A recommendation approach for digital TV systems based on multimodal features
Authors: 
Reudismam Rolim, Felipe Barbosa, Alexandre Costa, Giovanni Calheiros, Hyggo Almeida, Angelo Perkusich, Aldenor MartinsAuthors Info & Claims
Reudismam Rolim, Felipe Barbosa, Alexandre Costa, Giovanni Calheiros, Hyggo Almeida, Angelo Perkusich, Aldenor MartinsAuthors Info & ClaimsPages 289 - 291
Abstract
Digital TV content providers are becoming widespread, with hundreds of programs available each day. The information overload makes difficult for the user to find programs of interest. To help the user, Recommendation Systems (RS) are a popular path. However, applying RS to some environments is not easy, either due to the lack or insufficiency of data to create accurate recommendations. In Digital TV domain, the main information available to make recommendations is the Electronic Program Guide (EPG) that is limited, containing only reduced textual data, making difficult to get an accurate recommendation using standard techniques. In this work we introduce a multimodal approach to recommend Digital TV programs, combining EPG text and visual information. We experimentally demonstrated that using multimodal features improved accuracy when compared with RS standard approaches.
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Index Terms
- A recommendation approach for digital TV systems based on multimodal features
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Published In
March 2014
1890 pages
ISBN:9781450324694
DOI:10.1145/2554850
- Conference Chairs:
- Yookun Cho,
- Sung Y. Shin,
- Program Chairs:
- Sangwook Kim,
- Chih-Cheng Hung,
- Jiman Hong
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Published: 24 March 2014
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