Abstract
We present an approach to develop a Question Answering (QA) system over cooking recipes that makes use of Cooking Ontology management. QA systems are designed to satisfy the user’s specific information need whereas ontology is the conceptualization of knowledge and it exhibits the hierarchical structure. The system is an Information retrieval (IR) based system where the various tasks to be handled like question classification, answer pattern recognition, indexing, final answer generation. Our proposed QA System use Apache Lucene for document retrieval. All cooking related documents are indexed using Apache Lucene. Stop words are removed from each cooking related question and formed the query words which are identified to retrieve the most relevant document using Lucene. Relevant paragraphs are selected from the retrieved documents based on the tf-idf of the matching query words along with n-gram overlap of the paragraph with the original question. This paper also presents a way to develop an ontology model in such a way that the queries can be processed with the help of the ontology knowledge base and generate the exact answer.
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Manna, R., Pakray, P., Banerjee, S., Das, D., Gelbukh, A. (2017). CookingQA: A Question Answering System Based on Cooking Ontology. In: Sidorov, G., Herrera-Alcántara, O. (eds) Advances in Computational Intelligence. MICAI 2016. Lecture Notes in Computer Science(), vol 10061. Springer, Cham. https://doi.org/10.1007/978-3-319-62434-1_6
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