FAST: Friends Augmented Search Techniques - System Design & Data-Management Issues

Abstract

Improving web search solely based on algorithmic refinements has reached a plateau. The emerging generation of searching techniques tries to harness the ``wisdom of crowds'', using inputs from users in the spirit of Web 2.0. In this paper, we introduce a framework facilitating friends augmented search techniques (FAST). To that end, we present a browser add-on as front end for collaborative browsing and searching, supporting synchronous and asynchronous collaboration between users. We then describe the back end, a distributed key-value store for efficient information retrieval in the presence of an evolving knowledge base. The mechanisms we explore in supporting efficient query processing for FAST are applicable for many other recent Web 2.0 applications that rely on similar key-value stores. The specific collaborative search tool we present is expected to be an useful utility in its own right and spur further research on friends augmented search techniques, while the data-management techniques we developed are of general interest and applicability.