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Title:
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THE IMPACT OF DEMOGRAPHIC DATA ON A LATENT FACTOR MODEL |
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Author(s):
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Edson B. dos Santos Junior, Marcelo G. Manzato, Rudinei Goularte |
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ISBN:
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978-989-8533-24-1 |
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Editors:
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Pedro Isaías and Bebo White |
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Year:
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2014 |
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Edition:
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Single |
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Keywords:
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Recommender systems, demographic data, collaborative filtering, latent factor model. |
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Type:
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Full Paper |
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First Page:
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43 |
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Last Page:
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50 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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One of the major challenges in Recommender Systems is how to predict users preferences in a group context. The demographic data may be an effective way to consider users characteristics, enabling analysis about group of users and their contextual constraints. This paper proposes an analysis about the impact of demographic data on a hybrid recommender algorithm, which integrates a set of different users inputs into a unified and generic latent factor model. The recommender exploits users demographics, such as age, gender and occupation, along with implicit feedback and items metadata. Depending on the personal information from users, the recommender selects content whose subject is semantically related to their interests. |
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