Customer Service Automatic Answering System Based on Natural Language Processing

被引:4
|
作者
Gong, Xia [1 ]
Kong, Xiangyi [2 ]
Zhang, Zhujun [1 ]
Tan, Lin [3 ]
Zhang, Zixiong [1 ]
Shao, Bing [1 ]
机构
[1] Beihang Univ, Beijing 100191, Peoples R China
[2] Beijing Inst Technol, Beijing 100081, Peoples R China
[3] Beijing Foreign Studies Univ, Beijing 100089, Peoples R China
关键词
Natural Language Processing; unsupervised learning algorithm; Question-answering system; Customer-service; EXTRACTION;
D O I
10.1145/3364908.3365286
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:115 / 120
页数:6
相关论文
共 50 条
  • [1] Customer Service Assist System based on Natural Language Processing
    Department of Electrical Engineering, Kwangwoon University, Seoul
    01897, Korea, Republic of
    不详
    [J]. IEIE Trans. Smart Process Comput., 2022, 4 (248-254): : 248 - 254
  • [2] Intelligent Customer Service System Design Based on Natural Language Processing
    Wang Yijing
    [J]. 2018 5TH INTERNATIONAL CONFERENCE ON ELECTRICAL & ELECTRONICS ENGINEERING AND COMPUTER SCIENCE (ICEEECS 2018), 2018, : 374 - 379
  • [3] Shallow Parsing Natural Language Processing Implementation for Intelligent Automatic Customer Service System
    Antares, Ahmad Eries
    Kusnadi, Adhi
    Iswari, Ni Made Satvika
    [J]. 2014 INTERNATIONAL CONFERENCE ON ADVANCED COMPUTER SCIENCE AND INFORMATION SYSTEMS (ICACSIS), 2014, : 274 - 279
  • [4] Question-Answering System Design in Teaching and Learning, Based on Natural Language Processing
    Wang Ming
    Yuan Dachao
    [J]. PROCEEDINGS OF THE FOURTH NORTHEAST ASIA INTERNATIONAL SYMPOSIUM ON LANGUAGE, LITERATURE AND TRANSLATION, 2015, 2015, : 132 - 137
  • [5] Research on Computer Natural Language Processing Intelligent Question Answering System Based on Knowledge Graph
    Zhan, Liuchun
    Huang, Changjiang
    [J]. PROCEEDINGS OF 2024 INTERNATIONAL CONFERENCE ON MACHINE INTELLIGENCE AND DIGITAL APPLICATIONS, MIDA2024, 2024, : 70 - 74
  • [6] Customer satisfaction and natural language processing
    Piris, Yolande
    Gay, Anne-Cecile
    [J]. JOURNAL OF BUSINESS RESEARCH, 2021, 124 : 264 - 271
  • [7] A Multiple Ontologies Based System for Answering Natural Language Questions
    El-Ansari, Anas
    Beni-Hssane, Abderrahim
    Saadi, Mostafa
    [J]. EUROPE AND MENA COOPERATION ADVANCES IN INFORMATION AND COMMUNICATION TECHNOLOGIES, 2017, 520 : 177 - 186
  • [8] DBpedia and YAGO Based System for Answering Questions in Natural Language
    Boinski, Tomasz
    Szymanski, Julian
    Dudek, Bartlomiej
    Zalewski, Pawel
    Dompke, Szymon
    Czarnecka, Maria
    [J]. COMPUTATIONAL COLLECTIVE INTELLIGENCE, ICCCI 2018, PT I, 2018, 11055 : 383 - 392
  • [9] A SURVEY OF QUESTION ANSWERING IN NATURAL-LANGUAGE PROCESSING
    WERMTER, S
    LEHNERT, WG
    [J]. POETICS, 1990, 19 (1-2) : 99 - 120
  • [10] Natural Language Processing based Visual Question Answering Efficient: an EfficientDet Approach
    Gupta, Rahul
    Hooda, P. Arikshit
    Sanjeev
    Chikkara, Nikhil Kumar
    [J]. PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTING AND CONTROL SYSTEMS (ICICCS 2020), 2020, : 900 - 904