Detection of improper search queries in a wide area network search engine

• US 8,166,014 B2
• Filed: 05/02/2003
• Issued: 04/24/2012
• Est. Priority Date: 05/02/2003
• Status: Active Grant

• Current Assignee: R2 Solutions LLC (Acacia Research Corporation)
• Original Assignee: Yahoo! Inc. (Apollo Global Management, Inc.)
• Inventors: Kline, Scott B., Biggs, Jody D.
• Primary Examiner(s): DWIVEDI, MAHESH H
• Application Number:
  US10/429,209
• Publication Number:
  US 20040220915A1
• Time in Patent Office: 3,280 Days
• Field of Search: 707/10, 707/706, 707/709, 707/722
• US Class Current: 707/706
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 16/9532 Query formulation

Abstract

Search queries which are used to assess performance of search listings are filtered such that the remaining search queries more accurately represent behavior of human users genuinely looking for information in a search engine. Search queries which come from unrecognized user agents or which come from the same network address too closely together or too regularly are removed. If a volume of search queries for a given search term in a period of time exceeds an expected volume, search queries for that term are discarded.

Claims

1. A method for improving the accuracy by which a database of search queries represent human search behavior, the method comprising:

determining, by a computer, an expected quantity of search queries;

comparing a quantity of the search queries to the expected quantity of search queries;

determining that the quantity of search queries exceeds the expected quantity of search queries by at least a predetermined margin;

selecting a number of search queries of the quantity in accordance with an amount by which the quantity exceeds the expected quantity; and

removing the selected number of search queries from the quantity, where the search query includes a search term and a source,

where the determining the expected quantity of search queries includes determining an expected quantity of search queries based on a proportion of search volume attributable to the search term relative to the source, where the expected quantity of search queries based on a proportion of search volume attributable to the search term relative to the source is determined for a particular geographic region.

2. The method of claim 1, where the source is an Internet search engine.

3. The method of claim 1, where the determining the expected quantity of search queries includes determining an expected quantity of search queries based on a proportion of search volume attributable to the source.

4. The method of claim 3, where the expected quantity of search queries based on a proportion of search volume attributable to the source is determined for a particular geographic region.

5. The method of claim 1, where the determining the expected quantity of search queries includes determining an expected quantity of search queries based on a proportion of search volume attributable to the source relative to the search term.

6. The method of claim 5, where the expected quantity of search queries based on a proportion of search volume attributable to the source relative to the search term is determined for a particular geographic region.

7. A method for improving the accuracy by which a database of search queries represent human search behavior, the method comprising:

determining, by a computer, an expected quantity of search queries;

comparing a quantity of the search queries to the expected quantity of search queries;

determining that the quantity of search queries exceeds the expected quantity of search queries by at least a predetermined margin;

selecting a number of search queries of the quantity in accordance with an amount by which the quantity exceeds the expected quantity; and

removing the selected number of search queries from the quantity, where the search query includes a search term and a source,

where the determining the expected quantity of search queries includes determining an expected quantity of search queries based on a proportion of search volume attributable to the search term relative to the source, determining an expected quantity of search queries based on a proportion of search volume attributable to the source relative to the search term, and determining an expected quantity of search queries based on a proportion of search volume attributable to the source.

8. The method of claim 7, where the expected quantity of search queries based on a proportion of search volume attributable to the search term relative to the source is determined for a particular geographic region.

9. The method of claim 8, where the expected quantity of search queries based on a proportion of search volume attributable to the source is determined for a particular geographic region.

10. The method of claim 9, where the expected quantity of search queries based on a proportion of search volume attributable to the source relative to the search term is determined for a particular geographic region.