Rekomendasi Anime dengan Latent Semantic Indexing Berbasis Sinopsis Genre
| Main Authors: | Abarja, Rudy Aditya, Toba, Hapnes |
|---|---|
| Format: | Proceeding PeerReviewed Book |
| Terbitan: |
, 2015
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| Subjects: | |
| Online Access: |
http://repository.maranatha.edu/24788/1/18.%20Rekomendasi%20Anime.pdf http://repository.maranatha.edu/24788/ |
Daftar Isi:
- Animes fans are sometimes hard to find suitable animes that match their needs since information about animes is very limited. In this research, a Latent Semantic Indexing (LSI)-based animes recommendation system is proposed. LSI is chosen since it has the ability to index shared words between various documents. Since users preferences are usually based on genre’s information, it is used for creating the connection between existing animes synopsis. The experiment results show that the usage of LSI based on genre information gives better accuracy than the traditional information retrieval method, i.e. the vector space model (VSM) with TF/IDF weighting.