Find-similar: similarity browsing as a search tool

Search systems have for some time provided users with the ability to request documents similar to a given document. Interfaces provide this feature via a link or button for each document in the search results. We call this feature findsimilar or similarity browsing. We examined find-similar as a search tool, like relevance feedback, for improving retrieval performance. Our investigation focused on find-similar’s document-to-document similarity, the reexamination of documents during a search, and the user’s browsing pattern. Find-similar with a query-biased similarity, avoiding the reexamination of documents, and a breadth-like browsing pattern achieved a 23% increase in the arithmetic mean average precision and a 66% increase in the geometric mean average precision over our baseline retrieval. This performance matched that of a more traditionally styled iterative relevance feedback technique. Categories and Subject Descriptors H.3.3 [Information Storage and Retrieval]: Informat...

• Type: Conference
• Year: 2006
• Where: SIGIR
• Authors: Mark D. Smucker, James Allan
• Keywords: Mean Average Precision, Relevance Feedback, SIGIR 2006, Similarity Browsing