CN107770049A - A kind of invited user obtains the method and system of group information - Google Patents
A kind of invited user obtains the method and system of group information Download PDFInfo
- Publication number
- CN107770049A CN107770049A CN201710995642.3A CN201710995642A CN107770049A CN 107770049 A CN107770049 A CN 107770049A CN 201710995642 A CN201710995642 A CN 201710995642A CN 107770049 A CN107770049 A CN 107770049A
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- niquemin
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Classifications
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L51/00—User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail
- H04L51/04—Real-time or near real-time messaging, e.g. instant messaging [IM]
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L12/00—Data switching networks
- H04L12/02—Details
- H04L12/16—Arrangements for providing special services to substations
- H04L12/18—Arrangements for providing special services to substations for broadcast or conference, e.g. multicast
- H04L12/1813—Arrangements for providing special services to substations for broadcast or conference, e.g. multicast for computer conferences, e.g. chat rooms
- H04L12/1822—Conducting the conference, e.g. admission, detection, selection or grouping of participants, correlating users to one or more conference sessions, prioritising transmission
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L12/00—Data switching networks
- H04L12/02—Details
- H04L12/16—Arrangements for providing special services to substations
- H04L12/18—Arrangements for providing special services to substations for broadcast or conference, e.g. multicast
- H04L12/185—Arrangements for providing special services to substations for broadcast or conference, e.g. multicast with management of multicast group membership
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L51/00—User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail
- H04L51/52—User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail for supporting social networking services
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- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- General Engineering & Computer Science (AREA)
- Multimedia (AREA)
- Computing Systems (AREA)
- Information Transfer Between Computers (AREA)
Abstract
The invention provides a kind of method that invited user obtains group information, comprise the following steps：Instant communication information in group carries out machine learning, to determine the group type；The message request for carrying information about firms in group type and group is sent to the invited user；Friend relation in the group between each member is obtained according to information about firms in the group type and the group, to judge whether there is common friend between each member.The social network information of session group is sent to and invited user by the present invention, invited user is enabled to know the social network information of session group, so as to improve the security for adding session group, and lift the safe perceptibility of user and the value perceptibility to session group.
Description
Technical field
The present invention relates to communication technical field, obtains the method for group information more particularly to a kind of invited user and is
System.
Background technology
With the development of mobile communication technology, the use of instant communication software is more prevalent.User is using instant messaging
During software, it will usually add session group, and check message by session group or send message.
In the prior art, it is typically based on friend relation and invites user adding to conversation group, i.e. has added the use of session group
The good friend of itself is invited to add the session group in family.For the session group below hundred people, the rank and file that group advocates peace in group is equal
Good friend can be invited to add session group.For session groups more than hundred people, when number is less than hundred people in group, group advocates peace in group
Rank and file can invite good friend to add session group；When number reaches hundred people in group, only group master can invite good friend
Add session group.After invitee receives invitation notification, it is added directly into corresponding session group, shows in the session group
Show the information for inviting people and invitee.
Inventor has found that prior art at least has following defect during the present invention is realized：Invitee passes through
The invitation notification received can only know the information for inviting people, can not confirm whether the session group that is invited into is credible,
Security risk be present.
The content of the invention
The invention provides a kind of method that invited user obtains group information, comprise the following steps：
Instant communication information in group carries out machine learning, to determine the group type；
The message request for carrying information about firms in group type and group is sent to the invited user；
It is good between each member in the group to be obtained according to information about firms in the group type and the group
Friendly relation, to judge whether there is common friend between each member.
Further, the instant communication information in group carries out machine learning, comprises the following steps：
Forecast model is established using training data and by machine learning algorithm；
Multiple characteristics of the instant communication information in the group are extracted, and the multiple characteristic is divided
Class；
The niqueMin of the group type is predicted according to the feature of sorted data；
Type-collection of the niqueMin not less than the first default niqueMin is come out, using the group type as the group.
Further, the invitation letter for carrying information about firms in group type and group is sent to the invited user
Breath, comprises the following steps：
Receive the instant communication information of each member in the group, the instant communication information include chat message and
Chat file content；
According to the instant communication information of the member Data Identification is distributed to the member；
The member property is determined according to the Data Identification, the member property includes the class of member's chat content
Type；
Obtain the information about firms of the member, the information about firms include the member and other members in the group it
Between relation；
The message request for carrying information about firms in group type and group is sent to the invited user.
