Method and system to handle large volume of E-mail received from a plurality of senders intelligently

• US 6,816,885 B1
• Filed: 09/21/2000
• Issued: 11/09/2004
• Est. Priority Date: 09/21/2000
• Status: Expired due to Fees

• Current Assignee: Snap, Inc.
• Original Assignee: International Business Machines Corporation
• Inventors: Raghunandan, Hulikunta Prahlad
• Primary Examiner(s): Jaroenchonwanit, Bunjob
• Application Number:
  US09/666,230
• Time in Patent Office: 1,510 Days
• Field of Search: 709/205, 709/206, 709/207, 725/47
• US Class Current: 709/206
• CPC Class Codes: G06Q 10/107 Computer-aided management of electronic mailing [e-mailing]
• CPC Class Codes: H04L 51/212 using filtering or selective blocking

Abstract

This invention relates to a method, system and computer program product for intelligently handling a large volume of emails received from a plurality of senders by automatically parsing the email header and body to capture specified keywords and preparing a reply template using an expert system to analyze the received emails that are stored in a personalized email database.

Claims

1. In a computing system, a method to intelligently handle e-mails comprising the steps of:

receiving the e-mails;

sending e-mail responses to ones of the received e-mails;

parsing headers of the e-mails to identify senders and subjects;

parsing bodies of the e-mails;

parsing keywords of the e-mails;

categorizing the e-mails in response to the parsing of the e-mail bodies, wherein the categorizing includes identifying when reply templates are to be prepared for responses to respective ones of the e-mails, the reply templates being for completion by a user preparing the responses to the e-mails;

storing the received e-mails and parsed senders, subjects and keywords in a personalized e-mail database (PED);

preparing the reply templates using a reply template generator (RTG), including the step of;

analyzing the e-mails senders, subjects, and keywords stored in the PED using an expert system (ES) with machine learning capabilities to extract certain content of the e-mails, wherein such extracted content is included in ones of the reply templates;

storing the email responses in said PED; and

configuring said PED and said ES using an personalized email database configurator (PEC) for updation.

2. A method as claimed in claim 1, wherein the step of storing the received e-mails and parsed senders, subjects and keywords further comprises:

storing the received e-mails in a mailbox (MB) within said PED; and

storing the parsed senders, subjects, and keywords, in a New Knowledge Base (NKB) in the PED.

3. A method as claimed in claim 1, wherein the step of analyzing the e-mails and senders, subjects and keywords stored in the PED further comprises the step of:

selecting certain types of the contents of the e-mails to be included in the reply templates.

4. A method as claimed in claim 3, wherein for the step of selecting certain types of the contents of the e-mails to be included in the reply templates, the selecting being responsive to ages of the e-mails.

5. A method as claimed in claim 1 further including the steps of:

categorizing the received and sent e-mails in categories including;

i) initial e-mails received (e-mails R1), ii) e-mail responses sent for e-mails R1 (e-mails S1), iii) e-mails received in reply to e-mails S1 (emails R2), iv) e-mail responses sent for e-mails R2 (e-mails S2) and v) e-mails received in reply to e-mails S2 (e-mails R3); and

displaying the e-mails to the user in combinations of the categories of the e-mails R1, R2, R3, S1, S2 and S3 requested by the user, wherein the e-mails are displayed so that the categories of the e-mails are distinguishable by distinctive appearances.

6. A method as claimed in claim 1 wherein said reply template for one of the received e-mails is in a same format as an attachments of the e-mail.

7. A method as claimed in claim 1 further including searching the PED by said ES for co-relations amongst the e-mails received, wherein the co-relations are determined responsive to at least one of the following:

senders of the e-mails, subjects of the e-mails and keywords of the e-mails.

8. A method as claimed in claim 1, wherein the identifying when to prepare reply templates includes, for such a one of the reply templates, selecting among i) preparing the reply template immediately, ii) preparing the reply template at some future time, and iii) not preparing the reply template, the selecting being responsive to whether one of the received e-mails specifies a Cc address.

