STAIR: A System for Topical and Aggregated Information Retrieval

Abstract

Web content has exploded dramatically in the last decade and search is becoming increasingly com plex. In the current search paradigm, the user has to enter the query and is immediately presented results that are typically accessed sequentially. However, there are scenarios where the above model is not appropriate, either because results being in consumable form is more important than immediacy of results, or because the it is difficult and time consuming to navigate the results in sequential fashion. In this work, we describe the architecture, implementation and utility of STAIR- The System for Topical and Aggregated Information Retrieval, that uses a variant of focused crawling and retrieves just the relevant information from the web. We present a new interface that selects search results from different search engines, ranks the results and presents the most relevant results as an aggregated PDF document. User studies indicate that the relevance of the results produced by our approach is competitive with those of current search engines