Novel Method for Mining Semantic Relationships for Entities in WIS

Extracting semantic relationships for entities in Web Integration Systems (WIS) is an important step for further analysis and decision-making tasks. For example, for a search query in WIS that contains a company name, we can not only return the descriptions of the company, but list companies that compete with it and also ones that cooperate with it. It is not rare that an entity pair has more than one semantic relationship. However, existing researches on relation extraction assume that one entity pair has only one semantic relationship. We propose a novel method to mine multi-semantic relationships for a giving entity in WIS. We first extract related entities and corresponding contexts from web texts, then propose a clustering algorithm to cluster the related entities into different subsets, where each subset represents a semantic relationship to the entity. We evaluate our method by comparing it with the state-of-theart approach using real-world dataset generated by search engine. The results show that the proposed approach is efficient in mining multi-semantic relationships for the giving entity from WIS.