Path search between concepts over a semantic network is an issue of great interest for many applications, such as explanation generation and query expansion. In this study a new approach is proposed, to guide navigation over a collaborative concept network, in order to discover path between concepts. The method uses a semantic heuristic based on proximity measures, which reflects the collective knowledge embedded in search engines. The experiments held on the Wikipedia network and Bing search engine on a range of different semantic measures show that the proposed approach outperforms state of the art search methods.

Heuristic semantic walk: Browsing a collaborative network with a search engine-based heuristic

MILANI, Alfredo
2013-01-01

Abstract

Path search between concepts over a semantic network is an issue of great interest for many applications, such as explanation generation and query expansion. In this study a new approach is proposed, to guide navigation over a collaborative concept network, in order to discover path between concepts. The method uses a semantic heuristic based on proximity measures, which reflects the collective knowledge embedded in search engines. The experiments held on the Wikipedia network and Bing search engine on a range of different semantic measures show that the proposed approach outperforms state of the art search methods.
2013
978-3-64-239648-9
Collaborative network
Data mining
Heuristics
Information extraction
Query expansion
Semantic similarity measures
heuristics
information extraction
query expansion
semantic similarity measures
collaborative network
data mining
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14085/43049
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