Association search in semantic web: search + inference

Authors:
Liang Bangyong;Tang Jie;Li Juanzi
Affiliations:
Tsinghua University, Beijing, China;Tsinghua University, Beijing, China;Tsinghua University, Beijing, China
Venue:
WWW '05 Special interest tracks and posters of the 14th international conference on World Wide Web
Year:
2005

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Abstract

Association search is to search for certain instances in semantic web and then make inferences from and about the instances we have found. In this paper, we propose the problem of association search and our preliminary solution for it using Bayesian network. We first minutely define the association search and its categorization. We then define tasks in association search. In terms of Bayesian network, we take ontology taxonomy as network structure in Bayesian network. We use the query log of instances to estimate the network parameters. After the Bayesian network is constructed, we give the solution for association search in the network.