9. A method as claimed in claim 1, wherein the identifying when to prepare reply templates includes, for such a one of the reply templates, selecting among i) preparing the reply template immediately, ii) preparing the reply template at some future time, and iii) not preparing the reply template, the selecting being responsive to a length of one of the received e-mails.

10. A method as claimed in claim 1, wherein the categorizing of the e-mails includes identifying lengths of the e-mails, and the analyzing to extract certain content of the e-mails is responsive to the lengths.

11. In a computing system, a system to intelligently handle e-mails comprising:

means for receiving the e-mails;

means for sending e-mail responses to ones of the received e-mails;

means for parsing headers of the e-mails to identify senders and subjects;

means for parsing bodies of the e-mails;

means for parsing keywords of the e-mails;

means for categorizing the e-mails in response to the parsing of the e-mail bodies, wherein the means for categorizing includes means for identifying when reply templates are to be prepared for responses to respective ones of the e-mails, the reply templates being for completion by a user preparing the responses to the e-mails;

means for storing the received e-mails and parsed senders, subjects and keywords in a personalized e-mail database (PED);

means for preparing the reply templates using a reply template generator (RTG), including;

means for analyzing the e-mails senders, subjects and keywords stored in the PED using an Expert system (ES) with machine learning capabilities to extract certain content of the e-mails, wherein such extracted content is included in ones of the reply templates;

means for storing the email responses in said PED; and

means for configuring said PED an said ES using an personalized email database configurator (PEC) for updation.

12. A system as claimed in claim 11, wherein the means for storing the received e-mails and parsed senders, subjects and keywords further comprises:

means for storing the received e-mails in a mailbox (MB) within said PED; and

means for storing the parsed senders, subjects, and keywords in a New Knowledge Base (NKB) in the PED.

13. A system as claimed in claim 11, wherein the means for analyzing the e-mails and senders, subjects and keywords stored in the PED comprises:

means for selecting certain types of the contents of the e-mails to be included in the reply templates.

14. A system as claimed in claim 13, wherein for the means for selecting certain types of the contents of the e-mails to be included in the reply templates, the selecting being responsive to ages of the e-mails.

15. A system as claimed in claim 11, further comprising:

means for categorizing the received and sent e-mails in categories including;

i) initial e-mails received (e-mails R1), ii) e-mail responses sent for e-mails R1 (e-mails S1), iii) e-mails received in reply to e-mails S1 (e-mails R2), iv) e-mail responses sent for e-mails R2 (e-mail S2) and iv) e-mails received in reply to e-mails S2 (e-mails R3); and

means for displaying the e-mails to the user in combinations of the categories of the e-mails R1, R2, R3, S1, S2 and S3 requested by the user, wherein the e-mails are displayed so that the categories of the e-mails are distinguishable by distinctive appearances.

16. A system as claimed in claim 11 further including means for searching the PED by said ES for co-relations amongst e-mails received, wherein the co-relations are determined responsive to at least one of the following:

senders of the e-mails, subjects of the e-mails and keywords of the e-mails.

17. A system as claimed in claim 11, wherein the means for identifying when to prepare reply templates includes, for such a one of the reply templates, means for selecting among i) preparing the reply template immediately, ii) preparing the reply template at some future time, and iii) not preparing the reply template, the selecting being responsive to whether one of the received e-mails specifies a Cc address.

18. A system as claimed in claim 11, wherein the means for identifying when to prepare reply templates includes, for such a one of the reply templates, means for selecting among i) preparing the reply template immediately, ii) preparing the reply template at some future time, and iii) not preparing the reply template, the selecting being responsive to a length of one of the received e-mails.

19. A system as claimed in claim 11, wherein the means for categorizing of the e-mails includes means for identifying lengths of the e-mails, and the means for analyzing to extract certain content of the e-mails is responsive to the lengths.

