How May Click and Query Log Patterns Influence Search Results?
Imagine that many people use Google to perform a search for “orange,” and then “banana,” and then “pineapple,” and then choose the web page “http://www.example.com/fruit.htm” in the search results they see.
Now imagine that Google looks at the information it collects about what people do when they search, and finds click and query log patterns showing that there are a large number, a statistically significant number, of people who search for “orange,” and then “banana,” and then “pineapple,” or possibly the same search terms in a slightly different order. They tend to click on “http://www.example.com/fruit.htm.”
Google may also notice in query logs that people are looking for some very related terms during query sessions, such as consecutive searches for “banana,” “an apple,” and “pineapple.”
Since this second set of queries for “banana,” “an apple,” and “pineapple,” is so similar to the query sessions that contained the search terms “orange” and “banana” and “pineapple,” where people were choosing the page “http://www.example.com/fruit.htm,” Google may choose to adjust the ranking for “http://www.example.com/fruit.htm,” for people using those very related terms in their search sessions.
Google was granted a patent on this query log patterns process this past week:
Rank-adjusted content items
Invented by Mayur Datar, Kedar Dhamdhere, and Ashutosh Garg
Assigned to Google
US Patent 7,610,282
Granted October 27, 2009
Filed March 30, 2007
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.
Query Log patterns can be of great value to search engines since they can be used to see what visitors to the search engine are performing.