Media search broadening

• US 8,484,192 B1
• Filed: 04/30/2007
• Issued: 07/09/2013
• Est. Priority Date: 04/30/2007
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Sahami, Mehran, Gossweiler, Richard C. III, Patel, Manish G., Blackburn, John, Brown, David A., Gupta, Neha, Taylor, Thomas H.
• Primary Examiner(s): REYES, MARIELA D
• Application Number:
  US11/742,382
• Time in Patent Office: 2,262 Days
• Field of Search: 707/708, 707/765, 707/913
• US Class Current: 707/708
• CPC Class Codes: G06F 16/48 Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation

Abstract

A computer-implemented method includes receiving a search request at a central information provider, generating a query containing media-related terms relating to the search request, and submitting the query to a search engine having access to media-related search results, wherein the query is broader than the received search request, and transmitting media-related search results generated in response to the query by the search engine, to a remote device.

Claims

1. A computer-implemented method, comprising:

receiving at a central information provider a search request input by a user;

identifying one or more media-related terms in the search request that indicate that the search request is media-related and determining that the search request matches a first media-related category;

identifying a second media-related category that is different from the first media-related category and is based on the first media-related category, and determining, based on the second media-related category, one or more additional media-related terms;

in response to identifying the one or more media-related terms and the first and second media-related categories, and without receiving further input from the user about the search request, generating a query that is based on the search request and the one or more media-related terms in the search request and that additionally includes the one or more additional media-related terms that are not received from or selected by the user and that are related to the first and second media-related categories, and submitting the query to a search engine having access to media-related search results, wherein the query is broader than the received search request input by the user;

in response to determining that one or more search results, responsive to the submitted query, is media-related, generating code for formatting a display for the one or more media-related search results, the display comprising a list area that is adjacent to an electronic program guide grid, wherein;

(i) the list area displays (a) one or more icons that indicate that one or more search results is related to a television media program, (b) a media program identifier that identifies a name of a media program associated with one or more search results responsive to the submitted query, and (c) upcoming viewing times for one or more media programs associated with one or more search results responsive to the submitted query; and

(ii) the electronic program guide grid displays at least one of the media-related search results; and

transmitting the media-related search results, generated in response to the query by the search engine, to a remote device for presentation to the user in the generated format, wherein generating the query includes appending to the search request the one or more additional media-related terms.

2. The method of claim 1, wherein identifying the one or more media-related terms in the search request comprises comparing words or word groups in the search request to a media-related whitelist.

3. The method of claim 2, wherein identifying media-related terms in the search request comprises determining a distance between one or more terms in the search request and one or more terms in a graph of word and word group relationships in a machine learning system.

4. The method of claim 1, wherein the generated query submitted to the search engine includes terms relating to words or word groups in the search request joined by open-ended Boolean connectors.

5. The method of claim 1, wherein the search request is input by the user at and received from a general, non-media-specific, search engine page.

6. The method of claim 1, wherein generating the query comprises supplying one or more words or word groups to a machine learning system that has been trained on media-related content.

7. The method of claim 6, wherein the machine learning system includes a graph relating media-related words or word groups by normalized scores.

8. The method of claim 7, wherein generating the query comprises submitting one or more words included in the search request to a learning system to generate a context vector indicative of a relationship between the one or more words and media-related words in the graph.

9. A computer-implemented method, comprising:

receiving from a user a search request and submitting the search request to a central information provider;

identifying one or more media-related terms in the search request that indicate that the search request is media-related and determining that the search request matches a first media-related category;

identifying a second media-related category that is different from the first media-related category and is based on the first media-related category, and determining, based on the second media-related category, one or more additional media-related terms;

receiving in response to the search request media-related results that were generated by submitting a query to a search engine, wherein the query included one or more media-related terms that were not received from or selected by the user and that are based on the search request and that are related to the first and second media-related categories and was broader than the search request received from the user;

generating code for formatting a display for one or more media-related search results, the format comprising a list area that is adjacent to an electronic program guide grid, wherein;

(i) the list area displays (a) one or more icons that indicate that one or more search results is related to a television media program, (b) a media program identifier that identifies a name of a media program associated with one or more search results responsive to the submitted search request, and (c) upcoming viewing times for one or more media programs associated with one or more search results responsive to the submitted search request; and

(ii) the electronic program guide grid displays at least one of the media-related search results; and

generating a display of the search results in the generated format.

10. The method of claim 9, wherein the search request is submitted to a general, non-media-specific, search engine page.

11. The method of claim 9, wherein the response is produced by supplying one or more words or word groups to a machine learning system that has been trained on media-related content.

12. The method of claim 11, wherein the machine learning system includes a graph relating media-related words or word groups.

13. A computer-implemented system, comprising one or more computing devices including:

an interface programmed to receive search requests and to parse the search requests and to (i) identify one or more media-related terms in the search requests that indicate that the search requests are media-related, (ii) determine that the search request matches a first media-related category, (iii) identify a second media-related category that is different from the first media-related category and is based on the first media-related category, and (iv) determine, based on the second media-related category, one or more additional media-related terms, and (v) generate code for formatting a display for the one or more media-related search results, the display comprising a list area that is adjacent to an electronic program guide grid, wherein the list area displays (a) one or more icons that indicate that one or more search results is related to a television media program, (b) a media program identifier that identifies a name of a media program associated with one or more search results responsive to the submitted query, and (c) upcoming viewing times for one or more media programs associated with one or more search results responsive to the submitted query and the electronic program guide grid displays at least one of the media-related search results;

a search engine having access to one or more media-related search result indices; and

a query formatter to receive the parsed requests from the interface and, in response to parsed requests being identified as media-related, to add one or more additional media-related terms to the parsed requests to generate queries that are broader than the search requests, wherein the one or more media-related terms added to the parsed requests are related to the first and second media-related categories and were not included in the received search requests or selected by users that submitted the search requests.

14. The system of claim 13, wherein the query formatter is configured to pass an explicit media-related indicator to the search engine to cause the search engine to generate media-related search results.

15. The system of claim 13, further comprising a page formatter to generate code for the display of media-related search results responsive to the requests and electronic program guide grids showing media-related search results.

16. The method of claim 13, wherein the search request is received from a general, non-media-specific, search engine page.

17. The system of claim 13, further comprising a machine learning system trained on media-related content that is configured to receive portions of the search requests and generate terms that are similar to the portions of the search requests.

18. The system of claim 17, wherein the machine learning system includes a graph relating media-related words or word groups by normalized scores.