
Cohesion computing module 204, for calculating the cohesion between user and good friend according to network interaction record and/or personal information.
In one embodiment, cohesion computing module 204 can be used for according to the cohesion between the network interaction record calculating user between user and good friend and good friend.Concrete, cohesion computing module 204 can the network interaction frequency, mutual duration etc. between counting user and good friend, and the cohesion arranged between user and good friend is the increasing function of its network interaction frequency and duration.
In one embodiment, cohesion computing module 204 can be used for calculating cohesion between user and good friend according to the personal information of user and the personal information of good friend.Concrete, cohesion computing module 204 can be used for the similarity between the personal information of counting user and the personal information of good friend, and the cohesion arranged between user and good friend is the increasing function of the similarity of the personal information of user and good friend.
In another embodiment, cohesion computing module 204 can be used for calculating cohesion between user and good friend according to the network interaction record between user and good friend and the personal information of user and the personal information of good friend.Concrete, cohesion computing module 204 can be used for the similarity between the personal information of the network interaction frequency between comprehensive statistics user and good friend and duration and user and the personal information of good friend, and the cohesion arranged between user and good friend is the increasing function of the network interaction frequency, duration and personal information similarity.
Preferably, in one embodiment, relation chain storehouse (not shown) can be pre-set, after calculating the cohesion between user and good friend, this cohesion is stored in relation chain storehouse, and can relation chain storehouse be upgraded timing.
Likability acquisition module 300, for obtaining the business likability of the good friend of user.Concrete, the business likability of the good friend of user and the good friend of user are to the likability of Network.
As shown in Figure 8, in one embodiment, likability acquisition module 300 comprises operation note acquisition module 302, likability computing module 304, wherein:
Operation note acquisition module 302, for obtaining the operation note of good friend to Network of user.
Concrete, the operation of user to Network comprises registration operation, read operation and write operation.Such as, registration is operating as the operation that user registers some Networks, as submitted registration request to, filling registration information etc.; Read operation is the operation that the network information such as daily record, photograph album that user checks its good friend and delivers is carried out; Write operation then submits the operation of the network informations such as daily record, photograph album, comment to for user.Further, operation note acquisition module 302 can obtain the good friend of user to the number of operations of Network and/or operation duration.
Likability computing module 304, for calculating the business likability of the good friend of user according to aforesaid operations record.
Concrete, likability computing module 304 can according to the good friend of user to the good friend of the number of operations of Network and/or operation duration recording user to the likability of Network.Accordingly, if the good friend of user to the number of operations of Network and/or operation duration larger, then the business likability that can arrange the good friend of user is higher.
Preferably, in one embodiment, customer service storehouse (not shown) can be pre-set, the business likability of the good friend of the user calculated is stored in customer service storehouse.As mentioned above, because user and good friend are relative relations, customer service storehouse actual storage be the business likability of all users.
Expect likability computing module 400, the business likability for the good friend according to the cohesion between user and good friend and user calculates user to the expectation likability of Network.
Concrete, expect that likability is to the prediction index of user to the potential likability of Network.Because the hobby between more intimate good friend may be more similar, therefore, expect that likability computing module 400 can be used for calculating the expectation likability of user to Network according to the business likability of user and the cohesion of good friend and the good friend of user; The business likability of good friend to Network of user is higher and user and this good friend cohesion is higher, then can to arrange the expectation likability of user to this Network also higher for likability computing module 304.
Preferably, in one embodiment, expect that likability computing module 400 is for being calculated as follows the expectation likability of user to Network:
Wherein, ExpecF
arepresent that user is to the expectation likability of Network a, friendNum represents good friend's number of user, C
irepresent the cohesion between user and its i-th good friend, F
airepresent that this i-th good friend is to the business likability of Network a.
In one embodiment, expect that likability computing module 400 can be used for the user calculated to be stored to customer service storehouse to the expectation likability of Network as the business likability of user, to upgrade customer service storehouse, and for calculating the expectation likability of user to Network next time.
Info push module 500, for pushing the network information relevant to Network according to expectation likability to user.
As shown in Figure 9, in one embodiment, info push module 500 comprises order module 502, pushing module 504, wherein:
Order module 502, for sorting Network to the expectation likability order from high to low of Network according to user.
Pushing module 504, for pushing the network information relevant to the Network of the forward predetermined number of sequence to user.
In one embodiment, pushing module 504 can be used for presetting the network information relevant to Network, during pushing network information, then direct by the network information push that presets to user.In another embodiment, pushing module 504 also can be used for dynamically arranging the network information, the personal information of the good friend of user is joined in the network information and is pushed to user together.Such as, as shown in Figure 5, name Andy, Ben of the good friend of user are joined in the network information pushed to user.In the present embodiment, because the personal information of the good friend by user also joins in the network information, the attention rate of user can be improved further, thus improve the success rate that user accepts the Network that the network information is recommended further.
In one embodiment, in the network information relevant to Network of user's propelling movement, also can comprise the link information (as shown in Figure 5) of this Network.User directly clicks the page that this link just can enter into this Network, user friendly operation.
As shown in Figure 10, in one embodiment, the system of above-mentioned pushed information also comprises:
Feedback information acquisition module 600, for obtaining the feedback information of user to the network information pushed.
