Event data translation system

• US 20070220063A1
• Filed: 12/29/2006
• Published: 09/20/2007
• Est. Priority Date: 12/30/2005
• Status: Active Grant

• Current Assignee: Ganesh Peruvemba, Panoptic Development, Inc., Vadim Hunte
• Original Assignee: Panoptic Development, Inc.
• Inventors: Goldberg, Miriam, Woo, Peter, Sprague, Tibet, Bloch, Jonathan, O'Farrell, William, Shoemaker, Christopher
• Granted Patent: US 7,577,963 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/258 Data format conversion from or to a database
• CPC Class Codes: G06F 40/284 Lexical analysis, e.g. tokenisation or collocates
• CPC Class Codes: G06Q 10/109 Time management, e.g. calendars, reminders, meetings or time accounting
• CPC Class Codes: Y10S 707/99943 Generating database or data structure, e.g. via user interface

Abstract

An event translator system may perform at least three tasks: (1) extract or “harvest” date, time, description, and other information from digital files generated for human reading, such as web calendars or other event lists, emailed calendars, and imported files; (2) present the extracted event data to a user for modification, management, and monitoring; and (3) export the events to PIM software, web pages and/or application programming interfaces as appropriate file formats. The event translation system may be incorporated into a web site that is accessed by the user who enters a desired web address for event translation or otherwise transmits the digital files for translation. Alternatively, the system may be incorporated into a webpage as a browser plug-in that provides a user-selectable option to extract event information from a visited webpage. Other implementations are possible, including incorporation into desktop software, enterprise software on a server, and plug-ins for e-mail or other applications, among others.

Claims

1. An event data translation system, comprising:

an interface that receives input information;

at least one harvester that parses event data from the input information to generate at least one result event data set;

an analyzer that analyzes the result event data set output from the at least one harvester and selects at least a portion of the result event data set as a selected result event data set; and

a processing component that processes the selected result event data set to generate an event listing.

2. The event data translation system according to claim 1, further comprising:

a controller coupled to at least one of the at least one harvesters, the analyzer and the processing component.

3. The event data translation system according to claim 1, further comprising:

a pre-selector that selects the at least one harvester as a subset from a larger set of harvesters.

4. The event data translation system according to claim 1, further comprising:

a statistical analyzer that analyzes use of the event listing.

5. The event data translation system according to claim 1, wherein the at least one harvester includes a harvester of a type that is at least one of:

a table grammar harvester, a tree grammar inference harvester, and a two-tiered probabilistic harvester.

6. The event data translation system according to claim 1, wherein the interface displays the event listing.

7. The event data translation system according to claim 1, wherein the interface is a user interface.

8. The event data translation system according to claim 1, wherein the input information is at least one of:

an e-mail, a webpage, a text file and a pdf file.

9. The event data translation system according to claim 1, further comprising:

at least one of;

an HTML receiver and an HTML converter, wherein the input information is either received in an HTML format by the HTML receiver or converted into an HMTL format by the HTML converter.

10. The event data translation system according to claim 1, further comprising:

a monitor that monitors changes in a source of the input information.

11. The event data translation system according to claim 1, further comprising:

at least two harvesters that each parse event data from the input information to each generate a result event data set as a plurality of result event data sets, wherein the analyzer analyzes the plurality of result event data sets and selects at least a portion of the plurality of result event data sets as the selected result event data set.

12. The event data translation system according to claim 11, wherein the at least two harvesters include a harvester of a first type and having a first setting and a harvester of a first type and having a second setting, the first setting being different from the second setting.

13. A method for translating event data, comprising:

receiving input information;

performing at least one harvesting algorithm on the input information to generate a result event data set;

selecting at least a portion of the result event data set based on an analysis of the result event data set as a selected result event data set; and

generating an event listing from the selected result event data set.

14. The method according to claim 13, further comprising:

pre-selecting the at least one harvester algorithm as a subset from a larger set of harvesting algorithms.

15. The method according to claim 13, further comprising:

analyzing use of the event listing.

16. The method according to claim 13, wherein the at least one harvesting algorithm includes a harvesting algorithm of a type that is at least one of:

a table grammar harvesting algorithm, a tree grammar inference harvesting algorithm, and a two-tiered probabilistic harvesting algorithm.

17. The method according to claim 13, further comprising:

displaying the event listing.

18. The method according to claim 13, further comprising:

receiving user feedback on the event listing and using the user feedback to improve the at least one harvesting algorithm.

19. The method according to claim 13, wherein the input information is at least one of:

an e-mail, a webpage, a text file and a pdf file.

20. The method according to claim 13, further comprising:

at least one of;

receiving the input information in an HTML format and converting the input information into an HTML format.

21. The method according to claim 13, further comprising:

monitoring changes in a source of the input information.

22. The method according to claim 13, further comprising:

performing at least two harvesting algorithms on the input information to generate a plurality of result event data sets; and

selecting at least a portion of the plurality of result event data sets based on an analysis of the plurality of result event data sets as the selected result event data set.

23. A system including at least one processor that performs the steps recited in claim 13.

24. A method for extracting event information, comprising:

receiving source information;

processing the source information to generate processed source information;

harvesting the processed source information to generate result event information; and

outputting the result event information.

25. The method according to claim 24, wherein processing the source information includes breaking the source information into data chunks, and wherein harvesting the processed source information includes:

tokenizing the data chunks;

parsing the tokenized data chunks into a data structure; and

extracting the result event information from the tokenized and parsed data chunks.

26. The method according to claim 24, wherein processing the source information includes creating a tree structure, and wherein harvesting the processed source information includes:

traversing the tree structure to identify event information portions;

marking locations of identified event information portions with tokens on the tree structure;

identifying a tree grammar using at least some of the tokens as selected tokens;

associating text with the selected tokens according to the identified tree grammar to generate the result event information.

27. The method according to claim 24, wherein processing the source information includes:

classifying text from the source information according to pre-selected features to generate classified text;

assigning weights to the classified text based on use of a training data set to identify event information portions;

and wherein harvesting the processed source information includes;

associating identified event information portions according to pre-selected association features to generate the result event information.