Using user feedback to improve search results

• US 8,874,591 B2
• Filed: 01/31/2006
• Issued: 10/28/2014
• Est. Priority Date: 01/31/2006
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Dai, James, Farago, Julia H., Menezes, Natala J., Naam, Ramaz, Sathe, Saleel, Williams, Hugh J.
• Primary Examiner(s): SYED, FARHAN M
• Application Number:
  US11/342,606
• Publication Number:
  US 20080235204A1
• Time in Patent Office: 3,192 Days
• US Class Current: 707/751
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation

Abstract

The invention discloses a system and method for managing feedback data that will be used for ranking search results. The invention can aggregate a plurality of user feedback data from more than one user into a search index. The user feedback data can be associated with one or more documents within the index such that the one or more documents can be ranked based on the type of feedback data that is aggregated. Once the documents have been ranked, the ranked documents can be provided to a requester.

Claims

1. A method of managing feedback data used to rank search results, comprising:

receiving, at a computing device, one or more elements of feedback data, the one or more elements of feedback data being in an unstructured format, wherein the one or more elements of feedback data includes textual comments describing a particular document;

associating the one or more elements of feedback data with one or more documents;

ranking the one or more documents based from the one or more elements of feedback data, wherein, when ranking the one or more documents, the feedback data is emphasized based on how often the one or more documents is indexed, the feedback data being emphasized more when the feedback data corresponds to a document that is indexed more frequently than other documents; and

providing the ranked one or more documents.

2. The method of claim 1, further comprising;

storing words from the textual comments and keywords describing the particular document in an index;

ranking the particular document based on the keywords and the textual comments, wherein the words from the textual comments are given more weight than the keywords when determining the ranking.

3. The method of claim 2, further comprising receiving the one or more elements of feedback data in an email.

4. The method of claim 1, wherein the feedback data is received verbally and converted into text.

5. A method for managing feedback data used for ranking search results, comprising:

receiving a search query;

identifying a plurality of documents that are responsive to the search query;

ranking the plurality of documents for relevance to the search query based on words within the plurality of documents and at least one element of feedback data, the feedback data being associated with at least one document, wherein a different weight is given in association with a word in the feedback data than a weight given in association with the word within the plurality of documents when ranking the plurality of documents;

providing the plurality of ranked documents.

6. The method according to claim 5, wherein the one or more elements of feedback data is received in a structured format.

7. The method according to claim 5, wherein the one or more elements of feedback data is received in an unstructured format, wherein the one or more elements of feedback data includes textual comments describing a particular document.

8. The method according to claim 7, wherein the method further includes retrieving the textual comments from a blog post.

9. The method according to claim 5, further comprising ranking the document by identifying the which section of a particular document an individual word came from.

10. The method according to claim 5, further comprising providing a staleness rate for the at least one element of feedback data, wherein the weight given the at least one element of feedback data decreases over time, thereby lessening a ranking impact of old feedback data.

11. The method according to claim 10, wherein the staleness rate is varied according to a crawl rate of at least one of the plurality of documents, wherein the crawl rate is a frequency with which data on the at least one of the plurality of documents is indexed.