earticle

영어

The tremendous development in information technology led to an explosion of data and motivated the need for powerful yet efficient strategies for data mining and knowledge discovery. Question Answering (QA) systems made it possible to ask questions and retrieve answers using natural language (NL) queries, rather than the keyword-based retrieval mechanisms used by current search engines. In Ontology-based QA system, the knowledge based data, where the answers are sought, has a structured organization. The question-answer retrieval of ontology knowledge base provides a convenient way to obtain knowledge for use, but the natural language need to be mapped to the query statement of ontology. QASYO is a sentence level question-answering system that integrates natural language processing, ontologies and information retrieval technologies in a unified framework. It accepts queries expressed in natural language and YAGO ontology as inputs and provides answers drawn from the available semantic markup. QASYO combines several powerful techniques in a novel way to make sense of NL queries and to map them to semantic markup. Semantic analysis of questions is performed in order to extract keywords used in the retrieval queries and to detect the expected answer type. In this paper we describe the current version of the system, in particular discussing its reasoning capabilities, and Performance.