Knowledge Visualization Model for Intelligent Dynamic Decision-Making

Elouni, Jihed; Ltifi, Hela; Ayed, Mounir Ben

doi:10.1007/978-3-319-27221-4_19

Cited by 9 publications

(13 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To this end, he defined a framework of knowledge visualization (as opposed to information visualization), which is defined as "the use of visual representations to improve the transfer of knowledge between at least two persons or groups of persons". Since then, the own Burkhard and others have applied the framework to different areas of interdisciplinary visualization practice such as urban planning [33], decision-making support in the medical domain [34], or education [35]. In more recent times, Miller et al elaborated on Burkhard's ideas to frame a novel research field (visual musicology) as per the principles of methodology transfer [3] using their methodology transfer model (MTM).…”

Section: Methodology Transfermentioning

confidence: 99%

Defragmenting Research Areas with Knowledge Visualization and Visual Text Analytics

Benito-Santos

Therón

2020

Applied Sciences

View full text Add to dashboard Cite

The increasing specialization of science is motivating the fragmentation of traditional and well-established research areas into interdisciplinary communities of practice that focus on cooperation between experts to solve problems in a wide range of domains. This is the case of problem-driven visualization research (PDVR), in which groups of scholars use visualization techniques in different application domains such as the digital humanities, bioinformatics, sports science, or computer security. In this paper, we employ the findings obtained during the development of a novel visual text analytics tool we built in previous studies, GlassViz, to automatically detect interesting knowledge associations and groups of common interests between these communities of practice. Our proposed method relies on the statistical modeling of author-assigned keywords to make its findings, which are demonstrated in two use cases. The results show that it is possible to propose interactive, semisupervised visual approaches that aim at defragmenting a body of research using text-based, automatic literature analysis methods.

show abstract

Section: Methodology Transfermentioning

confidence: 99%

Defragmenting Research Areas with Knowledge Visualization and Visual Text Analytics

Benito-Santos

Therón

2020

Applied Sciences

View full text Add to dashboard Cite

show abstract

“…Data visualization is not only a way to give representation to data. Data visualization is a way to extract meaning from data (Elouni, et al, 2016). Data visualization affect the cognitive process of the researcher, analysts or decision maker to suggest the tools and the analytical strategy to extract meaning from data.…”

Section: Data Miningmentioning

confidence: 99%

The Location of Superstores in Italy: A Metric Approach

Leogrande¹,

Massaro²,

Galiano³

2020

IJoBM

View full text Add to dashboard Cite

show abstract

“…It has the ability to (1) automatically generate trend lines and interactive bubbles, (2) adjust them by the decision-makers, and (2) consequently update the associated data. 70 In the following section, we present our evaluation of these three visualization techniques developed in the system of Ltifi et al 38 and Elouni et al 70 Evaluation method application…”

Section: Case Study: Visual Idss For the Fight Against Nosocomial Infmentioning

confidence: 99%

Fuzzy logic–based evaluation of visualizations generated by intelligent decision support systems

Ltifi

Amri

Ayed

2016

Information Visualization

Self Cite

View full text Add to dashboard Cite

The development of intelligent decision support systems requires much research effort to solve decision-making problems’ complexity. In fact, the combination of both intelligent components and visualization aspects in intelligent decision support system required a lot of efforts in order to develop advanced information visualization schemes for decision-making processes. For this, an efficient evaluation of these systems has become a major concern for applications in multiple fields. The reports of the existing usability evaluation studies are helpful to verify the potential and the limitations of these tools. However, it is important to integrate more relevant metrics for visual analytics tasks in dynamic intelligent decision support system. The proposed method consists of a questionnaire that is given to the users and a subsequent analysis of the resulting data using fuzzy logic. The advantage of the fuzzy model is its ability to transform the input survey scores into linguistic variables, as well as linguistic evaluation of the overall intelligent decision support system visualization tool. With this approach, it is possible to model the vagueness in the ordinal judgments obtained from the users’ evaluation about the visualizations of intelligent decision support system and to support uncertainty in such evaluation.

show abstract

Knowledge Visualization Model for Intelligent Dynamic Decision-Making

Cited by 9 publications

References 13 publications

Defragmenting Research Areas with Knowledge Visualization and Visual Text Analytics

Defragmenting Research Areas with Knowledge Visualization and Visual Text Analytics

The Location of Superstores in Italy: A Metric Approach

Fuzzy logic–based evaluation of visualizations generated by intelligent decision support systems

Contact Info

Product

Resources

About