Generating query refinements from user preference data

US9378247B1 · US · B1

Patent metadata
FieldValue
Publication numberUS-9378247-B1
Application numberUS-201414574081-A
CountryUS
Kind codeB1
Filing dateDec 17, 2014
Priority dateJun 5, 2009
Publication dateJun 28, 2016
Grant dateJun 28, 2016

How to read this patent

A practical reading order for non-experts. Skip the full description unless you need deep technical detail.

  1. Title

    What the patent document calls the invention.

  2. Abstract

    A short plain-language summary of the technical disclosure.

  3. Assignees and inventors

    Who owns or filed the patent and who is credited as inventor.

  4. Key dates

    Filing, priority, publication, and grant dates set the timeline.

  5. First independent claim

    The legal scope of protection — read this for what is actually claimed.

  6. CPC / IPC classifications

    Technology tags used to group this patent with similar filings.

  7. Citations and related patents

    Prior art links and similar publications in this corpus.

Abstract

Official abstract text for this publication.

Methods, systems, and apparatus, including computer program products, for generating query refinements from user preference data. A group of query pairs are obtained. Each query pair includes a first query and a second query. A quality score is determined for each query pair from user preference data for documents responsive to both the first and the second query. A diversity score is determined for each query pair having a quality score satisfying a quality threshold, the diversity score determined from user preference data for documents responsive to the second, but not the first, query. For each query pair having a quality score satisfying the quality threshold and a diversity score satisfying a diversity threshold, the second query of the query pair is associated with the first query of the query pair as a candidate refinement for the first query.

First claim

Opening claim text (preview).

What is claimed is: 1. A method comprising: obtaining a group of query pairs, each query pair including a first query and a second query; determining, using one or more computers, a quality score for each query pair in the group of query pairs from user preference data for documents responsive to both the first and the second query; determining a diversity score for each query pair in the group of query pairs having a quality score satisfying a quality threshold, the diversity score determined from user preference data for documents responsive to the second, but not the first, query; and associating, for each query pair having a quality score satisfying the quality threshold and a diversity score satisfying a diversity threshold, the second query of the query pair with the first query of the query pair as a candidate refinement for the first query, wherein the associating comprises: determining that the second query of the query pair contains a reference to a first geographic location, determining whether the first query contains a reference to a second geographic location, and associating the second query with the first query only if the first query contains a reference to the second geographic location. 2. The method of claim 1 , wherein the user preference data for documents responsive to both the first and the second query is obtained from user preference data generated based on actions of a group of users, the actions including submitted queries and results responsive to the queries that are selected by respective users. 3. The method of claim 1 , further comprising: selecting a group of candidate refinements associated with a candidate query, the group of candidate refinements ordered according to an order; processing one or more of the candidate refinements according to the order and determining, for at least one additional candidate refinement in the one or more processed candidate refinements, that the additional candidate refinement has an intra-suggestion diversity score satisfying an intra-suggestion diversity threshold, the intra-suggestion diversity score estimating diversity between a first group of top documents responsive to the additional candidate refinement and a group of seen documents; associating the additional candidate refinement with the candidate query as a confirmed refinement; and adding the first group of top documents to the group of seen documents. 4. The method of claim 3 , wherein the group of seen documents comprises one or more top documents responsive to a highly ranked candidate refinement in the group of candidate refinements. 5. The method of claim 4 , further comprising associating the highly ranked candidate refinement with the candidate query as a confirmed refinement for the candidate query. 6. The method of claim 3 , wherein the intra-suggestion diversity score is determined from quality of result statistics for a first plurality of documents as search results for the additional candidate refinement, wherein the first plurality of documents are not in the group of seen documents. 7. The method of claim 3 , wherein the group of candidate refinements are ordered based on quality scores for query pairs corresponding to the candidate query and the candidate refinements. 8. The method of claim 1 , wherein the quality score for each query pair is determined from second quality of result statistics for a second plurality of documents as search results for the second query in the query pair, the second plurality of documents being responsive to the first query in the query pair and the second query in the query pair. 9. The method of claim 1 , wherein the diversity score for each query pair is determined from third quality of result statistics for a third plurality of documents as search results for the second query in the query pair, wherein the third plurality of documents are responsive to the second query in the query pair, but are not included in a top number of search results responsive to the first query in the query pair. 10. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: obtaining a group of query pairs, each query pair including a first query and a second query; determining, using one or more computers, a quality score for each query pair in the group of query pairs from user preference data for documents responsive to both the first and the second query; determining a diversity score for each query pair in the group of query pairs having a quality score satisfying a quality threshold, the diversity score determined from user preference data for documents responsive to the second, but not the first, query; and associating, for each query pair having a quality score satisfying the quality threshold and a diversity score satisfying a diversity threshold, the second query of the query pair with the first query of the query pair as a candidate refinement for the first query, wherein the associating comprises: determining that the second query of the query pair contains a reference to a first geographic location, determining whether the first query contains a reference to a second geographic location, and associating the second query with the first query only if the first query contains a reference to the second geographic location. 11. The system of claim 10 , wherein the user preference data for documents responsive to both the first and the second query is obtained from user preference data generated based on actions of a group of users, the actions including submitted queries and results responsive to the queries that are selected by respective users. 12. The system of claim 10 , further operable to perform operations comprising: selecting a group of candidate refinements associated with a candidate query, the group of candidate refinements ordered according to an order; processing one or more of the candidate refinements according to the order and determining, for at least one additional candidate refinement in the one or more processed candidate refinements, that the additional candidate refinement has an intra-suggestion diversity score satisfying an intra-suggestion diversity threshold, the intra-suggestion diversity score estimating diversity between a first group of top documents responsive to the additional candidate refinement and a group of seen documents; associating the additional candidate refinement with the candidate query as a confirmed refinement; and adding the first group of top documents to the group of seen documents. 13. The system of claim 12 , wherein the group of seen documents comprises one or more top documents responsive to a highly ranked candidate refinement in the group of candidate refinements. 14. The system of claim 13 , further operable to perform operations comprising associating the highly ranked candidate refinement with the candidate query as a confirmed refinement for the candidate query. 15. The system of claim 12 , wherein the intra-suggestion diversity score is determined from quality of result statistics for a first plurality of documents as search results for the additional candidate refinement, wherein the first plurality of documents are not in the group of seen documents. 16. The system of claim 12 , wherein the group of candidate refinements are ordered based on quality scores for query pairs corresponding to the candidate query and the candidate refinements. 17. The system of claim

Assignees

Inventors

Classifications

Patent family

Related publications grouped by family.

External sources

Frequently asked questions

Answers are generated from the same data shown on this page.

What does patent US9378247B1 cover?
Methods, systems, and apparatus, including computer program products, for generating query refinements from user preference data. A group of query pairs are obtained. Each query pair includes a first query and a second query. A quality score is determined for each query pair from user preference data for documents responsive to both the first and the second query. A diversity score is determine…
Who is the assignee on this patent?
Google Inc
What technology area does this patent fall under?
Primary CPC classification G06F17/30522. Mapped technology areas include Physics.
When was this patent published?
Publication date Tue Jun 28 2016 00:00:00 GMT+0000 (Coordinated Universal Time) (B1). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 8 related publications on this page (citations in our corpus or others sharing the same primary CPC).