An assessment on domain ontology-based information extraction techniques

Abstract

Domain ontology is used in information retrieval to retrieve more relevant information from a collection of unstructured information source. Information retrieval is becoming an important research area in the field of computer science. Information retrieval (IR) is generally concerned with the searching and retrieving of knowledge-based information from database. In this paper, we represent the various models and techniques for information retrieval. Domain ontology is a description of domain concepts with relation and properties to be used in knowledge engineering as a knowledge base. In this paper, various domain ontology-based information retrieval methods have been reviewed. A comparative analysis is made on all the available methods, which will allow the analyst to choose the suitable domain ontology-based information extraction method. There are various methods developed to make the information extraction more efficient. The methods have been classified as Boolean, vector space, semantic-based techniques and probabilistic. Semantic-based information retrieval can still be classified as semantic association, semantic similarity and semantic annotation. This assessment allows the developer to choose the best fit model for their requirement in an efficient way.