Tourist Attraction Recommendation Based on Knowledge Graph
| Autor: | Weitao Zhang, Phatpicha Yochum, Liang Chang, Tianlong Gu, Zhu Manli |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Information retrieval
Scale (ratio) Computer science Feature vector Cosine similarity 02 engineering and technology Recommender system Field (computer science) Knowledge graph Tourist attraction 020204 information systems 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Tourism |
| Zdroj: | IFIP Advances in Information and Communication Technology ISBN: 9783030008277 Intelligent Information Processing |
| Popis: | This paper focuses on building recommendation model based on knowledge graph in the tourism field. A knowledge graph for tourist attractions in the Bangkok city is constructed, and a tourist attraction recommendation model based on the knowledge graph is presented. Firstly, we collect tourism data in Bangkok and generate a tourist attraction knowledge graph by using the Neo4j tool. Then, by applying the network representation learning method Node2Vec, we generate the feature vectors of both attractions and tourists, and calculate the correlation scores between tourists and attractions according to the cosine similarity. Finally, we normalize the correlation scores to generate the recommended list. This model presented in the paper can overcome the sparsity problem of tourist knowledge graphs and can be used in large scale knowledge graph. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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