Google patent granted: Rank adjustments via click data
Google has this week been granted a patent for adjusting search rankings based on click data for related queries.
In plain English the patent explains that Google may be counting the number of people who search for “insurance” and then search for “confused.com”. Google can then analyse the queries and determine whether they are statistically significant enough for confused.com to be displayed in the rankings for “insurance”.
Rank-adjusted content items
Click logs and query logs are processed to identify statistical search patterns. A search session is compared to the statistical search patterns. Content items responsive to a query of the search session are identified, and a ranking of the content items is adjusted based on the comparison.
Inventors: Datar; Mayur (Santa Clara, CA), Dhamdhere; Kedar (Sunnyvale, CA), Garg; Ashutosh (Sunnyvale, CA)
Assignee: Google Inc. (Mountain View, CA)
Appl. No.: 11/694,268
Filed: March 30, 2007
Content items, e.g., video and/or audio files, web pages for particular subjects, news articles, etc., can be identified by a search engine in response to a query. The query can include one or more search terms, and the search engine can identify and rank the content items based on the search terms in the query. Typically the content items are displayed according to the rank.
The content items, however, are often identified only in response to a particular query, i.e., the search engine may identify and rank content items to independently for each query. For example, for three different queries, the search, engine may return a particular identification and rank of content items for each particular query, regardless of the other queries. In such implementations, a particular content item that may be highly relevant to a user’s current interests may not be identified and/or highly ranked and presented to the user until the user has conducted multiple searches. Additionally, other users may experience similar challenges when searching for content.
Disclosed herein are systems and methods of identifying content items. In one implementation, click logs and query logs are processed to identify statistical search patterns based on the click logs and query logs. A search session is compared to the statistical search patterns. Content items responsive to a query of the search session are identified, and a ranking of the content items is adjusted based on the comparison.
In another implementation, query paths and content terminuses associated with query paths are identified. Additionally, a context of a search session is identified and a determination of whether the context is related, to one or more of the query paths is made. Content items responsive to a query of the search session are identified based on the determination.
In another implementation, a system includes a mining engine and an adjusting engine. The mining engine mines click logs and query logs to identify query paths and content terminuses associated with the query paths. The adjusting engine adjusts a ranking of content items responsive to a search session query based on the identified query paths and content terminuses.
In one implementation, identification of a context of a search session facilitates the adjusting of a ranking of one or more content items in response to a search session query. The adjustment can, for example, be based on the likelihood that a current user is searching for the rank-adjusted content items because a statistically significant number of prior users that exhibited a similar behavior to the current user selected the rank-adjusted content items.