Entropy measures and granularity measures for set-valued information systems

Dai, Jianhua; Tian, Haowei

doi:10.1016/j.ins.2013.03.045

Cited by 116 publications

(22 citation statements)

References 52 publications

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“…Generalizations of the element based definition can be obtained by using non-equivalence binary relations [7,11,47,[51][52][53] . Let R be an arbitrary relation on the universe U , for any X ⊆ U , the lower approximation and upper approximation can be defined by element approach as follows [53] : (6) where R ( x ) denotes the relational neighborhood of…”

Section: Generalizations Of Rough Set Model By Element Approach and Gmentioning

confidence: 99%

Catoptrical rough set model on two universes using granule-based definition and its variable precision extensions

Dai

Han

Zhang

et al. 2017

Information Sciences

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Section: Generalizations Of Rough Set Model By Element Approach and Gmentioning

confidence: 99%

Catoptrical rough set model on two universes using granule-based definition and its variable precision extensions

Dai

Han

Zhang

et al. 2017

Information Sciences

Self Cite

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“…Granular computing [38][39][40] is an emerging conceptual and computing paradigm of information processing. It delivers a cohesive framework supporting a formation of information granules and facilitating their processing and has recently been considerable development [37,[41][42][43]].…”

Section: Related Workmentioning

confidence: 99%

A Hybrid Recommender System Based on User-Recommender Interaction

Zhang

Min

et al. 2015

Mathematical Problems in Engineering

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Recommender systems are used to make recommendations about products, information, or services for users. Most existing recommender systems implicitly assume one particular type of user behavior. However, they seldom consider user-recommender interactive scenarios in real-world environments. In this paper, we propose a hybrid recommender system based on userrecommender interaction and evaluate its performance with recall and diversity metrics. First, we define the user-recommender interaction. The recommender system accepts user request, recommends N items to the user, and records user choice. If some of these items favor the user, she will select one to browse and continue to use recommender system, until none of the recommended items favors her. Second, we propose a hybrid recommender system combining random and k-nearest neighbor algorithms. Third, we redefine the recall and diversity metrics based on the new scenario to evaluate the recommender system. Experiments results on the well-known MovieLens dataset show that the hybrid algorithm is more effective than nonhybrid ones.

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“…Information theory is certainly the most prominent example, which is rooted in the classical probability framework. However, information-theoretic concepts have been extended to modern models of information granules, such as in the case of imprecise probabilities (Bronevich and Klir 2010), fuzzy sets (Zhai and Mendel 2011), intuitionistic fuzzy sets (Montes et al 2015), and rough sets (Zhu and Wen 2012;Chen et al 2014;Dai and Tian 2013).…”

Section: Introductionmentioning

confidence: 99%

Granular computing, computational intelligence, and the analysis of non-geometric input spaces

Livi

Sadeghian

2015

Granul. Comput.

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Data granulation emerged as an important paradigm in modeling and computing with uncertainty, exploiting information granules as the main mathematical constructs involved in the context of granular computing. In this paper, we comment on the importance of data granulation in computational intelligence methods. Toward this aim, we discuss also the peculiar aspects related to the analysis of non-geometric patterns, which have recently attracted considerable attention by researchers. As a conclusion, we elaborate over the fundamental, conceptual problems underlying the process of data granulation, which drive the quest for a sound theory of granular computing.

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Entropy measures and granularity measures for set-valued information systems

Cited by 116 publications

References 52 publications

Catoptrical rough set model on two universes using granule-based definition and its variable precision extensions

Catoptrical rough set model on two universes using granule-based definition and its variable precision extensions

A Hybrid Recommender System Based on User-Recommender Interaction

Granular computing, computational intelligence, and the analysis of non-geometric input spaces

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