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Automatic construction of a large-scale situation ontology by mining how-to instructions from the web

by: Yuchul Jung, Jihee Ryu, Kyung M. Kim, Sung H. Myaeng
Web Semant., Vol. 8, No. 2-3. (July 2010), pp. 110-124, doi:10.1016/j.websem.2010.04.006  Key: citeulike:11494988

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Abstract

With the growing interests in semantic web services and context-aware computing, the importance of ontologies, which enable us to perform context-aware reasoning, has been accepted widely. While domain-specific and general-purpose ontologies have been developed, few attempts have been made for a situation ontology that can be employed directly to support activity-oriented context-aware services. In this paper, we propose an approach to automatically constructing a large-scale situation ontology by mining large-scale web resources, eHow and wikiHow, which contain an enormous amount of how-to instructions (e.g., ”How to install a car amplifier”). The construction process is guided by a situation model derived from the procedural knowledge available in the web resources. Two major steps involved are: (1) action mining that extracts pairs of a verb and its ingredient (i.e., objects, location, and time) from individual instructional steps (e.g., ) and forms goal-oriented situation cases using the results and (2) normalization and integration of situation cases to form the situation ontology. For validation, we measure accuracy of the action mining method and show how our situation ontology compares in terms of coverage with existing large-scale ontology-like resources constructed manually. Furthermore, we show how it can be utilized for two applications: service recommendation and service composition.


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