
Recommendation for movies can help discover new and enjoyable movies. This study uses the Neo4j Graph Database to create a recommendation system using the Netflix Movie Dataset. The objective of this research is the development of a movie recommendation algorithm using the k-NN similarity algorithm and FastRP node embedding machine learning. The results have provided recommendations based on similar attributes, such as actors, directors, country, type, and rating.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
