Empowering recommender systems using trust and argumentation

Bedi, Punam; Vashisth, Pooja

doi:10.1016/j.ins.2014.04.012

Cited by 49 publications

(31 citation statements)

References 25 publications

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“…Similarly, other approaches considering trust in memory-based collaborative filtering scenarios were developed at Birtolo and Ronca [19] and Bedi and Vashisth [15]. Table 4 presents further analysis of the referred research works, by additionally including other important aspects such as evaluation approaches, used datasets, and application areas.…”

Section: Sim(a B)mentioning

confidence: 99%

Fuzzy Tools in Recommender Systems: A Survey

Toledo¹,

Martínez²

2017

IJCIS

152

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Recommender systems are currently successful solutions for facilitating access for online users to the information that fits their preferences and needs in overloaded search spaces. In the last years several methodologies have been developed to improve their performance. This paper is focused on developing a review on the use of fuzzy tools in recommender systems, for detecting the more common research topics and also the research gaps, in order to suggest future research lines for boosting the current developments in fuzzy-based recommender systems. Specifically, it is developed an analysis of the papers focused at such aim, indexed in Thomson Reuters Web of Science database, in terms of they key features, evaluation strategies, datasets employed, and application areas.

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Section: Sim(a B)mentioning

confidence: 99%

Fuzzy Tools in Recommender Systems: A Survey

Toledo¹,

Martínez²

2017

IJCIS

152

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“…Based on the included studies in the review, the most commonly used technique is rulebased inference (Hsairi et al 2006;Gaertner and Toni 2007;Moraitis and Spanoudakis 2007;Yuan et al 2009;Obeid and Moubaiddin 2009;Caiquan et al 2010;Tannai et al 2011;Xiong et al 2012;Harvey et al 2007;Huang and Lin 2010;Janjua and Hussain 2012;Wardeh et al 2012;Rowe et al 2012;van der Weide et al 2011). However, there are other techniques that must not be ignored because they offer other alternatives to reason under uncertainty, such as fuzzy logic Hsairi et al 2010;Chow et al 2013;Wang and Luo 2010;Tao et al 2014;Bedi and Vashisth 2014) Vicari et al 2003), to reason based on similarity, such as CBR Aulinas et al 2012;), or to measure the benefit of a specific action using utility functions (Ge et al 2010).…”

Section: Agent Levelmentioning

confidence: 99%

A systematic review of argumentation techniques for multi-agent systems research

Carrera

Iglesias

2015

Artif Intell Rev

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The ability to build arguments that express thoughts is crucial for intelligent interactions among human beings. Thus, argumentation techniques have been applied for years in fields, such as rhetoric or artificial intelligence. More specifically, the agents paradigm fits into the use of these types of techniques because agents shape a society in which they interact to make arrangements or to decide future actions. Those interactions can be modelled using argumentation techniques. Therefore, the application of those techniques in multi-agent systems is an interesting research field. However, no systematic review has been conducted previously, to the best of the authors' knowledge, to provide an overview of argumentation techniques for multi-agent systems. This paper presents a systematic review of argumentation techniques for multi-agent systems research. The period of time that is included in this review is from 1998 to 2014. The objective of this review is to obtain an overview of the existing approaches and to study their impact on research and practice. The research method has been defined to identify relevant studies based on a predefined search strategy, and it is clearly defined to facilitate the reading of this paper. All of the included studies in this review have been analysed from two different points of view: the Application view and the Multi-Agent System view. A comprehensive analysis of the extracted data is provided in the paper, which is based on a set of research questions that are defined. The results of this review reveal suggestions for further research and practice. The argumentation technology is actually in a phase of internal enhancement and exploration. Moreover, the research interest in this topic has increased in the last years. Furthermore, several interesting findings are presented in the paper.

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“…In particular, several CF based systems have been proposed and evaluated in recent years, providing satisfactory results in various commercial applications [9,43,25,34,26]. On the other hand, rather than adopting CF, DF, and CBF as standalone approaches, hybrid systems can combine the strengths better represent user needs [50,4,11,49,39,57,5].…”

Section: Introductionmentioning

confidence: 99%