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Customer Service Automatic Answering System Based on Natural Language Processing

Published: 20 September 2019 Publication History

Abstract

With the rapid development of Internet, information grows explosively, and traditional search engine have failed to meet the needs of users. This paper proposes a customer service automatic answering system with a high-quality knowledge base. First of all, based on unsupervised learning algorithm, this system extracts the question and answer pairs from documents and store them in the knowledge base. Then employing semantic analysis module and the method of Natural Language Processing (NLP), this system gains the meaning of the customers' question accurately, then retrieve the knowledge base and return a high-resolution answer to the user. Furthermore, we construct a dialog management module, which makes reasonable guesses on issues that cannot be matched, and records the dialogue history so that the question-answering system can give more intelligent responses. Finally, due to the diversity of the document structure and the complexity of Chinese natural language, this system adds an edifying function that can add, delete, and modify the question and answer pair in the knowledge. Therefore, our customer service automatic answering system can be more intelligent and efficient than the existing question and answer system.

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Cited By

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  • (2022)Research on an Interactive Question Answering System of Artificial Intelligence Customer Service Based on Word2VecInternational Journal of e-Collaboration10.4018/IJeC.30404018:2(1-12)Online publication date: 1-Mar-2022
  • (2022)Learnings from a Pilot Hybrid Question Answering System: CQASProceedings of the 23rd Annual International Conference on Digital Government Research10.1145/3543434.3543661(437-439)Online publication date: 15-Jun-2022
  • (2021)Systematic Literature Review of Question Answering SystemsReliability and Statistics in Transportation and Communication10.1007/978-3-030-68476-1_5(54-62)Online publication date: 7-Feb-2021

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  1. Customer Service Automatic Answering System Based on Natural Language Processing

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    cover image ACM Other conferences
    SSPS '19: Proceedings of the 2019 International Symposium on Signal Processing Systems
    September 2019
    188 pages
    ISBN:9781450362412
    DOI:10.1145/3364908
    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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    • Beijing University of Posts and Telecommunications

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 20 September 2019

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    Author Tags

    1. Customer-service
    2. Natural Language Processing
    3. Question-answering system
    4. unsupervised learning algorithm

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    View all
    • (2022)Research on an Interactive Question Answering System of Artificial Intelligence Customer Service Based on Word2VecInternational Journal of e-Collaboration10.4018/IJeC.30404018:2(1-12)Online publication date: 1-Mar-2022
    • (2022)Learnings from a Pilot Hybrid Question Answering System: CQASProceedings of the 23rd Annual International Conference on Digital Government Research10.1145/3543434.3543661(437-439)Online publication date: 15-Jun-2022
    • (2021)Systematic Literature Review of Question Answering SystemsReliability and Statistics in Transportation and Communication10.1007/978-3-030-68476-1_5(54-62)Online publication date: 7-Feb-2021

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