Concrete, feedback information acquisition module 600 can obtain the broadcasting frequency of the network information, user to the clicking rate of the network information, and user is to the operation note of the Network that the network information is correlated with, if user is to the registration, login record, Visitor Logs, write operation record etc. of Network.
In the present embodiment, order module 502 is also for resequencing according to the Network to be recommended of above-mentioned feedback information to user.
In one embodiment, if the broadcasting frequency of the network information exceedes default threshold value, the Network that then this network information can be correlated with by order module 502 is discharged in the Network queue to be recommended of user backward, because if continue again to push the relevant network information of this Network to user, then may cause invasion to user.Accordingly, if the Network that user is relevant to the network information pushed adds operation note, as registration, login or access etc., then this Network also can be discharged by order module 502 in the Network queue to be recommended of user backward, because the Network that the network information pushed successfully has made user receive this network information recommends, then the relevant information of this Network can push to user after some cycles again.
The system of above-mentioned pushing network information, by according to user to the feedback information of the network information pushed, resequence to user's Network to be recommended, the renewable network information relevant to Network pushed to user, thus can further improve the success rate pushing the Network relevant to the network information, and reduce the invasion to user.
The method and system of above-mentioned pushing network information, according to the business likability of the good friend of the cohesion between user and good friend and user, obtain the expectation likability of user to Network, and expect that likability pushes the network information relevant to Network to user according to this.Because the hobby between the user that cohesion is high is likely similar, if user good friend buddy-buddy is very high to the likability of certain Network, then this user also may be interested in this Network, so adopt aforesaid way to push the relevant network information of the interested Network of its good friend to user, can the potential demand of effective digging user, the probability that user accepts the Network that the network information is recommended can be improved, thus improve the success rate of network information recommendation network business.
The above embodiment only have expressed several execution mode of the present invention, and it describes comparatively concrete and detailed, but therefore can not be interpreted as the restriction to the scope of the claims of the present invention.It should be pointed out that for the person of ordinary skill of the art, without departing from the inventive concept of the premise, can also make some distortion and improvement, these all belong to protection scope of the present invention.Therefore, the protection range of patent of the present invention should be as the criterion with claims.
Claims (10)
1. a method for pushing network information, comprises the following steps:
Obtain the good friend in the friend relation chain of user and friend relation chain;
Obtain the network interaction record between described user and good friend;
The cohesion between described user and good friend is calculated according to described network interaction record;
Obtain the good friend of user to the operation note of Network;
The business likability of the good friend of user is calculated according to described operation note;
The expectation likability of described user to Network is calculated according to described cohesion and described business likability; The business likability of good friend to described Network of described user is higher and described user and this good friend cohesion is higher, then the expectation likability of described user to described Network is higher;
The network information relevant to described Network is pushed to described user according to described expectation likability.
2. the method for pushing network information according to claim 1, is characterized in that, described calculate the step of the cohesion between described user and good friend according to described network interaction record before also comprise:
Obtain the personal information of user and good friend;
Describedly calculate cohesion between described user and good friend according to described network interaction record, comprising:
The cohesion between described user and good friend is calculated according to described network interaction record and personal information.
3. the method for pushing network information according to claim 1, is characterized in that, described operation note comprises the combination of one or more in log-on message, read-write record, evaluation information.
4. the method for pushing network information as claimed in any of claims 1 to 3, is characterized in that, the described step pushing the network information relevant to described Network to described user according to described expectation likability comprises:
Network is sorted to the expectation likability order from high to low of Network according to described user;
The network information relevant to the Network of the forward predetermined number that sorts is pushed to described user.
5. the method for pushing network information according to claim 4, is characterized in that, described method also comprises:
Obtain the feedback information of described user to the network information pushed;
Resequence according to the Network to be recommended of described feedback information to described user.
6. a system for pushing network information, is characterized in that, comprising:
Good friend's acquisition module, the good friend in the friend relation chain that obtains user and friend relation chain;
Cohesion relevant information acquisition module, for obtaining the network interaction record between user and good friend;
Cohesion computing module, for calculating the cohesion between described user and good friend according to described network interaction record;
Operation note acquisition module, for obtaining the operation note of good friend to Network of user;
Likability computing module, for calculating the business likability of the good friend of user according to described operation note;
Expect likability computing module, for calculating the expectation likability of described user to Network according to described cohesion and described business likability; The business likability of good friend to described Network of described user is higher and described user and this good friend cohesion is higher, then the expectation likability of described user to described Network is higher;
Info push module, for pushing the network information relevant to described Network according to described expectation likability to described user.
7. the system of pushing network information according to claim 6, is characterized in that, described cohesion relevant information acquisition module is also for obtaining the personal information of user and good friend;
Described cohesion computing module is also for calculating the cohesion between described user and good friend according to described network interaction record and personal information.
8. the system of pushing network information according to claim 6, is characterized in that, described operation note comprises the combination of one or more in log-on message, read-write record, evaluation information.
9. according to the system of the pushing network information in claim 6 to 8 described in any one, it is characterized in that, described info push module comprises:
Order module, for sorting Network to the expectation likability order from high to low of Network according to described user;
Pushing module, pushes the network information relevant to the Network of the forward predetermined number that sorts to described user.
10. the system of pushing network information according to claim 9, is characterized in that, described system also comprises:
Feedback information acquisition module, for obtaining the feedback information of described user to the network information pushed;
Described order module is also for resequencing according to the Network to be recommended of described feedback information to described user.
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