A Hybrid Approach using Ontology Similarity and Fuzzy Logic for Semantic Question Answering
Information Retrieval
2017-10-31 v2
Abstract
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 the collection of documents based on Ontology Similarity. The 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 system with more accurate answers than non-fuzzy Semantic Ontology approach.
Keywords
Cite
@article{arxiv.1709.09214,
title = {A Hybrid Approach using Ontology Similarity and Fuzzy Logic for Semantic Question Answering},
author = {Monika Rani and Maybin K. Muyeba and O. P. Vyas},
journal= {arXiv preprint arXiv:1709.09214},
year = {2017}
}