Further, Data Identification, including following step are distributed to the member according to the instant communication information of the member
Suddenly：
The characteristic in instant communication information corresponding to the member is extracted, and the characteristic is classified；
The niqueMin of the type of the member is predicted according to the feature of sorted data；
Type-collection of the niqueMin not less than the second default niqueMin is come out, using the Data Identification as the member.
Correspondingly, present invention also offers the system that a kind of invited user obtains group information, including：
Determining module, machine learning is carried out for the instant communication information in group, to determine the group type；
Sending module, inviting for information about firms in group type and group is carried for being sent to the invited user
Please information；
Judge module, it is each in the group for being obtained according to information about firms in the group type and the group
Friend relation between member, to judge whether there is common friend between each member.
Further, the determining module includes：
Unit is established, for using training data and establishing forecast model by machine learning algorithm；
First extraction unit, for extracting multiple characteristics of the instant communication information in the group, and by described in
Multiple characteristics are classified；
Predicting unit, for predicting the niqueMin of the group type according to the feature of sorted data；
Second extraction unit, for type-collection of the niqueMin not less than the first default niqueMin to be come out, to be used as institute
State the group type of group.
Further, the sending module includes：
Receiving unit, for receiving the instant communication information of each member in the group, the instant communication information bag
Include chat message and chat file content；
Allocation unit, Data Identification is distributed to the member for the instant communication information according to the member；
Determining unit, for determining the member property according to the Data Identification, the member property include it is described into
The type of member's chat content；
Acquiring unit, for obtaining the information about firms of the member, the information about firms includes the member and the group
Relation in group between other members；
Transmitting element, for the message request for carrying information about firms in group type and group to be sent into the quilt
Invite user.
Further, the allocation unit includes：
First extraction subelement, for extracting the characteristic in instant communication information corresponding to the member, and by institute
Characteristic is stated to be classified；
Subelement is predicted, the niqueMin of the type for predicting the member according to the feature of sorted data；
Second extraction subelement, for type-collection of the niqueMin not less than the second default niqueMin to be come out, using as
The Data Identification of the member.
The social network information of session group is sent to and invited user by the present invention so that invited user can obtain
Notify the social network information of words group, so as to improve the security for adding session group, and lift the safe perceptibility of user
And the value perceptibility to session group.
According to the accompanying drawings will be brighter to the detailed description of the specific embodiment of the invention, those skilled in the art
Above-mentioned and other purposes, the advantages and features of the present invention.
Brief description of the drawings
Some specific embodiments of the present invention are described in detail by way of example, and not by way of limitation with reference to the accompanying drawings hereinafter.
Identical reference denotes same or similar part or part in accompanying drawing.It should be appreciated by those skilled in the art that these
What accompanying drawing was not necessarily drawn to scale.In accompanying drawing：
Fig. 1 is the flow chart for the method that a kind of invited user according to an embodiment of the invention obtains group information；
Fig. 2 is a kind of block diagram of the system of invited user acquisition group information according to a further aspect of the present invention.
Embodiment
As shown in figure 1, the invention provides a kind of method that invited user obtains group information, comprise the following steps：
S100, the instant communication information in group carry out machine learning, to determine the group type；
S200, the message request for carrying information about firms in group type and group is sent to the invited user；
S300, obtained in the group between each member according to information about firms in the group type and the group
Friend relation, to judge whether there is common friend between each member.
Wherein, the instant communication information in group carries out machine learning in the step s 100, comprises the following steps：
S110, using training data and by machine learning algorithm establish forecast model；
S120, instant communication information in the extraction group multiple characteristics, and by the multiple characteristic
Classified；
S130, the niqueMin according to the feature of the sorted data prediction group type；
S140, type-collection of the niqueMin not less than the first default niqueMin come out, using the group as the group
Type.
