Integration of decision support systems to improve decision support performance

Decision support system (DSS) is a well-established research and development area. Traditional isolated, stand-alone DSS has been recently facing new challenges. In order to improve the performance of DSS to meet the challenges, research has been actively carried out to develop integrated decision support systems (IDSS). This paper reviews the current research efforts with regard to the development of IDSS. The focus of the paper is on the integration aspect for IDSS through multiple perspectives, and the technologies that support this integration. More than 100 papers and software systems are discussed. Current research efforts and the development status of IDSS are explained, compared and classified. In addition, future trends and challenges in integration are outlined. The paper concludes that by addressing integration, better support will be provided to decision makers, with the expectation of both better decisions and improved decision making processes

Group decision making and quality-of-information in e-Health systems

Knowledge is central to the modern economy and society. Indeed, the knowledge society has transformed the concept of knowledge and is more and more aware of the need to overcome the lack of knowledge when has to make options or address its problems and dilemmas. One`s knowledge is less based on exact facts and more on hypotheses, perceptions or indications. Even when we use new computational artefacts and novel methodologies for problem solving, like the use of Group Decision Support Systems (GDSS), the question of incomplete information is in most of the situations marginalized. On the other hand, common sense tells us that when a decision is made it is impossible to have a perception of all the information involved and the nature of its intrinsic quality. Therefore, something has to be made in terms of the information available and the process of its evaluation. It is under this framework that a Multi-valued Extended Logic Programming language will be used for knowledge representation and reasoning, leading to a model that embodies the Quality-of-Information (QoI) and its quantification, along the several stages of the decision making process. In this way it is possible to provide a measure of the value of the QoI that supports the decision itself. This model will be here presented in the context of a GDSS for VirtualECare, a system aimed at sustaining online healthcare services

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

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.This work was supported by the GrouPlanner Project (POCI-01-0145-FEDER-29178) and by National Funds through the FCT – Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) within the Projects UIDB/00319/2020 and UIDB/00760/2020

Representing decision-makers using styles of behavior: an approach designed for group decision support systems

Supporting decision-making processes when the elements of a group are geographically dispersed and on a tight schedule is a complex task. Aiming to support decision-makers anytime and anywhere, Web-based group decision support systems have been studied. However, the limitations in the decision-makers’ interactions associated to this scenario bring new challenges. In this work, we propose a set of behavioral styles from which decision-makers’ intentions can be modelled into agents. The goal is that, besides having agents represent typical preferences of the decision-makers (towards alternatives and criteria), they can also represent their intentions. To do so, we conducted a survey with 64 participants in order to find homogeneous operating values so as to numerically define the proposed behavioral styles in four dimensions. In addition, we also propose a communication model that simulates the dialogues made by decision-makers in face-to-face meetings. We developed a prototype to simulate decision scenarios and found that agents are capable of acting according to the decision-makers’ intentions and fundamentally benefit from different possible behavioral styles, just as a face-to-face meeting benefits from the heterogeneity of its participants.This work was supported by COMPETE Programme (operational programme for competitiveness) within Project POCI-01-0145-FEDER-007043, by National Funds through the FCT – Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) within the Projects UID/CEC/00319/2013, UID/EEA/00760/2013, and the Ph.D. grants SFRH/BD/89697/2012 and SFRH/BD/89465/2012 attributed to João Carneiro and Pedro Saraiva, respectively.info:eu-repo/semantics/publishedVersio

Inter-organization cooperation for ambient assisted living

In the last years we have witnessed to a substantial increase on the number of people in need of care services, espe-cially among the elderly, a phenomenon related to population ageing. However, this is becoming not exclusive of the elderly, as diseases like obesity, diabetes, and blood pressure have been increasing amongst young adults. This is a new reality which needs to be dealt by the healthcare sector, specifically the public one. Given these new scenarios, the importance of finding new and cost-effective ways for health care delivery are of particular relevance, especially when it is believed that these new patients should not be removed from their natural, day-to-day life, environment. The evolution of the, so called, new technolo-gies may pay here a very important role as they may become part of the solution for this new problematic. Actually, they are already been used as, in recent years, several projects have raised in this relatively new area of work. These projects, although legitimate ones, were essential for delineating a path to pursue for others to come, as they were in some case, very simple ones (e.g. panic buttons), and, especially, reactive ones. In this paper, we are going to present how we are trying to evolve these projects a step further, through the introduction of proactiveness as a key factor, taking advantage of “new”, as in applied to this areas, techniques of decision making, idea generation, argumentation and data quality, applied, not only to the in transit information, but also to the one provided by the several intervenient as well as themselves. In order to be able to pursue this delineated path, a new approach for knowledge representation, reasoning, and even for problem solving is proposed. To achieve these goals, the VirtualECare environment is presented, together with its sustaining infrastructure and architecture. Particular attention will be paidto how it may be used to simulate a virtual Assisted Living Environment in order to, later, bet-ter monitor real ones, attending to its customers’ needs

