It’s getting pretty common for search engines to suggest query revisions when someone does a search these days.
One common query revision strategy is to look at the query sessions from previous searchers who used the same query, and see how they might have refined their searches, including spelling corrections, or adding and deleting words in subsequent queries during the same session.
A paper from Microsoft researchers, Query Suggestion based on User Landing Pages, takes that approach, and looks at using it in conjunction with another approach that looks at what they call “final landing pages.”
This poster investigates a novel query suggestion technique that selects query refinements through a combination of many users’ post-query navigation patterns and the query logs of a large search engine. We compare this technique, which uses the queries that retrieve in the top-ranked search results places where searchers end up after post-query browsing (i.e., the landing pages), with an approach based on query refinements from user search sessions extracted from query logs.