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Emerging Technologies of Natural Language-Enabled Chatbots: A Review and Trend Forecast Using Intelligent Ontology Extraction and Patent Analytics

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  • Min-Hua Chao
  • Amy J. C. Trappey
  • Chun-Ting Wu
  • Abd E.I.-Baset Hassanien

Abstract

Natural language processing (NLP) is a critical part of the digital transformation. NLP enables user-friendly interactions between machine and human by making computers understand human languages. Intelligent chatbot is an essential application of NLP to allow understanding of users’ utterance and responding in understandable sentences for specific applications simulating human-to-human conversations and interactions for problem solving or Q&As. This research studies emerging technologies for NLP-enabled intelligent chatbot development using a systematic patent analytic approach. Some intelligent text-mining techniques are applied, including document term frequency analysis for key terminology extractions, clustering method for identifying the subdomains, and Latent Dirichlet Allocation for finding the key topics of patent set. This research utilizes the Derwent Innovation database as the main source for global intelligent chatbot patent retrievals.

Suggested Citation

  • Min-Hua Chao & Amy J. C. Trappey & Chun-Ting Wu & Abd E.I.-Baset Hassanien, 2021. "Emerging Technologies of Natural Language-Enabled Chatbots: A Review and Trend Forecast Using Intelligent Ontology Extraction and Patent Analytics," Complexity, Hindawi, vol. 2021, pages 1-26, May.
    • Handle: RePEc:hin:complx:5511866
    DOI: 10.1155/2021/5511866
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    Cited by:

    1. Massaro, Alessandro & Magaletti, Nicola & Cosoli, Gabriele & Giardinelli, Vito & Leogrande, Angelo, 2022. "Text Mining Approaches Oriented on Customer Care Efficiency," MPRA Paper 112244, University Library of Munich, Germany.

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