| Summary: | The emergence of Internet advertising brings about an economic and efficient marketing means for small and medium enterprises in service industries. Every day, massive service advertising information is published over the Internet. Nevertheless, on the other side, service consumers find it difficult to quickly and precisely retrieve their desired services. This problem is partly caused by the ubiquitous, heterogeneous, and ambiguous nature of online service advertising information. In this paper, we propose a systematic framework – UCOSAIS – for online service advertising information search. Inspired by the philosophy of user centered design, this framework comprises an ontology-learning-based focused crawler for service information discovery and classification, a faceted semantic search component for service concept selection, and a user-click-based similarity computing component for service concept ranking adjustment.
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