Successfully retrieving a web document is a twofold problem: having an adequate query that can usefully and properly help filtering relevant documents from huge collections, and presenting the user those that may indeed fulfill his/her needs. In this paper, we focus on the first issue -the problem of having a misleading user query. The aim of the work is to refine a query by using extracts instead of full documents. Extracts, in our context, are actually summaries of documents of a hitlist produced by an extractive automatic summarizer. Automatic summarization of single and multi-documents is explored through GistSumm, our Gist Summarizer, which is based on the gist of a document, hence its name. Results on pseudo-relevance feedback for the Portuguese CHAVE collection show that gist-based extracts may improve information retrieval.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.