Recommender systems support users by generating potentially interesting suggestions about relevant products and information.The increasing attention towards such tools is witnessed by both the great number of powerful and sophisticated recommenderalgorithms developed in recent years and their adoption in many popular Web platforms. However, performances of recommendersystems can be affected by many critical issues as for instance, over-specialization, attribute selection and scalability. To mitigate some of such negative effects, a hybrid recommender system,called Relevance Based Recommender, is proposed in this paper.It exploits individual measures of perceived relevance computed by each user for each instance of interest and, to obtain a better precision, also by considering the analogous measures computed by the other users for the same instances. Some experiments show the advantages introduced by this Recommender when generatingpotentially attractive suggestions.
A Novel Hybrid Approach Improving Effectiveness of Recommender Systems / Sarne', G. - In: JOURNAL OF INTELLIGENT INFORMATION SYSTEMS. - ISSN 0925-9902. - 44:3(2015), pp. 397-414. [10.1007/s10844-014-0338-z]
A Novel Hybrid Approach Improving Effectiveness of Recommender Systems
SARNE' G
2015-01-01
Abstract
Recommender systems support users by generating potentially interesting suggestions about relevant products and information.The increasing attention towards such tools is witnessed by both the great number of powerful and sophisticated recommenderalgorithms developed in recent years and their adoption in many popular Web platforms. However, performances of recommendersystems can be affected by many critical issues as for instance, over-specialization, attribute selection and scalability. To mitigate some of such negative effects, a hybrid recommender system,called Relevance Based Recommender, is proposed in this paper.It exploits individual measures of perceived relevance computed by each user for each instance of interest and, to obtain a better precision, also by considering the analogous measures computed by the other users for the same instances. Some experiments show the advantages introduced by this Recommender when generatingpotentially attractive suggestions.File | Dimensione | Formato | |
---|---|---|---|
art%3A10.1007%2Fs10844-014-0338-z.pdf
non disponibili
Licenza:
Non specificato
Dimensione
1.79 MB
Formato
Adobe PDF
|
1.79 MB | Adobe PDF | Visualizza/Apri Richiedi una copia |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.