Recommender systems are changing from novelties used by a few E-commerce sites, to serious business tools that are re-shaping the world of E-commerce. Many of the largest commerce...
Recommender systems are widely used to cope with the problem of information overload and, consequently, many recommendation methods have been developed. However, no one technique i...
To understand users’ acceptance of the emerging trend of personality-based recommenders (PBR), we evaluated an existing PBR using the technology acceptance model (TAM). We also ...
Abstract. Hard decisions constitute the major problem in digital watermarking applications, especially when content adaptive embedding methods are used. Soft-decision decoding, on ...
Current recommender systems have to cope with a certain reservation because they are considered to be hard to maintain and to give rather schematic advice. This paper presents an a...