By George A. Tsihrintzis, Maria Virvou, Lakhmi C. Jain
Multimedia providers at the moment are commonplace in quite a few actions within the day-by-day lives of people. similar software parts comprise providers that permit entry to massive depositories of knowledge, electronic libraries, e-learning and e-education, e-government and e-governance, e-commerce and e-auctions, e-entertainment, e-health and e-medicine, and e-legal providers, in addition to their cellular opposite numbers (i.e., m-services). regardless of the large development of multimedia providers over the hot years, there's an expanding call for for his or her additional improvement. This call for is pushed via the ever-increasing wish of society for simple accessibility to details in pleasant, customized and adaptive environments.
In this ebook handy, we learn contemporary Advances in Recommender structures. Recommender platforms are an important in multimedia prone, as they target at holding the provider clients from information overload. The publication contains 9 chapters, which current numerous contemporary examine ends up in recommender systems.
This study booklet is directed to professors, researchers, program engineers and scholars of all disciplines who're attracted to studying extra approximately recommender structures, advancing the corresponding cutting-edge and constructing recommender structures for particular applications.
Read Online or Download Multimedia Services in Intelligent Environments: Advances in Recommender Systems PDF
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User modeling for adaptive news access. User Model. User-Adapt. Interact. 10(2–3), 147–180 (2000) 46. : Hybrid recommender systems for electronic commerce. Presented at the Proceedings of Knowledge-Based Electronic Markets, Papers from the AAAI Workshop, AAAI Technical Report WS-00-04, pp. 78–83, Menlo Park, CA (2000) 47. : A personalized TV listings service for the digital TV age. Based Syst. 13, 53–59 (2000) 48. : Knowledge-based recommender systems. In: Kent, A. ) Encyclopedia of Library and Information Systems.
In: Proceedings of ACM SIGIR Workshop on Recommender Systems (1999) 45. : User modeling for adaptive news access. User Model. User-Adapt. Interact. 10(2–3), 147–180 (2000) 46. : Hybrid recommender systems for electronic commerce. Presented at the Proceedings of Knowledge-Based Electronic Markets, Papers from the AAAI Workshop, AAAI Technical Report WS-00-04, pp. 78–83, Menlo Park, CA (2000) 47. : A personalized TV listings service for the digital TV age. Based Syst. 13, 53–59 (2000) 48. : Knowledge-based recommender systems.
With a knowledgebased method. In the knowledge-based method, the authors construct a feature vector according to defined attributes that characterize the restaurants. This method is similar to content-based methods; however, it must be noted that these metadata are content-independent and for this reason the term knowledge-based is utilized. These restaurants are then ranked with a collaborative method. 24 A. S. Lampropoulos and G. A. 1 Adding Content-Based Characteristics to Collaborative Models In [10], the authors proposed collaboration via content.