An Approach to Automatically Constructing Domain Ontology

摘要

In this paper we present an approach to mining domain-dependent ontologies using term extraction and relationship discovery technology. There are two main innovations in our approach. One is extracting terms using log-likelihood ratio, which is based on the contrastive probability of term occurrence in domain corpus and background corpus. The other is fusing together information from multiple knowledge sources as evidences for discovering particular semantic relationships among terms. In the experiment, we also improve the traditional k-mediods algorithm for multi-level clustering. We have applied our approach to produce an ontology for the domain of computer science and obtained promising results.