Advanced decision support systems for managers

Managers need to make timely decisions to solve the problems in the organization or to take advantage of the opportunities. But accessing the related information and knowledge is a necessity for the purpose of decision-making. Current transactional information systems in organizations easily manage the affairs of the organization, but they do not provide the necessary ability and intelligence to take a good decision and business performance management. Here, the importance of using such systems to support management decisions and business intelligence tools are highlighted. The purpose of this paper is to analyze the decision-making process, the structure, components, and features. Also a decision support system (DSS) is described. Then, the types of decision support systems will be defined and their abilities and functions will be expressed. The following performance management and business intelligence are explained. Finally, Intelligent Decision Support System will be examined and their functions and abilities to develop a decision support tool for decision-making will be analyzed

Aplicação de técnicas de Clustering ao contexto da Tomada de Decisão em Grupo

Nowadays, decisions made by executives and managers are primarily made in a group. Therefore, group decision-making is a process where a group of people called participants work together to analyze a set of variables, considering and evaluating a set of alternatives to select one or more solutions. There are many problems associated with group decision-making, namely when the participants cannot meet for any reason, ranging from schedule incompatibility to being in different countries with different time zones. To support this process, Group Decision Support Systems (GDSS) evolved to what today we call web-based GDSS. In GDSS, argumentation is ideal since it makes it easier to use justifications and explanations in interactions between decision-makers so they can sustain their opinions. Aspect Based Sentiment Analysis (ABSA) is a subfield of Argument Mining closely related to Natural Language Processing. It intends to classify opinions at the aspect level and identify the elements of an opinion. Applying ABSA techniques to Group Decision Making Context results in the automatic identification of alternatives and criteria, for example. This automatic identification is essential to reduce the time decision-makers take to step themselves up on Group Decision Support Systems and offer them various insights and knowledge on the discussion they are participants. One of these insights can be arguments getting used by the decision-makers about an alternative. Therefore, this dissertation proposes a methodology that uses an unsupervised technique, Clustering, and aims to segment the participants of a discussion based on arguments used so it can produce knowledge from the current information in the GDSS. This methodology can be hosted in a web service that follows a micro-service architecture and utilizes Data Preprocessing and Intra-sentence Segmentation in addition to Clustering to achieve the objectives of the dissertation. Word Embedding is needed when we apply clustering techniques to natural language text to transform the natural language text into vectors usable by the clustering techniques. In addition to Word Embedding, Dimensionality Reduction techniques were tested to improve the results. Maintaining the same Preprocessing steps and varying the chosen Clustering techniques, Word Embedders, and Dimensionality Reduction techniques came up with the best approach. This approach consisted of the KMeans++ clustering technique, using SBERT as the word embedder with UMAP dimensionality reduction, reducing the number of dimensions to 2. This experiment achieved a Silhouette Score of 0.63 with 8 clusters on the baseball dataset, which wielded good cluster results based on their manual review and Wordclouds. The same approach obtained a Silhouette Score of 0.59 with 16 clusters on the car brand dataset, which we used as an approach validation dataset.Atualmente, as decisões tomadas por gestores e executivos são maioritariamente realizadas em grupo. Sendo assim, a tomada de decisão em grupo é um processo no qual um grupo de pessoas denominadas de participantes, atuam em conjunto, analisando um conjunto de variáveis, considerando e avaliando um conjunto de alternativas com o objetivo de selecionar uma ou mais soluções. Existem muitos problemas associados ao processo de tomada de decisão, principalmente quando os participantes não têm possibilidades de se reunirem (Exs.: Os participantes encontramse em diferentes locais, os países onde estão têm fusos horários diferentes, incompatibilidades de agenda, etc.). Para suportar este processo de tomada de decisão, os Sistemas de Apoio à Tomada de Decisão em Grupo (SADG) evoluíram para o que hoje se chamam de Sistemas de Apoio à Tomada de Decisão em Grupo baseados na Web. Num SADG, argumentação é ideal pois facilita a utilização de justificações e explicações nas interações entre decisores para que possam suster as suas opiniões. Aspect Based Sentiment Analysis (ABSA) é uma área de Argument Mining correlacionada com o Processamento de Linguagem Natural. Esta área pretende classificar opiniões ao nível do aspeto da frase e identificar os elementos de uma opinião. Aplicando técnicas de ABSA à Tomada de Decisão em Grupo resulta na identificação automática de alternativas e critérios por exemplo. Esta identificação automática é essencial para reduzir o tempo que os decisores gastam a customizarem-se no SADG e oferece aos mesmos conhecimento e entendimentos sobre a discussão ao qual participam. Um destes entendimentos pode ser os argumentos a serem usados pelos decisores sobre uma alternativa. Assim, esta dissertação propõe uma metodologia que utiliza uma técnica não-supervisionada, Clustering, com o objetivo de segmentar os participantes de uma discussão com base nos argumentos usados pelos mesmos de modo a produzir conhecimento com a informação atual no SADG. Esta metodologia pode ser colocada num serviço web que segue a arquitetura micro serviços e utiliza Preprocessamento de Dados e Segmentação Intra Frase em conjunto com o Clustering para atingir os objetivos desta dissertação. Word Embedding também é necessário para aplicar técnicas de Clustering a texto em linguagem natural para transformar o texto em vetores que possam ser usados pelas técnicas de Clustering. Também Técnicas de Redução de Dimensionalidade também foram testadas de modo a melhorar os resultados. Mantendo os passos de Preprocessamento e variando as técnicas de Clustering, Word Embedder e as técnicas de Redução de Dimensionalidade de modo a encontrar a melhor abordagem. Essa abordagem consiste na utilização da técnica de Clustering KMeans++ com o SBERT como Word Embedder e UMAP como a técnica de redução de dimensionalidade, reduzindo as dimensões iniciais para duas. Esta experiência obteve um Silhouette Score de 0.63 com 8 clusters no dataset de baseball, que resultou em bons resultados de cluster com base na sua revisão manual e visualização dos WordClouds. A mesma abordagem obteve um Silhouette Score de 0.59 com 16 clusters no dataset das marcas de carros, ao qual usamos esse dataset com validação de abordagem

