Algorithms for recollection of search terms based on the Wikipedia category structure

The common user interface for a search engine consists of a text field where the user can enter queries consisting of one or more keywords. Keyword query based search engines work well when the users have a clear vision what they are looking for and are capable of articulating their query using the same terms as indexed. For our multimedia database containing 202,868 items with text descriptions, we supplement such a search engine with a category-based interface whose category structure is tailored to the content of the database. This facilitates browsing and offers the users the possibility to look for named entities, even if they forgot their names. We demonstrate that this approach allows users who fail to recollect the name of named entities to retrieve data with little effort. In all our experiments, it takes 1 query on a category and on average 2.49 clicks, compared to 5.68 queries on the database's traditional text search engine for a 68.3% success probability or 6.01 queries when the user also turns to Google, for a 97.1% success probability.