Arguing with Behavior Influence: A Model for Web-Based Group Decision Support Systems

Carneiro, João; Martinho, Diogo; Marreiros, Goreti; Nováis, Paulo

doi:10.1142/s0219622018500542

Cited by 16 publications

(13 citation statements)

References 85 publications

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“…Multi-criteria decision analysis (MCDA) provides a comprehensive framework for building computational intelligence capable of emulating the decision making process of experts and stakeholders (Carneiro et al, 2019;Del Vasto-Terrientes et al, 2015;Beynon et al, 2001). This framework has been extensively used to produce expert systems for decision support under multiple criteria (e.g., Lakhani et al, 2019;Glaize et al, 2019;Bystrzanowska and Tobiszewski, 2018;Dehe and Bamford, 2015).…”

Section: Multi-criteria Decision Analysis and Machine Learningmentioning

confidence: 99%

Dimensionality reduction for multi-criteria problems: An application to the decommissioning of oil and gas installations

Martins

Bahiense

Infante

et al. 2020

Expert Systems with Applications

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This paper is motivated by decommissioning studies in the field of oil and gas, which comprise a very large number of installations and are of interest to a large number of stakeholders. Generally, the problem gives rise to complicated multi-criteria decision aid tools that rely upon the costly evaluation of multiple criteria for every piece of equipment. We propose the use of machine learning techniques to reduce the number of criteria by feature selection, thereby reducing the number of required evaluations and producing a simplified decision aid tool with no sacrifice in performance. In addition, we also propose the use of machine learning to explore the patterns of the multi-criteria decision aid tool in a training set. Hence, we predict the outcome of the analysis for the remaining pieces of equipment, effectively replacing the multicriteria analysis by the computational intelligence acquired from running it in the

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Section: Multi-criteria Decision Analysis and Machine Learningmentioning

confidence: 99%

Dimensionality reduction for multi-criteria problems: An application to the decommissioning of oil and gas installations

Martins

Bahiense

Infante

et al. 2020

Expert Systems with Applications

View full text Add to dashboard Cite

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“…We believe this will allow the tourists to feel part of the process and understand it. The dialogue model will also have a high level of expressiveness, meaning the agents will be capable of acting according to different intentions and motivations in the same dialogue, mirroring their tourist, as mentioned in our previous works [26,27].…”

Section: Intelligent Agents Dialogue Games and Gamification To Enhanmentioning

confidence: 99%

Modeling a Mobile Group Recommender System for Tourism with Intelligent Agents and Gamification

Alves

Carneiro

Marreiros

et al. 2019

Lecture Notes in Computer Science

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To provide recommendations to groups of people is a complex task, especially due to the group's heterogeneity and conflicting preferences and personalities. This heterogeneity is even deeper in occasional groups formed for predefined tour packages in tourism. Group Recommender Systems (GRS) are being designed for helping in situations like those. However, many limitations can still be found, either on their time-consuming configurations and excessive intrusiveness to build the tourists' profile, or in their lack of concern for the tourists' interests during the planning and tours, like feeling a greater liberty, diminish the sense of fear/being lost, increase their sense of companionship, and promote the social interaction among them without losing a personalized experience. In this paper, we propose a conceptual model that intends to enhance GRS for tourism by using gamification techniques, intelligent agents modeled with the tourists' context and profile, such as psychological and socio-cultural aspects, and dialogue games between the agents for the post-recommendation process. Some important aspects of a GRS for tourism are also discussed, opening the way for the proposed conceptual model, which we believe will help to solve the identified limitations.

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“…Thus, we propose a system that potentiates the communication between decision-makers. Obviously, it is different to communicate in face-to-face contexts and through an online application [93,94]. So, the communication should be more structured than the one practiced in presential contexts.…”

Section: Conceptual Flowmentioning

confidence: 99%

Group decision support systems for current times: Overcoming the challenges of dispersed group decision-making

et al. 2021

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We are living a change of paradigm regarding decision-making. On the one hand, there is a growing need to make decisions in group at both professional and personal levels, on the other hand, it is increasingly difficult for decision-makers to meet at the same place and at the same time. The Web-based Group Decision Support Systems intend to overcome this limitation, allowing decision-makers to contribute to the decision process anytime and anywhere. However, they have been defined inadequately which has been compromising its success. This work discusses the current Group Decision Support Systems limitations in terms of challenges and possible impediments for their acceptance by the organizations and propose a conceptual definition of a Web-based Group Decision Support System that intends to overcome the existing limitations and help them to affirm as a reliable and useful tool. In addition, some crucial topics are addressed, such as communication and perception, that are essential and sometimes forgotten in the support of dispersed decision-makers. We concluded that there are still some limitations, mostly in terms of models and applications, that prevent the design of higher quality systems.

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Arguing with Behavior Influence: A Model for Web-Based Group Decision Support Systems

Cited by 16 publications

References 85 publications

Dimensionality reduction for multi-criteria problems: An application to the decommissioning of oil and gas installations

Dimensionality reduction for multi-criteria problems: An application to the decommissioning of oil and gas installations

Modeling a Mobile Group Recommender System for Tourism with Intelligent Agents and Gamification

Group decision support systems for current times: Overcoming the challenges of dispersed group decision-making

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