CN107153659A - A kind of recommendation method and commending system applied to social networks - Google Patents
A kind of recommendation method and commending system applied to social networks Download PDFInfo
- Publication number
- CN107153659A CN107153659A CN201610123752.6A CN201610123752A CN107153659A CN 107153659 A CN107153659 A CN 107153659A CN 201610123752 A CN201610123752 A CN 201610123752A CN 107153659 A CN107153659 A CN 107153659A
- Authority
- CN
- China
- Prior art keywords
- targeted customer
- recommendation method
- module
- user
- commending system
- 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.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 26
- 239000000284 extract Substances 0.000 claims abstract description 5
- 238000000605 extraction Methods 0.000 claims description 14
- 230000003993 interaction Effects 0.000 claims description 6
- 230000002452 interceptive effect Effects 0.000 claims description 4
- 230000005236 sound signal Effects 0.000 claims description 2
- 230000015572 biosynthetic process Effects 0.000 claims 1
- 230000004044 response Effects 0.000 abstract description 12
- 230000000694 effects Effects 0.000 description 5
- 230000006399 behavior Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 230000011273 social behavior Effects 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
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
- G06F16/958—Organisation or management of web site content, e.g. publishing, maintaining pages or automatic linking
-
- 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—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/01—Social networking
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Databases & Information Systems (AREA)
- Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Physics & Mathematics (AREA)
- Primary Health Care (AREA)
- Marketing (AREA)
- Human Resources & Organizations (AREA)
- Strategic Management (AREA)
- Tourism & Hospitality (AREA)
- General Health & Medical Sciences (AREA)
- General Business, Economics & Management (AREA)
- Economics (AREA)
- Health & Medical Sciences (AREA)
- Computing Systems (AREA)
- Data Mining & Analysis (AREA)
- General Engineering & Computer Science (AREA)
- Collating Specific Patterns (AREA)
Abstract
The present invention discloses a kind of recommendation method applied to social networks, it is characterised in that：S1 targeted customers extract external environment condition oracle as input information, S2 in the social networks user input information cluster, formed clustering cluster user be can recommended user, S3 recommend described in can recommended user to targeted customer.Using the recommendation method of this spline structure, be conducive to setting up strange social networks between the people using same oracle, this oracle can be Quick Response Code can also be someone fingerprint, invention further discloses a kind of corresponding commending system.
Description
Technical field：
The present invention relates to a kind of recommendation method and commending system applied to social networks, especially
The consumer's friend-making recommendation method and commending system of a kind of like product.
Background technology：
Now with many social contact methods, but major part belongs to the social activity originated between acquaintance
It is acquaintance on line that method, which is only that acquaintance shifts under line, therefore has no idea to be had
The stranger of common hobby makes friends, although such as footpath between fields footpath between fields that some geographical position are made friends and
The wechat of friend-making is shaken, but randomness is again too strong, lacks certain common experience or fixed
To contact.
The present invention is to have common interest hobby, common shopping or the guarantee of some personal credit
Stranger's social recommendation method and commending system.
The content of the invention：
The present invention discloses a kind of recommendation method applied to social networks, it is characterised in that：S1
Targeted customer extracts the oracle of external environment condition as input information, and S2 is to the social activity
User's input information in network is clustered, and the user for forming clustering cluster is that can recommend to use
Family, S3 recommend it is described can recommended user to targeted customer.Also corresponding commending system.
Using the recommendation method of this spline structure, be conducive between the people using same oracle
Set up strange social networks, this oracle can be public arenas, cinema, chain
The wireless base station apparatus in hotel etc. or the Quick Response Code of company, product Quick Response Code etc., such as
Really the external information is biological information such as fingerprint, palmmprint, face or the iris of someone,
Social intercourse system then can be set up around the personal credit.
Brief description of the drawings：
Fig. 1 is the recommendation method of the present invention with recommending system logic chart
Embodiment：
As shown in figure 1, a kind of recommendation method applied to social networks, it is characterised in that：S1
Targeted customer extracts the oracle of external environment condition as input information, and S2 is to the social activity
User's input information in network is clustered, and the user for forming clustering cluster is that can recommend to use
Family, S3 recommend it is described can recommended user to targeted customer.Using the recommendation method of this spline structure,
Be conducive to setting up strange social networks, this outside letter between the people using same oracle
Breath source can be the two dimension of public arenas, the wireless base station apparatus of cinema or company
Code, product Quick Response Code etc., if the external information be the fingerprint of someone, palmmprint, face or
Person's iris, then can set up social intercourse system around the individual.
Passable preferential improvement is：The oracle be bar code or two microcodes or
Other visible ray block letter.This is that most widely used scene of the invention, price are cheapest, such as
Because liking some luxury goods brand jointly, these luxury goods buyer can priority different location
The bar code or Quick Response Code of the common scan luxury goods, so that these priority different times are bought
Consumer be clustered, at least targeted customer be known that before this how many people to have purchased this same
Class product, visible ray block letter herein can also be electronic curtain shape in addition to paper media is situated between certainly
Into bar code or Quick Response Code or other patterns.