20. A computer program product comprising computer readable program code stored on computer readable storage medium embodied therein for causing a computer to intelligently handle e-mails, said computer product comprising:

computer readable program code means configured for receiving e-mails;

computer readable program code means configured for sending e-mail responses to ones of the received e-mails;

computer readable program code means configured for parsing headers of the e-mails to identify senders, and subjects;

computer readable program code means configured for parsing bodies of the e-mails;

computer readable program code means configured for parsing keywords of the e-mails;

computer readable program code means configured for categorizing the e-mails in response to the parsing of the e-mail bodies wherein the categorizing includes identifying when reply templates are to be prepared for responses to respective ones of the e-mails, the reply templates being for completion by a user preparing the responses to the e-mails;

computer readable program code means configured for storing the received e-mails and parsed senders, subject and keywords in a personalized e-mail database (PED);

computer readable program code means configured for preparing the reply templates using a reply template generator (RTG), including;

computer readable program code means configured for analyzing the e-mails senders, subjects and keywords stored in the PED using an expert system (ES) with machine learning capabilities to extract certain content of the e-mails,

wherein such extracted content is included in ones of the reply templates;

computer readable program code means configured for storing the email responses in said PED; and

computer readable program code means for configuring said PED and said ES using an personalized email database configurator (PEC) for updation.

21. A computer program product as claimed in claim 20, wherein computer readable program code means configured for storing the received e-mails and parsed senders, subjects and keywords further comprises:

computer readable program code means configured for storing the received e-mails in a mailbox (MB) within said PED; and

;

computer readable program code means configured for storing the parsed senders, subjects and keywords in a New Knowledge Base (NKB) in the PED.

22. A computer program product as claimed in claim 20, wherein the computer readable program code means configured for analyzing the e-mails and senders, subjects and keywords stored in the PED further comprises:

computer readable program code means configured for selecting certain types of the contents of the e-mail to be included in the reply templates.

23. A computer program product as claimed in claim 22, wherein for the computer readable program code means configured for selecting certain types of the contents of the e-mails to be included in the reply templates, the selecting being responsive to ages of the e-mails.

24. A computer program product as claimed in claim 20, further including:

computer readable program code means configured for categorizing the received and sent e-mails in categories including;

i) initial e-mails received (e-mails R1), ii) e-mail responses sent for e-mails R1 (e-mails S1), iii) e-mails received in reply to e-mails S1 (e-mails R2), iv) e-mail responses sent for e-mails R2 (e-mails S2) and v) e-mails received in reply to e-mails S2 (e-mails R3); and

computer readable program code means configured for displaying the e-mails to the user in combinations of the categories of the e-mails R1, R2, S1, S2 and S3 requested by the user, wherein the e-mails are displayed so that the categories of the e-mails are distinguishable by distinctive appearances.

25. A computer program product as claimed in claim 20 further including computer readable program code means configured for searching the PED by said ES for co-relations amongst the e-mails received, wherein the co-relations are determined responsive to at least one of the following:

senders of the e-mails, subjects of the emails and keywords of the e-mails.

26. A computer program product as claimed in claim 20, wherein the identifying when to prepare reply templates includes, for such a one of the reply templates, selecting among i) preparing the reply template immediately, ii) preparing the reply template at some future time, and iii) not preparing the reply template, the selecting being responsive to whether one of the received e-mails specifies a Cc address.

27. A computer program product as claimed in claim 20, wherein the identifying when to prepare reply templates includes, for such a one of the reply templates, selecting among i) preparing the reply template immediately, ii) preparing the reply template at some fixture time, and ii) not preparing the reply template, the selecting being responsive to a length of one of the received e-mails.

28. A computer program product as claimed in claim 20, wherein the categorizing of the e-mails includes identifying lengths of the e-mails, and the analyzing to extract certain content of the e-mails is responsive to the lengths.