Ontology Equipped Natural Language Processing for Real World Applications

Natural language processing is an area of artificial intelligence that defines a set of methods and techniques used to automate the translation process between computers and humans or mediate the human-machine communication. NLP focuses on developing systems that allow computers to communicate with people using everyday language and also concerns how computational methods can aid the understanding of human language. To make this possible, NLP has to define a communication format and software able to analyze, understand and give appropriate response. For the communication level, a formal representation of the knowledge is needed that can be represented by ontology. Ontology represents knowledge in a formal model based on conceptualization. This paper has threefold objective. Firstly, it defines ontology as a concept based model to represent objects, concepts, entities and relations that exist between objects. Users’ access to information and the presentation of information to users are both mediated via natural language, and the ontology used in the reasoning component is coupled with the lexicon used in the natural language component. Secondly, it throws light on ontology framework that is based on the resource description framework (i.e. defines ontology metadata) and classification of ontology languages. Thirdly, it focuses on role of ontology in natural language processing applications viz. Knowledge representation, semantic annotation and conceptual indexing along with various advantages and disadvantages. Keywords— Artificial Intelligence, Natural Language Processing, Ontology, Resource Description Framework, Semantic Web.