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Learning to Find Interesting Connections in Wikipedia
Auteur(s)
Maison d'édition
: IEEE
Date de parution
2010-4-6
Résumé
To help users answer the question, what is the relation between (real world) entities or concepts, we might need to go well beyond the borders of traditional information retrieval systems. In this paper, we explore the possibility of exploiting the Wikipedia link graph as a knowledge base for finding interesting connections between two or more given concepts, described by Wikipedia articles. We use a modified Spreading Activation algorithm to identify connections between input concepts. The main challenge in our approach lies in assessing the strength of a relation defined by a link between articles. We propose two approaches for link weighting and evaluate their results with a user evaluation. Our results show a strong correlation between used weighting methods and user preferences; results indicate that the Wikipedia link graph can be used as valuable semantic resource.
Notes
, 2010
Nom de l'événement
APWEB'10: 12th International Asia-Pacific Web Conference
Lieu
Busan, Korea
Autre version
http://dx.doi.org/10.1109/APWeb.2010.62
Type de publication
Resource Types::text::conference output::conference proceedings::conference paper
