An Ontology-Driven Question Answering System for Computer Network Module

Abstract

Data is found everywhere around us. Furthermore, these data are commonly found in structured, semi-structured and unstructured formats. Data are used in our daily lives in a variety of ways. Various search engines are used to search and retrieve the data we need. However, instead of search engines giving accurate and precise answers to the user queries, they often returned the list of links. Then, the user clicks on each link one by one to get the answer he wants. This method of searching can sometimes not giving the precise answers to the user queries, or the user may have to spend more time in searching for the answer, and hence the users may experience discomfort. This situation can be avoided by using the semantic concept. The normal web data are machinereadable and can be understood by humans, whereas the semantic web information are machinereadable and understandable. Semantic web technologies are often used to create data stores, build vocabularies, and write rules for manipulating data. Ontology is the main component of the semantic web. Ontology can be described as the structure of knowledge-representation of a particular domain or subject. It clearly describes concepts, roles, instances, and the relationships between them. The Question Answering System (QAS) is used to extract the exact and precise answer to the user queries from the data repository. The system can be developed using different techniques like NLP with IR, reasoning with the NLP, web-based QAS, ontology-based QAS, and more. This particular question answering system is developed using the ontology model. This ontology-driven question answering (QA) system provides the facility to the students for finding accurate answers to their queries. Teachers also can use this system to assess the knowledge and skill of students whenever they want. This QA system mainly focuses to apply in the education domain especially in ICT subject areas. It defines a set of questions and relevant answers which are organized in a structured way with the help of Natural Language Processing (NLP).