Optimisation using Natural Language Processing: Personalized Tour Recommendation for Museums
This paper proposes a new method to provide personalized tour recommendation for museum visits. It combines an optimization of preference criteria of visitors with an automatic extraction of artwork importance from museum information based on Natural Language Processing using textual energy. This project includes researchers from computer and social sciences. Some results are obtained with numerical experiments. They show that our model clearly improves the satisfaction of the visitor who follows the proposed tour. This work foreshadows some interesting outcomes and applications about on-demand personalized visit of museums in a very near future.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
User Preferential Tour Recommendation Based on POI-Embedding Methods
Tour itinerary planning and recommendation are challenging tasks for tourists in unfamiliar countries. Many tour recommenders only consider broad POI categories and do not align well with users' preferences and other loc…
BTRec: BERT-Based Trajectory Recommendation for Personalized Tours
An essential task for tourists having a pleasant holiday is to have a well-planned itinerary with relevant recommendations, especially when visiting unfamiliar cities. Many tour recommendation tools only take into accoun…
Language ModellingSentenceSentence CompletionPOIBERT: A Transformer-based Model for the Tour Recommendation Problem
Tour itinerary planning and recommendation are challenging problems for tourists visiting unfamiliar cities. Many tour recommendation algorithms only consider factors such as the location and popularity of Points of Inte…
Language ModelingLanguage ModellingSentenceSentence CompletionRAG-Optimized Tibetan Tourism LLMs: Enhancing Accuracy and Personalization
With the development of the modern social economy, tourism has become an important way to meet people's spiritual needs, bringing development opportunities to the tourism industry. However, existing large language models…
HallucinationRAGRetrievalRetrieval-augmented GenerationPersonalized LLM Response Generation with Parameterized Memory Injection
Large Language Models (LLMs) have exhibited remarkable proficiency in comprehending and generating natural language. On the other hand, personalized LLM response generation holds the potential to offer substantial benefi…
Bayesian Optimisationparameter-efficient fine-tuningResponse Generation