Mining query-logs towards learning useful kick-off ontologies: an incentive to semantic web content creation Online publication date: Sat, 07-Mar-2015
by Konstantinos Kotis, Andreas Papasalouros, Manolis Maragoudakis
International Journal of Knowledge Engineering and Data Mining (IJKEDM), Vol. 1, No. 4, 2011
Abstract: The aim of the paper is to present an ontology learning method that automatically (unsupervised) builds useful kick-off ontologies from query logs. We introduce tasks related to the proposed method in all phases of an ontology engineering lifecycle, extending human-centred and collaborative engineering methodologies for devising continuously evolving ontologies such as the human centred ontology engineering methodology (HCOME). Users, both knowledge workers of an organisational knowledge management setting and WWW users, are provided with a useful kick-off ontology that is automatically built from users' search interests in order to meet ontology engineering and ontology-based application needs. The paper provides evidences that this new approach plays a significant role as an incentive in the semantic content creation bottleneck.
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