scholarly journals Towards the Formulation of a Unified Data Mining Theory, Implemented by Means of Multiagent Systems (MASs)

10.5772/47984 ◽  
2012 ◽  
Author(s):  
Dost Muhammad ◽  
Nawaz Mohamudally ◽  
D. K. R. Babajee
Keyword(s):  
Data Mining ◽  
Multiagent Systems

An Approach to Generate Software Agents for Health Data Mining

2017 ◽  
Vol 27 (09n10) ◽  
pp. 1579-1589 ◽  
Author(s):  
Reinier Morejón ◽  
Marx Viana ◽  
Carlos Lucena
Keyword(s):  
Machine Learning ◽  
Data Mining ◽  
Software Engineering ◽  
Multiagent Systems ◽  
Significant Role ◽  
Software Agents ◽  
Health Data ◽  
Large Datasets ◽  
Agent Oriented Software Engineering ◽  
Data Volume

Data mining is a hot topic that attracts researchers of different areas, such as database, machine learning, and agent-oriented software engineering. As a consequence of the growth of data volume, there is an increasing need to obtain knowledge from these large datasets that are very difficult to handle and process with traditional methods. Software agents can play a significant role performing data mining processes in ways that are more efficient. For instance, they can work to perform selection, extraction, preprocessing, and integration of data as well as parallel, distributed, or multisource mining. This paper proposes a framework based on multiagent systems to apply data mining techniques to health datasets. Last but not least, the usage scenarios that we use are datasets for hypothyroidism and diabetes and we run two different mining processes in parallel in each database.

scholarly journals Data mining agent conversations: A qualitative approach to multiagent systems analysis

2013 ◽  
Vol 230 ◽  
pp. 132-146 ◽  
Author(s):  
Emilio Serrano ◽  
Michael Rovatsos ◽  
Juan A. Botía
Keyword(s):  
Data Mining ◽  
Multiagent Systems ◽  
Systems Analysis ◽  
Qualitative Approach

scholarly journals Behavioral Analysis for Child Protection in Social Network through Data Mining and Multiagent Systems

2016 ◽  
Author(s):  
Mário Sérgio Rodrigues Falcão Jr. ◽  
Enyo José Tavares Gonçalves ◽  
Tciciana Linhares Coelho da Silva ◽  
Marcos de Oliveira
Keyword(s):  
Data Mining ◽  
Social Network ◽  
Multiagent Systems ◽  
Child Protection ◽  
Behavioral Analysis

Data Mining and Machine Learning

2020 ◽  
Author(s):  
Mohammed J. Zaki ◽  
Wagner Meira, Jr
Keyword(s):  
Machine Learning ◽  
Data Mining

Heart Rate Variability, Emotions, and Music

2010 ◽  
Vol 24 (2) ◽  
pp. 112-119 ◽  
Author(s):  
F. Riganello ◽  
A. Candelieri ◽  
M. Quintieri ◽  
G. Dolce
Keyword(s):  
Data Mining ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Vegetative State ◽  
Low Frequency ◽  
Emotional Reactions ◽  
Heart Beat ◽  
Healthy Controls ◽  
Frequency Spectra ◽  
Emotional Value

The purpose of the study was to identify significant changes in heart rate variability (an emerging descriptor of emotional conditions; HRV) concomitant to complex auditory stimuli with emotional value (music). In healthy controls, traumatic brain injured (TBI) patients, and subjects in the vegetative state (VS) the heart beat was continuously recorded while the subjects were passively listening to each of four music samples of different authorship. The heart rate (parametric and nonparametric) frequency spectra were computed and the spectra descriptors were processed by data-mining procedures. Data-mining sorted the nu_lf (normalized parameter unit of the spectrum low frequency range) as the significant descriptor by which the healthy controls, TBI patients, and VS subjects’ HRV responses to music could be clustered in classes matching those defined by the controls and TBI patients’ subjective reports. These findings promote the potential for HRV to reflect complex emotional stimuli and suggest that residual emotional reactions continue to occur in VS. HRV descriptors and data-mining appear applicable in brain function research in the absence of consciousness.

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