EFFICIENTLY SHARING USER SELECTED INFORMATION WITH A SET OF DETERMINED RECIPIENTS

• US 20120192085A1
• Filed: 07/25/2011
• Published: 07/26/2012
• 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, FREDDY PL, TU, GIANT HM, YANG, JASON CS
• Granted Patent: US 8,930,826 B2
• Time in Patent Office: Days
• US Class Current: 715/752
• 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

Abstract

Information concerning a set of recipients of previously conveyed messages from a sender can be collected. Patterns between content of the previously conveyed messages and each of the set of recipients can be determined and stored. Information can be selected within a user interface to share with others. The selected information can be analyzed and matched against the stored patterns. A subset of the recipients can be automatically determined. The subset can be those recipients likely to be interested in the selected information based on results of the analyzing and the matching. The information can be conveyed within at least one message from a sender device of the sender to one or more remotely located devices. Each of the one or more remotely located devices can be devices associated with at least a portion of the subset of the recipients.

Claims

1. A method comprising:

collecting information concerning a set of recipients of previously conveyed messages from a sender;

determining and storing patterns between content of the previously conveyed messages and each of the set of recipients;

selecting information within a user interface to share with others;

analyzing the selected information and matching it against the stored patterns;

automatically determining a subset of the recipients that are likely to be interested in the selected information based on results of the analyzing and the matching; and

conveying the information within at least one message from a sender device of the sender to one or more remotely located devices, wherein each of the one or more remotely located devices are devices associated with at least a portion of the subset of the recipients.

2. The method of claim 1, wherein the previously conveyed messages are conveyed using a plurality of different applications running on the sender device, each of the different applications being for a specific one of a plurality of different messaging types, each of the different messaging types having a recipient specific address associated that is unique to that one message type;

said method further comprising;

storing and indexing recipient specific addresses and messaging types for the previously conveyed messages, which are indexed against the stored patterns;

when automatically determining the subset of recipients, also automatically determining a messaging type and a recipient specific address for each of the subset of recipients based on the stored and indexed information; and

conveying the information to the portion of the subset of recipients, wherein the conveying is to the automatically determined recipient specific address and uses one of the different applications running on the sender device that is associated with the automatically determined messaging type.

3. The method of claim 2, wherein the different messaging types comprise at least three different messaging types selected from a group consisting of an email type, a short message type, a voice message type, a video conferencing type, and a micro-blogging type.

4. The method of claim 1, further comprising:

automatically conveying the information from the sender device to remotely located devices of the subset of recipients without the sender ever manually inputting an identity of any of the recipients into a user interface, as the set of recipients is automatically determined using the patterns and results of the matching.

5. The method of claim 1, wherein message information of the previously conveyed messages is stored along with the patterns, wherein the message information comprises 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.

6. The method of claim 1, wherein said step of analyzing further comprises calculating a similarity score between content of the previously conveyed messages and the selected information, wherein the subset of recipients is determined by the similarly score associated with a recipient being above a threshold, wherein other ones of the recipients having a similarly score below the threshold are not including in the determined subset of recipients.

7. The method of claim 6, wherein said similarity score is a cosine similarity score between each existing group and each term-based information content and said each term-based information content is calculated by a TF/IDF weighting technique or an equivalent technique so as to express as a “

vector”

.

8. The method of claim 7, further comprising a step of determining shortlisted groups.

9. The method of claim 8, wherein said determining step further 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.

10. The method of claim 9, wherein said result of analysis comprises group information and related said previously conveyed messages, and each said group information comprises a “

group ID” and

a “

vector”

calculated by said TF/IDF weighting technique to represent one of said one or more shortlisted groups containing said information content.

11. The method of claim 10, further comprising a secondary text clustering step to re-calculate one or more “

vectors”

for representing said one or more shortlisted groups containing said information content by combining one or more “

vectors”

representing one or more shortlisted groups previously stored by said secondary text clustering but being indicated by said one or more group IDs with said information content by using said TF/IDF weighting technique;

wherein said secondary text clustering step, further included in a dispatching step, when 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.

12. The method of claim 11, further comprising a step of categorizing according to a user-made rule to determine whether said information content matches said user user-made rule and determine that said targeted information belongs to a specific group if keywords of said rule are present in said information content.

13. The method of claim 12, wherein said user-made rule comprises one or more user-made terms or a combination thereof for functioning as keywords according to said user'"'"'s preference.

14. A computer program product for handling media, the computer program product comprising:

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

computer usable program code configured to collect information concerning a set of recipients of previously conveyed messages from a sender;

computer usable program code configured to determine and storing patterns between content of the previously conveyed messages and each of the set of recipients;

computer usable program code configured to select information within a user interface to share with others;

computer usable program code configured to analyze the selected information and match it against the stored patterns;

computer usable program code configured to automatically determine a subset of the recipients that are likely to be interested in the selected information based on results of the analyzing and the matching; and

computer usable program code configured to convey the information within at least one message from a sender device of the sender to one or more remotely located devices, wherein each of the one or more remotely located devices are devices associated with at least a portion of the subset of the recipients.

15. The computer program product of claim 14, wherein the previously conveyed messages are conveyed using a plurality of different applications running on the sender device, each of the different applications being for a specific one of a plurality of different messaging types, each of the different messaging types having a recipient specific address associated that is unique to that one message type;

said method further comprising;

computer usable program code configured to store and indexing recipient specific addresses and messaging types for the previously conveyed messages, which are indexed against the stored patterns;

computer usable program code configured to, when automatically determining the subset of recipients, also automatically determine a messaging type and a recipient specific address for each of the subset of recipients based on the stored and indexed information; and

computer usable program code configured to convey the information to the portion of the subset of recipients, wherein the conveying is to the automatically determined recipient specific address and uses one of the different applications running on the sender device that is associated with the automatically determined messaging type.

16. The computer program product of claim 15, wherein the different messaging types comprise at least three different messaging types selected from a group consisting of an email type, a short message type, a voice message type, a video conferencing type, and a micro-blogging type.

17. The computer program product of claim 14, further comprising:

computer usable program code configured to automatically convey the information from the sender device to remotely located devices of the subset of recipients without the sender ever manually inputting an identity of any of the recipients into a user interface, as the set of recipients is automatically determined using the patterns and results of the matching.

18. A system comprising a bus system, a memory connected to the bus system, wherein an instruction set is stored in the memory, a processing unit connected to the bus system, wherein said processing unit is configured to execute the instruction set, wherein when the system executes the instruction set said system is operable to:

collect information concerning a set of recipients of previously conveyed messages from a sender;

determine and storing patterns between content of the previously conveyed messages and each of the set of recipients;

select information within a user interface to share with others;

analyze the selected information and match it against the stored patterns;

automatically determine a subset of the recipients that are likely to be interested in the selected information based on results of the analyzing and the matching; and

convey the information within at least one message from a sender device of the sender to one or more remotely located devices, wherein each of the one or more remotely located devices are devices associated with at least a portion of the subset of the recipients.

19. 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 determining 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.

20. The method of claim 19, 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.

21. The method of claim 20, 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.

22. The method of claim 21, further comprising a step of determining shortlisted groups.

23. The method of claim 22, 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.

24. The method of claim 20, 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.

25. The method of claim 24, 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.