Method and System for Agent Based Summarization

• US 20110099134A1
• Filed: 10/27/2010
• Published: 04/28/2011
• Est. Priority Date: 10/28/2009
• Status: Abandoned Application

• Current Assignee: Sameer Yami, Sanika Shirwadkar
• Original Assignee: Sameer Yami, Sanika Shirwadkar
• Inventors: Yami, Sameer, Shirwadkar, Sanika
• Application Number:
  US12/913,593
• Publication Number:
  US 20110099134A1
• Time in Patent Office: Days
• US Class Current: 706/12
• CPC Class Codes: G06F 16/345 Summarisation for human users

Abstract

A method and system for using a proxy agent based access to documents and the corresponding summaries and its subsequent usage is disclosed. The method and system provides for retrieving a document, generating or retrieving summary, generating statistical parameters to judge the summary quality, using text segmentation to judge the quality of the summary, getting user rating input and using it to train a classifier, using the classifier to predict the rating of a summary, displaying the summary along with its rating, and optionally overlaying the summary display with relevant advertising and thus prevent denial of information/information overload and stimulating accelerated learning.

Claims

1. A method comprising:

Generating or accessing pre-generated document summary using an intermediary agent component,

whereby said summary prevents information overload when plurality of electronic data is available.

2. The method of claim 1, wherein the said summary comprises of the most informative sentences of the document and wherein the generation of said summary further comprises:

comparing with the original document and calculating statistical parameters;

storing parameters in a cache and training a classifier with the statistical parameters to predict the summary rating.

3. The method of claim 1, wherein the said summary is displayed along with other useful features not limited to a predicted rating, an option for further input of user rating, and a relevant advertisement.

4. The method of claim 1, wherein the said summary uses semantic priming to accelerate user learning.

5. The method of claim 1, wherein the summary is used for processing by a natural language processing system for appropriate substitution of various part of speech tags.

6. The method of claim 1, wherein the said summary'"'"'s parameters and the said summary'"'"'s probability distribution is compared with the original document'"'"'s parameters and probability distribution.

7. The method of claim 1, wherein the precision and recall of the summary is calculated based on the concepts present in the original document.

8. A system comprising:

Means adapted for generating or accessing pre-generated document summary using an intermediary agent component,

whereby said summary prevents information overload when plurality of electronic data is available.

9. The system of claim 8, wherein the said summary comprises of the most informative sentences of the document and wherein the generation of said summary further comprises:

comparing with the original document and calculating statistical parameters;

storing parameters in a cache and training a classifier with the statistical parameters to predict the summary rating.

10. The system of claim 8, wherein the said summary is displayed along with other useful features not limited to:

a predicted rating, an option for further input of user rating; and

a relevant advertisement.

11. The method of claim 8, wherein the said summary uses semantic priming to accelerate user learning.

12. The system of claim 8, wherein the summary is used for processing by a natural language processing system for appropriate substitution of various part of speech tags.

13. The system of claim 8, wherein the said summary'"'"'s parameters and the said summary'"'"'s probability distribution is compared with the original document'"'"'s parameters and probability distribution.

14. The system of claim 8, wherein the precision and recall of the summary is calculated based on the concepts present in the original document.

15. A non-transitory computer readable medium of instructions comprising:

instructions for generating or accessing pre-generated document summary using an intermediary agent component,

whereby said summary prevents information overload when plurality of electronic data is available.

16. The non-transitory computer readable medium of instructions of claim 15, wherein the said summary comprises of the most informative sentences of the document and wherein the generation of said summary further comprises:

comparing with the original document and calculating statistical parameters;

storing parameters in a cache and training a classifier with the statistical parameters to predict the summary rating.

17. The non-transitory computer readable medium of instructions of claim 15, wherein the said summary is displayed along with other useful features not limited to:

a predicted rating, an option for further input of user rating; and

a relevant advertisement.

18. The non-transitory computer readable medium of instructions of claim 15, wherein the said summary uses semantic priming to accelerate user learning.

19. The non-transitory computer readable medium of instructions of claim 15, wherein the summary is used for processing by a natural language processing system for appropriate substitution of various part of speech tags.

20. The non-transitory computer readable medium of instructions of claim 15, wherein the said summary'"'"'s parameters and the said summary'"'"'s probability distribution is compared with the original document'"'"'s parameters and probability distribution.

21. The non-transitory computer readable medium of instructions of claim 15, wherein the precision and recall of the summary is calculated based on the concepts present in the original document.