Intelligent methods for information access in context: The role of topic descriptors and discriminators

Successful access to information sources on the Web depends on effective methods for identifying the needs of a user and making relevant information resources available when needed. This paper formulates a theoretical framework for the study of context-drivenWeb search and proposes new methods for l...

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Detalles Bibliográficos
Autores principales: Cecchini, Rocío L., Maguitman, Ana Gabriela, Lorenzetti, Carlos M.
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2007
Materias:
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/23581
Aporte de:
id I19-R120-10915-23581
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
Informática
context modeling
information retrieval
Information Search and Retrieval
Web-based interaction
Value of information
Frameworks
spellingShingle Ciencias Informáticas
Informática
context modeling
information retrieval
Information Search and Retrieval
Web-based interaction
Value of information
Frameworks
Cecchini, Rocío L.
Maguitman, Ana Gabriela
Lorenzetti, Carlos M.
Intelligent methods for information access in context: The role of topic descriptors and discriminators
topic_facet Ciencias Informáticas
Informática
context modeling
information retrieval
Information Search and Retrieval
Web-based interaction
Value of information
Frameworks
description Successful access to information sources on the Web depends on effective methods for identifying the needs of a user and making relevant information resources available when needed. This paper formulates a theoretical framework for the study of context-drivenWeb search and proposes new methods for learning query terms based on the user task. These methods use an incrementally-retrieved, topic-dependent selection of Web documents for term-weight reinforcement reflecting the aptness of the terms in describing and discriminating the topic of the user context. Based on this framework, we propose an incremental search algorithm for information retrieval agents that has the potential to improve significantly over the traditional IR techniques. The new algorithm learns new descriptors by searching for terms that tend to occur often in relevant documents, and learns good discriminators by identifying terms that tend to occur only in the context of the given topic. We discuss the technical challenges posed by this new framework, outline our agent system architecture, and present an evaluation of the proposed techniques.
format Objeto de conferencia
Objeto de conferencia
author Cecchini, Rocío L.
Maguitman, Ana Gabriela
Lorenzetti, Carlos M.
author_facet Cecchini, Rocío L.
Maguitman, Ana Gabriela
Lorenzetti, Carlos M.
author_sort Cecchini, Rocío L.
title Intelligent methods for information access in context: The role of topic descriptors and discriminators
title_short Intelligent methods for information access in context: The role of topic descriptors and discriminators
title_full Intelligent methods for information access in context: The role of topic descriptors and discriminators
title_fullStr Intelligent methods for information access in context: The role of topic descriptors and discriminators
title_full_unstemmed Intelligent methods for information access in context: The role of topic descriptors and discriminators
title_sort intelligent methods for information access in context: the role of topic descriptors and discriminators
publishDate 2007
url http://sedici.unlp.edu.ar/handle/10915/23581
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