Wherein, sent in step s 200 to the invited user and carry information about firms in group type and group
Message request, comprise the following steps：
S210, the instant communication information for receiving each member in the group, the instant communication information, which includes chat, to be believed
Breath and chat file content；
S220, according to the instant communication information of the member distribute Data Identification to the member；
S230, the member property is determined according to the Data Identification, the member property is included in member chat
The type of appearance；
S240, the information about firms for obtaining the member, the information about firms include the member with the group other
Relation between member；
S250, the message request for carrying information about firms in group type and group is sent to described it is invited to use
Family.
Wherein, in step S220, Data Identification, bag are distributed to the member according to the instant communication information of the member
Include following steps：
Characteristic in instant communication information corresponding to S221, the extraction member, and the characteristic is carried out
Classification；
S222, predicted according to the feature of sorted data the member type niqueMin；
S223, type-collection of the niqueMin not less than the second default niqueMin come out, using the data as the member
Mark.
Correspondingly, as shown in Fig. 2 present invention also offers the system that a kind of invited user obtains group information, including：
Determining module, machine learning is carried out for the instant communication information in group, to determine the group type；
Sending module, inviting for information about firms in group type and group is carried for being sent to the invited user
Please information；
Judge module, it is each in the group for being obtained according to information about firms in the group type and the group
Friend relation between member, to judge whether there is common friend between each member.
Further, the determining module includes：
Unit is established, for using training data and establishing forecast model by machine learning algorithm；
First extraction unit, for extracting multiple characteristics of the instant communication information in the group, and by described in
Multiple characteristics are classified；
Predicting unit, for predicting the niqueMin of the group type according to the feature of sorted data；
Second extraction unit, for type-collection of the niqueMin not less than the first default niqueMin to be come out, to be used as institute
State the group type of group.
Further, the sending module includes：
Receiving unit, for receiving the instant communication information of each member in the group, the instant communication information bag
Include chat message and chat file content；
Allocation unit, Data Identification is distributed to the member for the instant communication information according to the member；
Determining unit, for determining the member property according to the Data Identification, the member property include it is described into
The type of member's chat content；
Acquiring unit, for obtaining the information about firms of the member, the information about firms includes the member and the group
Relation in group between other members；
Transmitting element, for the message request for carrying information about firms in group type and group to be sent into the quilt
Invite user.
Further, the allocation unit includes：
First extraction subelement, for extracting the characteristic in instant communication information corresponding to the member, and by institute
Characteristic is stated to be classified；
Subelement is predicted, the niqueMin of the type for predicting the member according to the feature of sorted data；
Second extraction subelement, for type-collection of the niqueMin not less than the second default niqueMin to be come out, using as
The Data Identification of the member.
The social network information of session group is sent to and invited user by the present invention so that invited user can obtain
Notify the social network information of words group, so as to improve the security for adding session group, and lift the safe perceptibility of user
And the value perceptibility to session group.
So far, although those skilled in the art will appreciate that detailed herein have shown and described multiple showing for the present invention
Example property embodiment, still, still can be direct according to present disclosure without departing from the spirit and scope of the present invention
It is determined that or derive many other variations or modifications for meeting the principle of the invention.Therefore, the scope of the present invention is understood that and recognized
It is set to and covers other all these variations or modifications.
Claims (8)
1. a kind of method that invited user obtains group information, it is characterised in that comprise the following steps：
Instant communication information in group carries out machine learning, to determine the group type；
The message request for carrying information about firms in group type and group is sent to the invited user；
The good friend in the group between each member is obtained according to information about firms in the group type and the group to close
System, to judge whether there is common friend between each member.
2. the method that invited user according to claim 1 obtains group information, it is characterised in that according in group
Instant communication information carries out machine learning, comprises the following steps：
Forecast model is established using training data and by machine learning algorithm；
Multiple characteristics of the instant communication information in the group are extracted, and the multiple characteristic is classified；
The niqueMin of the group type is predicted according to the feature of sorted data；
Type-collection of the niqueMin not less than the first default niqueMin is come out, using the group type as the group.
3. the method that invited user according to claim 2 obtains group information, it is characterised in that be invited to described
User sends the message request for carrying information about firms in group type and group, comprises the following steps：
The instant communication information of each member in the group is received, the instant communication information includes chat message and chat
File content；
According to the instant communication information of the member Data Identification is distributed to the member；
The member property is determined according to the Data Identification, the member property includes the type of member's chat content；
The information about firms of the member is obtained, the information about firms is included in the member and the group between other members
Relation；
The message request for carrying information about firms in group type and group is sent to the invited user.
