One of the challenges in information retrieval is providing accurate answers to a user's question often expressed as uncertainty words. Most answers are based on a Syntactic approach rather than a Semantic analysis of the query. In this paper our objective is to present a hybrid approach for a Semantic question answering retrieval system using Ontology Similarity and Fuzzy logic. We use a Fuzzy Co-clustering algorithm to retrieve collection of documents based on Ontology Similarity. Fuzzy scale uses Fuzzy type-1 for documents and Fuzzy type-2 for words to prioritize answers. The objective of this work is to provide retrieval systems with more accurate answers than non-fuzzy Semantic Ontology approach. © Springer International Publishing Switzerland 2014.
CITATION STYLE
Rani, M., Muyeba, M. K., & Vyas, O. P. (2014). A hybrid approach using Ontology Similarity and Fuzzy logic for semantic question answering. In Smart Innovation, Systems and Technologies (Vol. 27, pp. 601–609). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-319-07353-8_69
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