Passable preferential improvement is：The oracle is sound signal.It is such to change
Enter to be applied to make friends with the cluster of a word or same section of melody.
Passable preferential improvement is：The external information be biological image fingerprint, palmmprint,
Face, iris etc..This is more than general Quick Response Code progress, because Quick Response Code after all can be with
Stealthily scanned by people, and the personal biometric identification indicia of hotel owner such as fingerprint, palmmprint, face,
Iris etc. can just be obtained after having to wait for payment, and the guarantee of this personal property may insure social activity
The reliability of group friend is substantially improved.
Passable preferential improvement is：Between the S2 and S3, also S21 notifications
Advertising message, targeted customer, which must receive notifications advertising message, could enter S3.One society
Hand over the inevitable expense of maintenance of group's system, thus targeted customer obtain Hierarchical Clustering result it
It is preceding receive notifications advertisement be it is a kind of be beneficial to the way of system, if targeted customer refusal system
System notifies question and answer, then Social behaviors are terminated.
Passable preferential improvement is：Between the S1 and S3, also S22 checking targets
Subscriber identity information, targeted customer, which must receive system identity checking, could enter S3.It is such
Checking is to ensure that people computer system, prevents hand-set from stolen from using and causing privacy leakage problem.
Passable preferential improvement is：Between the S1 and S3, also S23 counts identical
The oracle typing number of times, record control outside the fixed length time cycle or fixed length space away from
From the typing number of times of the outer identical oracle.Such improvement is advantageous for hotel owner's system
Count the true consumption number of times of the consumer, especially hotel and attract the preferential of Double Spending
Improve.
Passable preferential improvement is：, can recommended user described in also S4 after the S3
It is interactive with targeted customer.So social intercourse system not only tells what your how many people existed in the system
Static data, and interactive real friend-making further can be directly contacted between them.
Passable preferential improvement is：Between the S3 and S4, also S31 notifications
Advertising message, targeted customer, which must receive notifications advertising message, could enter S4.Increase system
System income is to improve system operation, if refusal advertisement, friend-making behavior is terminated.
Recommend system present invention additionally comprises corresponding with social contact method, one kind is applied to social networks
Commending system, its improvement is, including：
Extraction module T1, extracts the information that the targeted customer is derived from external environment condition.
Cluster module T2, for being clustered to the user in the social networks, forms poly-
Class cluster, the user for constituting clustering cluster is can recommended user.
Recommending module T3, for by it is described can recommended user recommend the targeted customer.
It is such improve provide obtained by common oracle include product, service,
The subsidiary oracle of human body carries out social method.
Passable preferential improvement is：The extraction module is optics barcode scanning device.It is such
Improvement is most popular, almost can be used in streets and lanes.Such as cinema, theater,
The Quick Response Code in hotel can cluster the people of common hobby, such as certain product BMW, benz
Quick Response Code can be clustered as automobile friend club, and leakage can be used if multiple Quick Response Codes are inputted simultaneously
Struggle against model discrimination mode, can reach in theory final 1 can recommended user to 1 targeted customer
Accurate social intercourse system.
Passable preferential improvement is：The extraction module is sound extraction module.It is such
Improvement facilitates the friend-making between same a word or the friend-making of same section of melody.
Passable preferential improvement is：The extraction module is biological image extraction element, is used
In taking the fingerprint, palmmprint, face, iris.Such improvement adds personal credit guarantee,
Compared to simple Quick Response Code, biological information individual fingerprint, palmmprint etc. can not almost be forged, greatly
The big reliability for improving social group, while using the fingerprint of same person, palmmprint as the society clustered
Hand over to have and property is can contact under great line, be particularly suitable for use in star's social group, or some is necessary
The service dealer's social group contacted face-to-face, it is the ideal of social organizer to realize everybody, i.e.,
It is mute even blind person to make him.
Passable preferential improvement is：Also have between T2 and T3 and notify advertisement module T21,
For advertising message will to be notified to be sent to targeted customer.I.e. targeted customer obtain recommended user it
It is preceding to receive the notice class or advertisement category information of system, so as to allow system to be in the black chance.
Passable preferential improvement is：There is targeted customer's authentication mould between T2 and T3
Block T22, for verifying targeted customer's identity information.Such checking can protect targeted customer
Privacy, prevent hand-set from stolen use or identity it is spoofed.
Passable preferential improvement is：There is counting module T23 between T2 and T3, be used for
The record of the identical oracle is recorded outside the fixed length time cycle or outside fixed length space length
Indegree.Such improve is lived similar hotel suitable for same targeted customer during travelling
Statistics, be conducive to improve service trade to same consumer according to the preferential of its consumption quantity.
