CookingQA: A question answering system based on cooking ontology

Riyanka Manna; Partha Pakray; Somnath Banerjee; Dipankar Das; Alexander Gelbukh

doi:10.1007/978-3-319-62434-1_6

CookingQA: A question answering system based on cooking ontology

Riyanka Manna, Partha Pakray, Somnath Banerjee, Dipankar Das, Alexander Gelbukh

Centro de Investigación en Computación (CIC)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

7 Scopus citations

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.

Original language	English
Title of host publication	Advances in Soft Computing - 15th Mexican International Conference on Artificial Intelligence, MICAI 2016, Proceedings
Editors	Oscar Herrera-Alcantara, Grigori Sidorov
Publisher	Springer Verlag
Pages	67-78
Number of pages	12
ISBN (Print)	9783319624334
DOIs	https://doi.org/10.1007/978-3-319-62434-1_6
State	Published - 2017
Event	15th Mexican International Conference on Artificial Intelligence, MICAI 2016 - Cancun, Mexico Duration: 23 Oct 2016 → 28 Oct 2016

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10061 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	15th Mexican International Conference on Artificial Intelligence, MICAI 2016
Country/Territory	Mexico
City	Cancun
Period	23/10/16 → 28/10/16

Access to Document

10.1007/978-3-319-62434-1_6

Cite this

Manna, R., Pakray, P., Banerjee, S., Das, D., & Gelbukh, A. (2017). CookingQA: A question answering system based on cooking ontology. In O. Herrera-Alcantara, & G. Sidorov (Eds.), Advances in Soft Computing - 15th Mexican International Conference on Artificial Intelligence, MICAI 2016, Proceedings (pp. 67-78). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10061 LNAI). Springer Verlag. https://doi.org/10.1007/978-3-319-62434-1_6

Manna, Riyanka ; Pakray, Partha ; Banerjee, Somnath et al. / CookingQA : A question answering system based on cooking ontology. Advances in Soft Computing - 15th Mexican International Conference on Artificial Intelligence, MICAI 2016, Proceedings. editor / Oscar Herrera-Alcantara ; Grigori Sidorov. Springer Verlag, 2017. pp. 67-78 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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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{\textquoteright}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.",

author = "Riyanka Manna and Partha Pakray and Somnath Banerjee and Dipankar Das and Alexander Gelbukh",

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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 O Herrera-Alcantara & G Sidorov (eds), Advances in Soft Computing - 15th Mexican International Conference on Artificial Intelligence, MICAI 2016, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10061 LNAI, Springer Verlag, pp. 67-78, 15th Mexican International Conference on Artificial Intelligence, MICAI 2016, Cancun, Mexico, 23/10/16. https://doi.org/10.1007/978-3-319-62434-1_6

CookingQA: A question answering system based on cooking ontology. / Manna, Riyanka; Pakray, Partha; Banerjee, Somnath et al.
Advances in Soft Computing - 15th Mexican International Conference on Artificial Intelligence, MICAI 2016, Proceedings. ed. / Oscar Herrera-Alcantara; Grigori Sidorov. Springer Verlag, 2017. p. 67-78 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10061 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

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T2 - 15th Mexican International Conference on Artificial Intelligence, MICAI 2016

AU - Manna, Riyanka

AU - Pakray, Partha

AU - Banerjee, Somnath

AU - Das, Dipankar

AU - Gelbukh, Alexander

PY - 2017

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N2 - 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.

AB - 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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DO - 10.1007/978-3-319-62434-1_6

M3 - Contribución a la conferencia

SN - 9783319624334

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 67

EP - 78

BT - Advances in Soft Computing - 15th Mexican International Conference on Artificial Intelligence, MICAI 2016, Proceedings

A2 - Herrera-Alcantara, Oscar

A2 - Sidorov, Grigori

PB - Springer Verlag

Y2 - 23 October 2016 through 28 October 2016

ER -

Manna R, Pakray P, Banerjee S, Das D, Gelbukh A. CookingQA: A question answering system based on cooking ontology. In Herrera-Alcantara O, Sidorov G, editors, Advances in Soft Computing - 15th Mexican International Conference on Artificial Intelligence, MICAI 2016, Proceedings. Springer Verlag. 2017. p. 67-78. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-62434-1_6

CookingQA: A question answering system based on cooking ontology

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