Utilizing GP 2 for Restaurant Recommendation

Authors

  • Nitamayega Telkom University
  • Gia Septiana Wulandari Telkom University
  • Kemas Rahmat Saleh Wiharja Telkom University

DOI:

https://doi.org/10.34818/INDOJC.2024.9.1.907

Keywords:

GP 2, knowledge graph, recommender system, restaurant recommendation

Abstract

The increasing diversity of food and beverage providers poses a challenge for people to find a restaurant that aligns with their preferences. Restaurant recommendation systems can address this problem by providing accurate and relevant suggestions. Although there are many previous studies have explored various recommendation methodologies, the utilization of knowledge graph implemented with GP 2 is still limited. Knowledge graphs can represent complex information in a structured way, while GP 2 is a graph-specific programming language that has a simple syntax. This research focuses on the implementation of a knowledge graph-based restaurant recommendation system with GP 2. The recommendation scheme built can provide the best accuracy, reaching 84.97%. This shows that the knowledge graph-based restaurant recommendation system with GP 2 can demonstrate the effectiveness of the system in providing accurate and relevant recommendations, showing the potential of knowledge graph and GP 2 for the development of recommendation systems in the future and being an effective solution to overcome recommendation problems.

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Published

2024-05-13

How to Cite

Nitamayega, Gia Septiana Wulandari, & Kemas Rahmat Saleh Wiharja. (2024). Utilizing GP 2 for Restaurant Recommendation. Indonesian Journal on Computing (Indo-JC), 9(1), 8–19. https://doi.org/10.34818/INDOJC.2024.9.1.907

Issue

Vol. 9 No. 1 (2024): April, 2024

Section

Computer Science

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