The growth of technology and sciences has greatly influenced the area of management and decision-making procedures, and has dramatically changed the decision-making processes in different levels, both quantitatively and qualitatively. Knowledge management plays a vital role in supporting enterprise learning, since it facilitates the effective collective intellect of the enterprise. Different methods for user-friendly knowledge access have been developed previously. The most sophisticated ones provide a simple text box for a query which takes Natural Language (NL) queries as input. Question Answering (QA) system is playing an important role in current search engine optimization. Natural language processing technique is mostly implemented in QA system for asking user's question and several steps are also followed for conversion of questions to query form for getting an exact answer. Query languages have complex syntax, requiring a good understanding of the representation schema, including knowledge of details like namespaces, class and property names. In this research we proposed an model to implement Conceptual Question Answering and Automatic Information Inferences for the enterprise's operational knowledge management in ontology-based learning organization.

Peer Reviewed