Back to Search
Start Over
A novel framework for augmenting the quality of explanations in recommender systems.
- Source :
- Intelligent Decision Technologies; 2017, Vol. 11 Issue 2, p187-197, 11p
- Publication Year :
- 2017
-
Abstract
- A significant challenge being faced in recommender systems research concerns the provision of robust explanations about why a particular option is suggested. These explanations may exploit diverse data types concerning the users and items under consideration. In line with the above, this paper introduces a novel framework for automatic explanations building in recommender systems. The proposed solution follows a hybrid approach that meaningfully integrates collaborative filtering and sentiment analysis features into classical multi-attribute based ranking. A comprehensive evaluation of the proposed solution advocates the exploitation of additional and diverse information in explanation building, since this better fulfils a series of recommendation related aims such as transparency, persuasiveness, effectiveness and satisfaction. [ABSTRACT FROM AUTHOR]
- Subjects :
- RECOMMENDER systems
AUGMENTED reality
ROBUST control
Subjects
Details
- Language :
- English
- ISSN :
- 18724981
- Volume :
- 11
- Issue :
- 2
- Database :
- Complementary Index
- Journal :
- Intelligent Decision Technologies
- Publication Type :
- Academic Journal
- Accession number :
- 124294011
- Full Text :
- https://doi.org/10.3233/IDT-170287