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A novel CNN-based method for Question Classification in Intelligent Question Answering

Published: 21 December 2018 Publication History

Abstract

Sentence classification, which is the foundation of the subsequent text-based processing, plays an important role in the intelligent question answering (IQA). Convolutional neural networks (CNN) as a kind of common architecture of deep learning, has been widely used to the sentence classification and achieved excellent performance in open field. However, the class imbalance problems and fuzzy sentence feature problem are common in IQA. With the aim to get better performance in IQA, this paper proposes a simple and effective method by increasing generalization and the diversity of sentence features based on simple CNN. In proposed method, the professional entities could be replaced by placeholders to improve the performance of generalization. And CNN reads sentence vectors from both forward and reverse directions to increase the diversity of sentence features. The testing results show that our methods can achieve better performance than many other complex CNN models. In addition, we apply our method in practice of IQA, and the results show the method is effective.

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  1. A novel CNN-based method for Question Classification in Intelligent Question Answering

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    cover image ACM Other conferences
    ACAI '18: Proceedings of the 2018 International Conference on Algorithms, Computing and Artificial Intelligence
    December 2018
    460 pages
    ISBN:9781450366250
    DOI:10.1145/3302425
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    • The Hong Kong Polytechnic: The Hong Kong Polytechnic University
    • City University of Hong Kong: City University of Hong Kong

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    New York, NY, United States

    Publication History

    Published: 21 December 2018

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    Author Tags

    1. Convolutional Neural Networks
    2. Intelligent Question Answering
    3. Question Classification

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    ACAI '18 Paper Acceptance Rate 76 of 192 submissions, 40%;
    Overall Acceptance Rate 173 of 395 submissions, 44%

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    Cited By

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    • (2024)TagRec++: Hierarchical Label Aware Attention Network for Question CategorizationIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2024.3354504(1-12)Online publication date: 2024
    • (2024)A Deep Learning model for Question Analysis in Low-resource Languages: A Dataset and Case Study for Persian2024 14th International Conference on Pattern Recognition Systems (ICPRS)10.1109/ICPRS62101.2024.10677830(1-7)Online publication date: 15-Jul-2024
    • (2024)KeyHierQC: Leveraging Keywords and Hierarchical Data for Enhanced Classification of Question Knowledge PointsAdvanced Intelligent Computing Technology and Applications10.1007/978-981-97-5663-6_36(427-438)Online publication date: 1-Aug-2024
    • (2024)Comparative Analysis of Large Language Models for Question Answering from Financial DocumentsCommunication and Intelligent Systems10.1007/978-981-97-2079-8_23(297-308)Online publication date: 11-May-2024
    • (2023)A Deep Learning Model for the Normalization of Institution Names by Multisource Literature Feature Fusion: Algorithm Development StudyJMIR Formative Research10.2196/474347(e47434)Online publication date: 18-Aug-2023
    • (2023)Performance Analysis of Machine Learning and Deep Learning Techniques for Answer Type extraction of Marathi Questions2023 5th Biennial International Conference on Nascent Technologies in Engineering (ICNTE)10.1109/ICNTE56631.2023.10146625(1-6)Online publication date: 20-Jan-2023
    • (2023)Instructor-assisted question classification system using machine learning algorithms with N-gram and weighting schemesDiscover Artificial Intelligence10.1007/s44163-023-00073-53:1Online publication date: 8-Aug-2023
    • (2023)FarsNewsQA: a deep learning-based question answering system for the Persian news articlesInformation Retrieval Journal10.1007/s10791-023-09417-226:1Online publication date: 19-Mar-2023
    • (2022)Building a Question Answering System for the Manufacturing DomainIEEE Access10.1109/ACCESS.2022.319167810(75816-75824)Online publication date: 2022
    • (2022)Transformer models used for text-based question answering systemsApplied Intelligence10.1007/s10489-022-04052-853:9(10602-10635)Online publication date: 20-Aug-2022
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