Event naming

• US 8,463,790 B1
• Filed: 08/27/2010
• Issued: 06/11/2013
• Est. Priority Date: 03/23/2010
• Status: Active Grant

• Current Assignee: Aurea Software Incorporated (ESW Capital, LLC)
• Original Assignee: FirstRain, Inc. (Ignite Technologies Incorporated)
• Inventors: Joshi, Ashutosh, Gupta, Aparna, Mohanty, Binay, Upadhyay, Jalvin, Arora, Rajiv, Betz, Martin, Prospero, Michael, Cooke, David, Rao, Prashant
• Primary Examiner(s): Kerzhner, Aleksandr
• Application Number:
  US12/870,691
• Time in Patent Office: 1,019 Days
• Field of Search: 707/738, 707/999.002
• US Class Current: 707/738
• CPC Class Codes: G06F 16/93 Document management systems
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 2218/12 Classification; Matching
• CPC Class Codes: G06F 3/0482 Interaction with lists of selectable items, e.g. menus
• CPC Class Codes: G06V 30/40 Document-oriented image-based pattern recognition

Abstract

Some embodiments provide a machine-implemented method. The method identifies an event for a particular category based on a number of documents classified as relevant to the particular category in a particular period of time. Based on content of the documents classified as relevant to the particular category, the method identifies a set of keywords for the event. The method uses the keywords to automatically select a representative document for the event. Some embodiments store a link to the representative document and automatically determine whether the particular document is still accessible at the link. When the document is no longer accessible at the link, the method replaces the document with a backup document as the representative document for the event.

Claims

1. A machine-implemented method comprising:

identifying an event for a particular category based on a first quantity of documents classified as relevant to the particular category in a first period of time compared with a second quantity of documents relevant to the particular category in a previous, second period of time;

identifying a first set of key words in the first quantity of documents and a second set of key words in the second quantity of documents;

based on a comparison of the first set of key words to the second set of key words, identifying a set of event keywords more prevalent in the documents classified as relevant to the particular category in the first period of time than in the documents classified as relevant to the particular category in the second period of time;

calculating scores for each of the first quantity of documents based on appearances of the event keywords in the documents;

automatically selecting a highest scoring document as a representative document for the event and identifying a link to the representative document;

automatically determining whether the representative document is still accessible at the identified link; and

when the representative document is no longer accessible at the identified link, replacing the highest scoring document with a next highest scoring document as the representative document for the event.

2. The method of claim 1, wherein the representative document has a title that is used as a name for the event.

3. The method of claim 2, wherein the name for the event is used to display the event to a user.

4. The method of claim 1, wherein the method is performed by a research system that crawls the world wide web on an ongoing basis for new documents.

5. The method of claim 1, wherein the event is identified when the first quantity of documents classified as relevant to the particular category in the first period of time is anomalously high.

6. The method of claim 1, wherein the particular category is one of a company, an industry, a person, and a product.

7. The method of claim 1, wherein the first period of time is a particular day and the first quantity of documents classified as relevant to the particular category in the first period of time is the quantity of new documents relevant to the particular category appearing on the world wide web on the particular day.

8. The method of claim 1, wherein the set of event keywords more prevalent in the first quantity of documents than in the second quantity of documents comprises keywords that occur above a particular minimum number of times in the documents classified as relevant to the particular category in the first period of time.

9. The method of claim 1, wherein the highest scoring document is a document that most prominently uses the event keywords of the documents classified as relevant to the particular category in the first period of time.

10. A machine readable medium storing a program which when executed by at least one processor maintains a stored link to a document, the program comprising sets of instructions for:

identifying an event for a particular category based on a first quantity of documents classified as relevant to the particular category in a first period of time compared with a second quantity of documents relevant to the particular category in a previous, second period of time;

identifying a first set of key words in the first quantity of documents and a second set of key words in the second quantity of documents;

based on a comparison of the first set of key words to the second set of key words, identifying a set of event keywords more prevalent in the documents classified as relevant to the particular category in the first period of time than in the documents classified as relevant to the particular category in the second period of time;

calculating scores for each of the first quantity of documents based on appearances of the event keywords in the documents;

automatically selecting a highest scoring document as a representative document for the event and identifying a link to the representative document;

automatically determining whether the representative document is still accessible at the identified link; and

when the representative document is no longer accessible at the identified link, replacing the highest scoring document with a next highest scoring document as the representative document for the event.

11. The machine readable medium of claim 10, wherein the event is an occurrence of an abnormally high volume of documents appearing on the world wide web relevant to a particular category.

12. The machine readable medium of claim 10, wherein the set of instructions for automatically determining whether the representative document is still accessible comprises a set of instructions for accessing a URL stored for the document.

13. The machine readable medium of claim 10, wherein an error is received when the representative document is no longer accessible at the identified link.

14. The machine readable medium of claim 10, wherein the program automatically determines whether the representative document is still accessible on a regularly scheduled basis.

15. The machine readable medium of claim 10, wherein the next highest scoring document has a different title than the highest scoring document.

16. The machine readable medium of claim 10, wherein the next highest scoring document has a different quantity of event keywords associated with the event than the highest scoring document.

17. The machine readable medium of claim 10, wherein the next highest scoring document has different content than the highest scoring document.