摘要:Web searching techniques have been investigated and implemented in many
aspects.Particularly, in case of personalization, more important issue is how to
manipulate the results retrieved from search engines for better user
understandability and satisfaction. Such manipula-tion processes are i)
ranking the results in accordance with user relevance, and ii)
exchangingthe results between users who have similar tastes. Thus, our work has
been mainly focusing on relevance-based ranking mechanism as well as sharing
schemes for the results retrieved from het-erogeneous web information sources.
In this paper, we propose a hybrid model for meta search agent systems with
three main functionalities, i.e., i) URL filtering method for
preprocessing, ii) tag-based information conceptualization scheme for
ranking, and iii ) ontology-based stan-dardization scheme for sharing. It
means that the proposed meta search agent model exploits semantized tags to
formalize and share heterogeneous information obtained from multiple
searchengines and to finally maintain the shared information. Within the
tag-based information space, a conceptual distance between retrieval interest
and search results can be efficiently computed. Byconducting some
experimentations, we have shown the semantized tag model can conceptualize the
retrieved results, and make them sharable. We also compare performance of the
proposedsystem with hyperlink-based methodologies.
关键词:information searching, meta searching, ontology, semantiization