Paper Info
Title
Using and Evaluating User Directed Summaries to Improve Information Access
Abstract
Textual information available has grown so much as to make necessary to study new techniques that assist users in information access (IA). In this paper, we propose utilizing a user directed summarization system in an IA setting for helping users to decide about document relevance. The summaries are generated using a sentence extraction method that scores the sentences performing some heuristics employed successfully in previous works (keywords, title and location). User modeling is carried out exploiting user's query to an IA system and expanding query terms using WordNet. We present an objective and systematic evaluation method oriented to measure the summary effectiveness in two IA significant tasks: ad hoc retrieval and relevance feedback. Results obtained prove our initial hypothesis, i.e., user adapted summaries are a useful tool assisting users in an IA context.
Year
DOI
Venue
1999
10.1007/3-540-48155-9_14
ECDL3
Keywords
Field
DocType
ia system,user modeling,ia setting,ia significant task,improve information access,ia context,sentence extraction method,information access,user directed summaries,query term,document relevance,relevance feedback,user model
Automatic summarization,World Wide Web,Relevance feedback,Query expansion,Information retrieval,Computer science,Information access,Heuristics,Sentence extraction,User modeling,WordNet
Conference
ISBN
Citations 
PageRank 
3-540-66558-7
11
1.66
References 
Authors
17
3
Name
Order
Citations
PageRank
Manuel Maña López110614.57
Manuel De Buenaga Rodríguez26716.59
José María Gómez Hidalgo322524.70