Dealing with incomplete information in a fuzzy linguistic recommender system to disseminate information in university digital libraries

Porcel, Carlos; Liu, Xinyue

doi:10.1016/j.knosys.2009.07.007

Cited by 193 publications

(85 citation statements)

References 46 publications

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“…There are three different methodologies to deal with incomplete LPRs, which are defined according to the three different linguistic decision frameworks: (i) 2-tuple LPRs [3,12,59];…”

Section: Managing Missing Preference Values In Lprsmentioning

confidence: 99%

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Managing incomplete preference relations in decision making: A review and future trends

Ureña

Chiclana

Morente-Molinera

et al. 2015

Information Sciences

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246

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“…There are three different methodologies to deal with incomplete LPRs, which are defined according to the three different linguistic decision frameworks: (i) 2-tuple LPRs [3,12,59];…”

Section: Managing Missing Preference Values In Lprsmentioning

confidence: 99%

“…Porcel and Herrera-Viedma [59] present an application in the context of fuzzy linguistic recommender systems that allows incomplete linguistic information.…”

Section: Managing Missing Preference Values In Lprsmentioning

confidence: 99%

Managing incomplete preference relations in decision making: A review and future trends

Ureña

Chiclana

Morente-Molinera

et al. 2015

Information Sciences

Self Cite

246

View full text Add to dashboard Cite

“…In [18] a review of consensus models in a fuzzy environment can be found. There is, nowadays, a wide range of areas of application for these methods, from managerial to medical or engineering [6,8,10,30]. In particular, some fuzzy Delphi approaches have been proposed to deal with uncertainty and linguistic information [9,12,27].…”

Section: Introductionmentioning

confidence: 99%

A consensus model for Delphi processes with linguistic terms and its application to chronic pain in neonates definition

Agell

Ganzewinkel

Sánchez

et al. 2015

Applied Soft Computing

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This paper proposes a new model of consensus based on linguistic terms to be implemented in Delphi processes. The model of consensus involves qualitative reasoning techniques and is based on the concept of entropy. The proposed model has the ability to reach consensus automatically without the need for either a moderator or a final interaction among panelists. In addition, it permits panelists to answer with different levels of precision depending on their knowledge on each question. The model defined has been used to establish the relevant features for the definition of a type of chronic disease. A real-case application conducted in the Department of Neonatology of Máxima Medical Center in The Netherlands is presented. This application considers the opinions of stakeholders of neonate healthcare in order to reach a final consensual definition of chronic pain in neonates.

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“…Although social networks provide a great infrastructure where people can make connections and exchange information, people are also exposed to unwanted connections and information. Researchers in the field proposed several methods to alleviate the problem such as collaborative filtering [1], [2] and recommender systems [3], [4].…”

Section: Introductionmentioning

confidence: 99%

Estimating Social Tie Strength for Autonomous D2D Collaborations

Choi¹,

Kang²,

Jung³

et al. 2015

IJFCC

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7 Abstract-With the new paradigm, Internet of Things, devices are now able to share services and resources generating higher level of services. However, the management and configuration of the smart devices are often troublesome, interrupting user's primary task. To automate the process of device collaboration, smart devices should be able to configure and manage themselves, self-identifying peer devices and their relationships. Hence, we proposed the concept of device sociality, which describes social relationship between devices. In device social network with device sociality, devices are able to detect peer devices and determine resources and services to share. To derive device sociality, we investigated social relationships between users and analyzed correlations between online social interactions and social relationships. Moreover, we also investigated social ties in terms of interaction direction, individual peculiarity, and network topology. In the experiment, we not only derived directional and individualized social affinity models, but also detected organizational structure and groups of the participants, confirming the potential of D2D collaboration.Index Terms-Device social, social relationship, social network, internet of things, communication, relationship model, tie strength.

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Dealing with incomplete information in a fuzzy linguistic recommender system to disseminate information in university digital libraries

Cited by 193 publications

References 46 publications

Managing incomplete preference relations in decision making: A review and future trends

Managing incomplete preference relations in decision making: A review and future trends

A consensus model for Delphi processes with linguistic terms and its application to chronic pain in neonates definition

Estimating Social Tie Strength for Autonomous D2D Collaborations

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