Ontology Based Thai Chatbot on Social Media Marketing for Community Enterprise
Sumitra Nuanmeesri1, Lap Poomhiran2
1Sumitra Nuanmeesri, Assistant Professor Department of Information Technology, Faculty of Science and Technology at Suan Sunandha Rajabhat University (SSRU), Bangkok, Thailand.
2Lap Poomhiran, student in Information Technology, Faculty of Information Technology, King Mongkut’s University of Technology North Bangkok (KMUTNB), Thailand. 

Manuscript received on November 12, 2019. | Revised Manuscript received on November 24 2019. | Manuscript published on 30 November, 2019. | PP: 10153-10158 | Volume-8 Issue-4, November 2019. | Retrieval Number: D4510118419/2019©BEIESP | DOI: 10.35940/ijrte.D4510.118419

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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Communicating with customers is the key to maintaining relationships so that customers are loyal to the business. But employees in the organization are unable to support or keep contact with the customer all day, especially for community enterprise with limited budgets. The chatbot is one of the tools that can increase the efficiency of automated communication with customers at all times. This paper presents Thai chatbot on social media marketing for community enterprise using the ontology technique. To develop a semi-automatic approach to create query terms and answers in different styles of response which is related to describe the features of online community product purchases for online buyers with community enterprise. The Longest matching approach was used to increase the capability of the Thai word segmentation, thus providing detailed and accurate information. The results show effectiveness and evaluation in terms of the accuracy of the classification and relationship of ontology and black box testing at the high-level while being used has high consensus both experts and users.
Keywords: Ontology, Word Segmentation, Semi-Automatic, Social Media, Q&A, Chatbot.
Scope of the Article: Big Data Analytics for Social Networking using IoT.