Automatic construction of domain ontology using dependence parsing patterns and WordNet similarity

Collecting useful knowledge from various sources and maintaining in a knowledge repository is a useful process for providing required information on demand with greater accuracy and efficiency. Domain ontology is considered as a set of candidate attributes used to model a domain concept of knowledge or discourse, which provides knowledge for both human users and system. Manually constructing domain ontology by extracting knowledge from enormous and cluttered documents would be tedious, difficult and time consuming task. In this paper we proposed a dependence parsing patterns based iterative algorithm for automatically extracting concept attributes and associations from web documents and Wikipedia documents. We evaluated the performance of our proposed method using manual evaluation done by domain experts. The performance of the proposed method is empirically proved by comparing with another well performing method.