Efficiently sharing user selected information with a set of determined recipients

• US 10,216,393 B2
• Filed: 12/02/2014
• Issued: 02/26/2019
• Est. Priority Date: 07/30/2010
• Status: Active Grant

• Current Assignee: Beijing Zitiao Network Technology Company Limited (ByteDance Ltd.)
• Original Assignee: International Business Machines Corporation
• Inventors: Lu, Pei-Lun, Tu, Giant, Yang, Jason C S
• Primary Examiner(s): Salomon, Phenuel S
• Application Number:
  US14/557,698
• Publication Number:
  US 20150089391A1
• Time in Patent Office: 1,547 Days
• CPC Class Codes: G06F 3/04842 Selection of displayed objects or displayed text elements G06F3/0482 takes precedence
• CPC Class Codes: G06F 3/04847 Interaction techniques to control parameter settings, e.g. interaction with sliders or dials
• CPC Class Codes: G06Q 10/107 Computer-aided management of electronic mailing [e-mailing]
• CPC Class Codes: H04L 51/214 using selective forwarding
• CPC Class Codes: H04L 51/52 for supporting social networking services
• CPC Class Codes: H04L 51/56 Unified messaging, e.g. interactions between e-mail, instant messaging or converged IP messaging [CPM]

Abstract

Targeted information to be shared according to a “pre-analyzed user behavior” of a set of potential candidates is analyzed. The pre-analyzed user behavior is determined from a set of previously conveyed messages from a sender to one of the potential candidates. A list representing a determined subset of the potential candidates and related preference tools/applications is presented to the sender via a user interface. Tools/applications are determined for sending said targeted information content. An action message is sent to the tools/applications of selected candidates, which results in each of the subset of potential candidates receiving the targeted information.

Claims

1. A method comprising:

analyzing targeted information to be shared according to a “

pre-analyzed user behavior”

of a set of potential candidates, wherein

the pre-analyzed user behavior is determined from a set of previously conveyed messages from a sender to one of the potential candidates;

presenting a list representing a determined subset of the potential candidates and related preference tools/applications to the sender via a user interface;

determining tools/applications for sending said targeted information content; and

sending an action message to said tools/applications of selected candidates, which results in each of the subset of potential candidates receiving the targeted information, wherein

said analyzing step further comprises a step of segmenting content of said information to be shared and calculating said similarity score between each group and said targeted information content by a TF/IDF weighting technique or an equivalent technique.

2. The method of claim 1, wherein

said “

pre-analyzed user behavior”

comprises group information and a user behavior message related thereto, said share request message comprises targeted information and a current time, and said action message comprises targeted information and a selected candidate.

3. The method of claim 2, wherein

said user behavior messages each comprise candidates, a delivery type, a delivery time, and other alternative information, said other alternative information comprising a description of a location where a user interacts with a person, said person'"'"'s gender and age, and a best available tool of delivery;

wherein said group information comprises a “

group ID” and

a “

vector”

calculated by said TF/IDF weighting technique to represent one or more shortlisted groups in conjunction with said information content.

4. The method of claim 3, wherein

said analyzing step further comprises a secondary text clustering step, when said targeted information is directly determined as belonging to a selected group, for re-calculating a “

vector”

for representing said selected group containing said targeted information content.

5. The method of claim 1, further comprising a step of determining shortlisted groups.

6. The method of claim 5, wherein

said determining step comprises comparing a similarity score threshold with said similarity score between each group and said information content to determine one or more shortlisted groups which said information content belongs to.

7. A computer program product comprising:

a computer usable hardware storage device having computer usable program code embodied therewith, the computer usable program code comprising;

computer usable program code configured to analyze targeted information to be shared according to a “

pre-analyzed user behavior”

of a set of potential candidates, wherein

the pre-analyzed user behavior is determined from a set of previously conveyed messages from a sender to one of the potential candidates;

computer usable program code configured to present a list representing a determined subset of the potential candidates and related preference tools/applications to the sender via a user interface;

computer usable program code configured to determine tools/applications for sending said targeted information content; and

computer usable program code configured to send an action message to said tools/applications of selected candidates, which results in each of the subset of potential candidates receiving the targeted information, wherein

said analyzing step further comprises a step of segmenting content of said information to be shared and calculating said similarity score between each group and said targeted information content by a TF/IDF weighting technique or an equivalent technique.

8. The computer program product of claim 7, wherein

said “

pre-analyzed user behavior”

comprises group information and a user behavior message related thereto, said share request message comprises targeted information and a current time, and said action message comprises targeted information and a selected candidate.

9. The computer program product of claim 8, wherein

said computer usable program code to analyze further comprises computer usable program code to determine shortlisted groups.

10. The computer program product of claim 9, wherein

said computer usable program code to determine further comprises computer usable program code to compare a similarity score threshold with said similarity score between each group and said information content to determine one or more shortlisted groups which said information content belongs to.

11. The computer program product of claim 8, wherein

said user behavior messages each comprise candidates, a delivery type, a delivery time, and other alternative information, said other alternative information comprising a description of a location where a user interacts with a person, said person'"'"'s gender and age, and a best available tool of delivery;

wherein said group information comprises a “

group ID” and

a “

vector”

calculated by said TF/IDF weighting technique to represent one or more shortlisted groups in conjunction with said information content.

12. The computer program product of claim 11, wherein

said computer usable program code to analyze further comprises computer usable program code to implement a secondary text clustering step, when said targeted information is directly determined as belonging to a selected group, for re-calculating a “

vector”

for representing said selected group containing said targeted information content.

13. A system comprising:

one or more processors;

a non-transitory storage medium storing computer usable program code that the one or more processors execute, the computer usable program code comprising;

computer usable program code configured to analyze targeted information to be shared according to a “

pre-analyzed user behavior”

of a set of potential candidates, wherein

the pre-analyzed user behavior is determined from a set of previously conveyed messages from a sender to one of the potential candidates;

computer usable program code configured to present a list representing a determined subset of the potential candidates and related preference tools/applications to the sender via a user interface;

computer usable program code configured to determine tools/applications for sending said targeted information content; and

computer usable program code configured to send an action message to said tools/applications of selected candidates, which results in each of the subset of potential candidates receiving the targeted information, wherein

said analyzing step further comprises a step of segmenting content of said information to be shared and calculating said similarity score between each group and said targeted information content by a TF/IDF weighting technique or an equivalent technique.

14. The system of claim 13, wherein

said “

pre-analyzed user behavior”

comprises group information and a user behavior message related thereto, said share request message comprises targeted information and a current time, and said action message comprises targeted information and a selected candidate.

15. The system of claim 14, wherein

said computer usable program code to determine further comprises computer usable program code to compare a similarity score threshold with said similarity score between each group and said information content to determine one or more shortlisted groups which said information content belongs to.

16. The system of claim 14, wherein

said user behavior messages each comprise candidates, a delivery type, a delivery time, and other alternative information, said other alternative information comprising a description of a location where a user interacts with a person, said person'"'"'s gender and age, and a best available tool of delivery;

wherein said group information comprises a “

group ID” and

a “

vector”

calculated by said TF/IDF weighting technique to represent one or more shortlisted groups in conjunction with said information content.

17. The system of claim 13, wherein

said computer usable program code to analyze further comprises computer usable program code to determine shortlisted groups.