Tell Me What You Want: Embedding Narratives for Movie Recommendations
Recommender systems are efficient exploration tools providing their users with valuable suggestions about items, such as products or movies. However, in scenarios where users have more specific ideas about what they are looking for (e.g., they provide describing narratives, such as “Movies with minimal story, but incredible atmosphere, _such as No Country for Old Men”_ ), traditional recommender systems struggle to provide relevant suggestions. In this paper, we study this problem by investigati- doi
- 10.1145/3372923.3404818
- name
- Tell Me What You Want: Embedding Narratives for Movie Recommendations
- pages
- 6
- acm_url
- https://dl.acm.org/doi/10.1145/3372923.3404818
- authors
- Lukas Eberhard, Simon Walk, Denis Helic
- doi_url
- https://doi.org/10.1145/3372923.3404818
- license
- restricted
- summary
- Recommender systems are efficient exploration tools providing their users with valuable suggestions about items, such as products or movies. However, in scenarios where users have more specific ideas about what they are looking for (e.g., they provide describing narratives, such as “Movies with minimal story, but incredible atmosphere, _such as No Country for Old Men”_ ), traditional recommender systems struggle to provide relevant suggestions. In this paper, we study this problem by investigati
- keywords
- Narrative-driven recommendations; Recommender systems; Em-
- source_pdf
- HT-2020_51-35_3372923/3372923.3404818.pdf
- import_kind
- full_text
- open_access
- false
- ccs_concepts
- • Information systems →Recommender systems; Users and
- displayAuthor
- Lukas Eberhard, Simon Walk, Denis Helic
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