Passable preferential improvement is：The extraction module T1, cluster module T2, recommendation
After module T3, also user interaction module T4, for it is described can recommended user and target use
It is interactive between family.Direct communication between consumer is real social activity.
Passable preferential improvement is：Also have between the T3 and T4 and notify advertisement module
T31, sends with receiving for the notice advertising message that they are got in touch with before interaction.I.e. target is used
Family before recommended user's contact interaction with that can must receive the notice class or commercial paper letter of system
Breath, so as to allow system to be in the black again chance.
The present invention is not limited to above-mentioned preferred forms, and anyone can opening in the present invention
The product of other forms is made under showing, no matter but what change its method or system have, it is any
The technical scheme similar with the present invention each falls within protection scope of the present invention.
Claims (18)
1. a kind of recommendation method applied to social networks, it is characterised in that：S1 targeted customers
The oracle of external environment condition is extracted as input information, S2 is in the social networks
User input information clustered, formation clustering cluster user be can recommended user,
S3 recommend it is described can recommended user to targeted customer.
2. a kind of recommendation method as claimed in claim 1, it is characterised in that：The outside letter
Breath source is bar code or two microcodes or other visible ray block letter.
3. a kind of recommendation method as claimed in claim 1, it is characterised in that：The outside letter
Breath source is sound signal.
4. a kind of recommendation method as claimed in claim 1, it is characterised in that：The outside
Information is biological image fingerprint, palmmprint, face, iris etc..
5. a kind of recommendation method as claimed in claim 1 or 2 or 3 or 4, it is characterised in that：
Between the S2 and S3, also S21 notifications advertising message, targeted customer must connect
It could be entered S3 by notifications advertising message.
6. a kind of recommendation method as claimed in claim 1 or 2 or 3 or 4, it is characterised in that：
Between the S1 and S3, also S22 checking targeted customer's identity informations, targeted customer
System identity checking, which must be received, could enter S3.
7. a kind of recommendation method as claimed in claim 1 or 2 or 3 or 4, it is characterised in that：
Between the S1 and S3, also S23 counts the identical oracle typing number of times,
The identical outside letter of the record control outside the fixed length time cycle or outside fixed length space length
The typing number of times in breath source.
8. a kind of recommendation method as claimed in claim 1 or 2 or 3 or 4, it is characterised in that：
, can recommended user and targeted customer's interaction described in also S4 after the S3.
9. a kind of recommendation method as claimed in claim 9, it is characterised in that：The S3 with
Between S4, also S31 notifications advertising message, targeted customer must receive notifications
Advertising message could enter S4.
10. a kind of commending system applied to social networks, it is characterised in that including：
Extraction module T1, extracts the information that the targeted customer is derived from external environment condition.
Cluster module T2, for being clustered to the user in the social networks, forms poly-
Class cluster, the user for constituting clustering cluster is can recommended user.
Recommending module T3, for by it is described can recommended user recommend the targeted customer.
11. a kind of commending system as claimed in claim 10, it is characterised in that the extraction
Module is optics barcode scanning device.
12. a kind of commending system as claimed in claim 10, it is characterised in that the extraction
Module is sound extraction module.
13. a kind of commending system as claimed in claim 10, it is characterised in that the extraction
Module is biological image extraction element, for taking the fingerprint, palmmprint, face, iris.
14. a kind of commending system as described in claim 10 or 11 or 12 or 13, its feature
It is：Also have between T2 and T3 and notify advertisement module T21, for advertising message will to be notified
It is sent to targeted customer.
15. a kind of commending system as described in claim asks 10 or 11 or 12 or 13, it is special
Levy and be：There is targeted customer authentication module T22 between T2 and T3, for verifying
Targeted customer's identity information.
16. a kind of commending system as described in claim 10 or 11 or 12 or 13, its feature
It is：Also have counting module T23 between T2 and T3, for outside the fixed length time cycle or
The typing number of times of the identical oracle is recorded outside fixed length space length.
17. a kind of commending system as described in claim 10 or 11 or 12 or 13, its feature
It is after the extraction module T1, cluster module T2, recommending module T3, also have
User interaction module T4, for it is described can between recommended user and targeted customer it is interactive.
