ONTOLOGY-BASED SEMANTIC CHATBOT USING ALICE, AIML, AND SPARQL FOR E-COMMERCE CUSTOMER SERVICE
DOI:
https://doi.org/10.31849/navnn352Keywords:
Digital Marketing, Ontology, Semantic-Based Chatbot, SPARQL, Virtual Customer ServiceAbstract
The rapid development of the digital ecosystem in e-commerce has encouraged the adoption of artificial intelligence as a strategic solution to enhance customer service quality, particularly through the use of chatbots as virtual customer service agents. This study focuses on the development of a semantic-based chatbot implemented in the PineRoma Perfume Online Store, aiming to improve the system’s ability to understand the context and meaning of user queries related to perfume products, which are inherently subjective and context-dependent. The research employs a system development approach by integrating the Artificial Linguistic Internet Computer Entity (ALICE) and Artificial Intelligence Markup Language (AIML) to manage interaction patterns, combined with semantic ontology and SPARQL queries to support meaning-based information retrieval and knowledge expansion. The research stages include data collection and modeling, knowledge base design, chatbot implementation, and system evaluation through expert validation and precision testing. The results indicate that the developed chatbot is capable of responding to various user query variations in a relevant and contextual manner, achieving an average precision rate of 97% in supporting virtual customer service. These findings demonstrate that the implementation of a semantic-based chatbot contributes significantly to improving customer service quality and supports the effectiveness of digital marketing strategies in online retail environments.
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