Domain Hyponymy Hierarchy Discovery by Iterative Web Searching and Inferable Semantics Based Concept Selecting

The hyponymy hierarchy is an essential part of domain knowledge, which is widely used in many applications. With the development of the Internet, the World Wide Web is now an invaluable resource of hyponymy discovering. However, acquiring domain hyponymy hierarchy from the web is still a low efficient work, because the hyponymy acquiring process is often disturbed by numerous irrelevant terms. In this paper, we propose a new iterative domain hyponymy hierarchy discovering method, where irrelevant terms can be eliminated automatically by inferable semantic information. Our approach is evaluated by the experiments in two programming-related domains. The results show that our approach works well.