18. a kind of commending system as claimed in claim 17, it is characterised in that the T3 with
Also have between T4 and notify advertisement module T31, the notice before getting in touch with interaction for them is wide
Information is accused to send with receiving.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610123752.6A CN107153659A (en) | 2016-03-04 | 2016-03-04 | A kind of recommendation method and commending system applied to social networks |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610123752.6A CN107153659A (en) | 2016-03-04 | 2016-03-04 | A kind of recommendation method and commending system applied to social networks |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN107153659A true CN107153659A (en) | 2017-09-12 |
Family
ID=59791402
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610123752.6A Pending CN107153659A (en) | 2016-03-04 | 2016-03-04 | A kind of recommendation method and commending system applied to social networks |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107153659A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109818852A (en) * | 2019-01-30 | 2019-05-28 | 施勤 | A kind of method for running based on internet friend-making business |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20110230229A1 (en) * | 2010-03-20 | 2011-09-22 | International Business Machines Corporation | Social Recommender System for Generating Dialogues Based on Similar Prior Dialogues from a Group of Users |
| CN103327045A (en) * | 2012-03-21 | 2013-09-25 | 腾讯科技（深圳）有限公司 | User recommendation method and system in social network |
| US20140379729A1 (en) * | 2013-05-31 | 2014-12-25 | Norma Saiph Savage | Online social persona management |
| CN104794656A (en) * | 2014-01-16 | 2015-07-22 | 朱开一 | Recommendation method and recommendation system applied to social networks |
| CN105046601A (en) * | 2015-07-09 | 2015-11-11 | 传成文化传媒（上海）有限公司 | User data processing method and system |
| CN105227971A (en) * | 2015-07-09 | 2016-01-06 | 传成文化传媒（上海）有限公司 | The information recommendation method of a kind of hotel TV and system |
-
2016
- 2016-03-04 CN CN201610123752.6A patent/CN107153659A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20110230229A1 (en) * | 2010-03-20 | 2011-09-22 | International Business Machines Corporation | Social Recommender System for Generating Dialogues Based on Similar Prior Dialogues from a Group of Users |
| CN103327045A (en) * | 2012-03-21 | 2013-09-25 | 腾讯科技（深圳）有限公司 | User recommendation method and system in social network |
| US20140379729A1 (en) * | 2013-05-31 | 2014-12-25 | Norma Saiph Savage | Online social persona management |
| CN104794656A (en) * | 2014-01-16 | 2015-07-22 | 朱开一 | Recommendation method and recommendation system applied to social networks |
| CN105046601A (en) * | 2015-07-09 | 2015-11-11 | 传成文化传媒（上海）有限公司 | User data processing method and system |
| CN105227971A (en) * | 2015-07-09 | 2016-01-06 | 传成文化传媒（上海）有限公司 | The information recommendation method of a kind of hotel TV and system |
Non-Patent Citations (1)
| Title |
|---|
| 刘海峰: "社交网络用户交互模型及行为偏好预测研究", 《中国博士学位论文全文数据库 信息科技辑》 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109818852A (en) * | 2019-01-30 | 2019-05-28 | 施勤 | A kind of method for running based on internet friend-making business |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11232670B2 (en) | Identification verification system | |
| Chang | An ethical framework for big data and smart cities | |
| US10250733B1 (en) | Lock screen interface for a mobile device apparatus | |
| CN107291732B (en) | Information pushing method and device | |
| TWI321761B (en) | ||
| US8255452B2 (en) | Systems and methods for universal enhanced log-in, identity document verification, and dedicated survey participation | |
| US20130325567A1 (en) | System and method for creating a virtual coupon | |
| US20140229251A1 (en) | Method and apparatus for presenting content in response to user inputs using dynamic intelligent profiling | |
| US20130191394A1 (en) | System and method for dynamically forming user groups | |
| US20130297416A1 (en) | Systems, apparatuses and methods for verifying consumer activity and providing value to consumers based on consumer activity | |
| JP4941860B2 (en) | Goods management system | |
| CN105190659A (en) | Methods and arrangements for smartphone payments and transactions | |
| US20090094158A1 (en) | Method and Apparatus for Processing and Transmitting Demographic Data Based on Secondary Marketing Identifier in a Multi-Computer Environment | |
| CN103729782A (en) | Public platform based product drawing method | |
| WO2013103708A1 (en) | Universal loyalty program including food and medicine recall, anti-counterfeiting, anti-identity theft and more | |
| KR102157536B1 (en) | System and method for managing customer in shop and shop using face recognition | |
| CN104424581A (en) | Method for carrying out consumption tracking survey and information spreading by utilizing two-dimensional code | |
| US20160180396A1 (en) | Mobile Promotion System, Method and Computer Program Product | |
| CN107153659A (en) | A kind of recommendation method and commending system applied to social networks | |
| AU2016299550A1 (en) | On-line advertisement method using advertisement website | |
| US20230360084A9 (en) | Creating an Advertisement Strategy | |
| US10417640B2 (en) | Systems and methods to provide data communication channels for user inputs to a centralized system | |
| KR101499531B1 (en) | Method and apparatus for providing product-based community service | |
| JP2021197111A (en) | Double authentication-preventive built-in system utilizing point system | |
| van’t Hof et al. | Check In/Check Out |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20170912 |
|
| WD01 | Invention patent application deemed withdrawn after publication |