4. the method that the invited user according to any one of claim 1-3 obtains group information, it is characterised in that root
Data Identification is distributed to the member according to the instant communication information of the member, is comprised the following steps：
The characteristic in instant communication information corresponding to the member is extracted, and the characteristic is classified；
The niqueMin of the type of the member is predicted according to the feature of sorted data；
Type-collection of the niqueMin not less than the second default niqueMin is come out, using the Data Identification as the member.
A kind of 5. system that invited user obtains group information, it is characterised in that including：
Determining module, machine learning is carried out for the instant communication information in group, to determine the group type；
Sending module, the invitation letter of information about firms in group type and group is carried for being sent to the invited user
Breath；
Judge module, for obtaining each member in the group according to information about firms in the group type and the group
Between friend relation, to judge whether there is common friend between each member.
6. the system that invited user according to claim 1 obtains group information, it is characterised in that the determining module
Including：
Unit is established, for using training data and establishing forecast model by machine learning algorithm；
First extraction unit, for extracting multiple characteristics of the instant communication information in the group, and will be the multiple
Characteristic is classified；
Predicting unit, for predicting the niqueMin of the group type according to the feature of sorted data；
Second extraction unit, for type-collection of the niqueMin not less than the first default niqueMin to be come out, to be used as the group
The group type of group.
7. the system that invited user according to claim 6 obtains group information, it is characterised in that the sending module
Including：
Receiving unit, for receiving the instant communication information of each member in the group, the instant communication information includes chatting
Its information and chat file content；
Allocation unit, Data Identification is distributed to the member for the instant communication information according to the member；
Determining unit, for determining the member property according to the Data Identification, the member property is chatted including the member
The type of its content；
Acquiring unit, for obtaining the information about firms of the member, the information about firms is included in the member and the group
Relation between other members；
Transmitting element, for the message request for carrying information about firms in group type and group to be sent into described be invited to
User.
8. the system that the invited user according to any one of claim 5-7 obtains group information, it is characterised in that institute
Stating allocation unit includes：
First extraction subelement, for extracting the characteristic in instant communication information corresponding to the member, and by the spy
Sign data are classified；
Subelement is predicted, the niqueMin of the type for predicting the member according to the feature of sorted data；
Second extraction subelement, for type-collection of the niqueMin not less than the second default niqueMin to be come out, using as described
The Data Identification of member.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710995642.3A CN107770049A (en) | 2017-10-23 | 2017-10-23 | A kind of invited user obtains the method and system of group information |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710995642.3A CN107770049A (en) | 2017-10-23 | 2017-10-23 | A kind of invited user obtains the method and system of group information |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN107770049A true CN107770049A (en) | 2018-03-06 |
Family
ID=61268356
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710995642.3A Pending CN107770049A (en) | 2017-10-23 | 2017-10-23 | A kind of invited user obtains the method and system of group information |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107770049A (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110245542A (en) * | 2018-03-09 | 2019-09-17 | 株式会社东芝 | Information processing unit, information processing method and recording medium |
| CN111211963A (en) * | 2019-12-23 | 2020-05-29 | 北京达佳互联信息技术有限公司 | Chat group joining method and device, electronic equipment and storage medium |
| CN112508507A (en) * | 2020-11-17 | 2021-03-16 | 北京聚友大道科技发展有限公司 | Information management method and device and electronic equipment |
| CN113645205A (en) * | 2021-07-28 | 2021-11-12 | 上海纽盾网安科技有限公司 | Safety control method, client and system for preventing phishing and adding contacts |
| WO2022143505A1 (en) * | 2021-01-04 | 2022-07-07 | 腾讯科技（深圳）有限公司 | Group type identification method and apparatus, computer device, and medium |
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| CN113645205A (en) * | 2021-07-28 | 2021-11-12 | 上海纽盾网安科技有限公司 | Safety control method, client and system for preventing phishing and adding contacts |
| CN113645205B (en) * | 2021-07-28 | 2023-05-12 | 上海纽盾网安科技有限公司 | Safety control method, client and system for adding contact person for preventing phishing |
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