Rekomendasi Anime dengan Latent Semantic Indexing Berbasis Sinopsis Genre

Abarja, Rudy Aditya and Toba, Hapnes (2015) Rekomendasi Anime dengan Latent Semantic Indexing Berbasis Sinopsis Genre. In: Seminar Teknik Informatika & Sistem Informasi, 9 April 2015, Bandung.

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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.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: information retrieval, latent semantic indexing, recommendation system, word co-occurences, anime
Subjects: T Technology > T Technology (General)
Depositing User: Perpustakaan Maranatha
Date Deposited: 26 Sep 2018 07:25
Last Modified: 26 Sep 2018 07:25

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