Towards a framework for trusting the automated learning of social ontologies
KSEM'10 Proceedings of the 4th international conference on Knowledge science, engineering and management
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Ontology engineering has been fully or partially practiced by knowledge engineers or knowledge workers, towards delivering either fully fledged conceptualizations of domains or providing lightweight ontology versions for less demanding but more frequent knowledge tasks. Domain-specific information can be shaped into ontologies either manually or (semi-)automatically using ontology learning techniques. The aim of the paper is to present a novice ontology learning approach that automatically constructs kick-off and useful ontologies from query logs. We place tasks related to the proposed learning approach in all phases of an ontology engineering life-cycle. By providing knowledge workers a useful kick-off ontology that is automatically built from “their needs (i. e. users’ search interests)” in order to address “their needs (i. e. use of the kick-off ontology to query data precisely)”, an approach that contributes as an incentive in the semantic content creation bottleneck is introduced.