Byungsoo Kim

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We develop a question answering system over linked data and text data. We combine knowledgebase-based question answering (KBQA) approach and information retrieval based question answering (IRQA) approach to solve complex questions. To solve this kind of complex question using only knowledgebase and SPARQL query, we use various methods to translate natural(More)
Previous studies in Open Information Extraction (Open IE) are mainly based on extraction patterns. They manually define patterns or automatically learn them from a large corpus. However, these approaches are limited when grasping the context of a sentence, and they fail to capture implicit relations. In this paper, we address this problem with the following(More)
This paper presents a multi-strategy and multi-source question answering (QA) system that can use multiple strategies to both answer natural language (NL) questions and respond to keywords. We use multiple information sources including curated knowledge base, raw text, auto-generated triples, and NL processing results. We develop open semantic answer type(More)
e-AIRS[1,2], an abbreviation of 'e-Science Aerospace Integrated Research System,' is a virtual organization designed to support aerodynamic flow analyses in aerospace engineering using the e-Science environment. As the first step toward a virtual aerospace engineering organization, e-AIRS intends to give a full support of aerodynamic research process.(More)
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