DocumentCode :
3635551
Title :
Learning to Find Interesting Connections in Wikipedia
Author :
Marek Ciglan;Étienne Rivière;Kjetil Nørvåg
Author_Institution :
Dept. of Comput. &
fYear :
2010
Firstpage :
243
Lastpage :
249
Abstract :
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.
Keywords :
"Wikipedia","Information retrieval","Computer science","Information science","Collaboration","Natural language processing","Ontologies","Buildings","Dinosaurs","Algorithm design and analysis"
Publisher :
ieee
Conference_Titel :
Web Conference (APWEB), 2010 12th International Asia-Pacific
Print_ISBN :
978-1-4244-6599-6;978-1-7695-4012-2
Type :
conf
DOI :
10.1109/APWeb.2010.62
Filename :
5474131
Link To Document :
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