ABS4GD: a multi-agent system that simulates group decision processes considering emotional and argumentative aspects

Emotion although being an important factor in our every day life it is many times forgotten in the development of systems to be used by persons. In this work we present an architecture for a ubiquitous group decision support system able to support persons in group decision processes. The system considers the emotional factors of the intervenient participants, as well as the argumentation between them. Particular attention will be taken to one of components of this system: the multi-agent simulator, modeling the human participants, considering emotional characteristics, and allowing the exchanges of hypothetic arguments among the participants

Advanced decision support systems for managers

Managers need to make timely decisions to solve the problems in the organization or to take advantage of the opportunities. But accessing the related information and knowledge is a necessity for the purpose of decision-making. Current transactional information systems in organizations easily manage the affairs of the organization, but they do not provide the necessary ability and intelligence to take a good decision and business performance management. Here, the importance of using such systems to support management decisions and business intelligence tools are highlighted. The purpose of this paper is to analyze the decision-making process, the structure, components, and features. Also a decision support system (DSS) is described. Then, the types of decision support systems will be defined and their abilities and functions will be expressed. The following performance management and business intelligence are explained. Finally, Intelligent Decision Support System will be examined and their functions and abilities to develop a decision support tool for decision-making will be analyzed

Ambient intelligence in emotion based ubiquitous decision making

As the time goes on, it is a question of common sense to involve in the process of decision making people scattered around the globe. Groups are created in a formal or informal way, exchange ideas or engage in a process of argumentation and counterargumentation, negotiate, cooperate, collaborate or even discuss techniques and/or methodologies for problem solving. In this work it is proposed an agent-based architecture to support a ubiquitous group decision support system, i.e. based on the concept of agent, which is able to exhibit intelligent, and emotional-aware behaviour, and support argumentation, through interaction with individual persons or groups. It is enforced the paradigm of Mixed Initiative Systems, so the initiative is to be pushed by human users and/or intelligent agents