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Title:
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GENERATING IMPLICIT CUSTOMER FEEDBACK TO MULTI-AGENT RECOMMENDER SYSTEMS THROUGH SOCIAL NETWORKS |
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Author(s):
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Fabiana Lorenzi, Bruno Fontanella |
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ISBN:
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978-989-8533-16-6 |
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Editors:
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Bebo White and Pedro Isaías |
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Year:
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2013 |
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Edition:
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Single |
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Keywords:
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Social Networks; Implicit Customer Feedback; Multi-Agent Recommender Systems; Trust. |
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Type:
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Full Paper |
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First Page:
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59 |
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Last Page:
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66 |
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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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Recommender Systems deal with the challenge of obtaining customers feedback to improve their recommendations. Gathering information from users social networks may help in the composition of the user feedback. This paper presents an implicit information gathering mechanism that collects useful information in the social networks to compose automatically the user evaluation. The composed evaluation helps the recommender systems to improve next recommendations. The proposed mechanism was validated with travel packages recommendations and experiments were done to illustrate how the implicit evaluation process may avoid the possibility of the user does not evaluate the received recommendations. The results corroborate the idea that implicit evaluations help recommender systems to increase the quality of recommendation provided by them. |
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