An Efficient Approach to Book Review Mining Using Data Classification

2015 ◽  
pp. 629-636
Author(s):  
Harvinder ◽  
Devpriya Soni ◽  
Shipra Madan
Keyword(s):  
Data Classification ◽  
Efficient Approach ◽  
Review Mining ◽  
Using Data

scholarly journals Application of Data Mining Techniques for Medical Data Classification: A Review

2018 ◽  
Vol 150 ◽  
pp. 06003 ◽  
Author(s):  
Saima Anwar Lashari ◽  
Rosziati Ibrahim ◽  
Norhalina Senan ◽  
N. S. A. M. Taujuddin
Keyword(s):  
Data Mining ◽  
Data Classification ◽  
Past Research ◽  
Medical Data ◽  
Extensive Literature ◽  
Literature Analysis ◽  
Data Mining Techniques ◽  
Medical Data Classification ◽  
Using Data

This paper investigates the existing practices and prospects of medical data classification based on data mining techniques. It highlights major advanced classification approaches used to enhance classification accuracy. Past research has provided literature on medical data classification using data mining techniques. From extensive literature analysis, it is found that data mining techniques are very effective for the task of classification. This paper analysed comparatively the current advancement in the classification of medical data. The findings of the study showed that the existing classification of medical data can be improved further. Nonetheless, there should be more research to ascertain and lessen the ambiguities for classification to gain better precision.

Book Review: Mining and Social Change

Urban Studies ◽  
1979 ◽  
Vol 16 (1) ◽  
pp. 129-130
Author(s):  
A. Slaven
Keyword(s):  
Social Change ◽  
Review Mining

scholarly journals Educational Data Classification Framework for Community Pedagogical Content Management using Data Mining

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Husnain Mushtaq ◽  
Imran Siddique ◽  
Dr. Babur ◽  
Muhammad Ahmed ◽  
Umair Muneer ◽  
...  
Keyword(s):  
Data Mining ◽  
Data Classification ◽  
Content Management ◽  
Pedagogical Content ◽  
Classification Framework ◽  
Using Data

scholarly journals Autenticação Contínua de Usuários Utilizando Contadores de Desempenho do Sistema Operacional

2019 ◽  
Author(s):  
César Andrade ◽  
Paulo Henrique Gonçalves ◽  
Hendrio Bragança ◽  
Eduardo Souto
Keyword(s):  
Operating System ◽  
Performance Indicators ◽  
System Performance ◽  
Data Classification ◽  
Behavioral Model ◽  
Assessment Methodology ◽  
Behavioral Models ◽  
Source Data ◽  
Using Data

Computer authentication systems based on login and password have been vulnerable to the action of unauthorized users. Currently, authentication techniques based on behavioral models predominantly use information extracted from mouse and/or keyboard to authenticate users. Operating system performance indicators can be used as an alternative. This work proposes an approach using data from performance indicators such as source data, CNN/LSTM networks for data classification, and reliability-based assessment methodology for the purpose of authenticating the user on an ongoing basis. The results obtained demonstrate the feasibility of using these attributes as the origin of the data to define a behavioral model. The best result obtained in this research is that 100% of genuine users are never inadvertently blocked and 100% of the imposters are detected after the average of three actions. Sistemas de autenticação de computadores baseados em credencias de contas (e.g. login e senha) têm sido vulneráveis à ação de usuários não autorizados. Atualmente, as técnicas de autenticação baseadas em modelos comportamentais predominantemente usam informações extraídas de mouse e/ou teclado para autenticar os usuários. Contadores de desempenho de sistema operacional podem ser utilizadas como alternativa. Este trabalho propõe uma abordagem utilizando dados de contadores de desempenho como dados de origem, redes CNN/LSTM para classificação dos dados e metodologia de avaliação baseada em nível de confiança com o propósito de autenticar o usuário de forma contínua. Os resultados obtidos demonstram a viabilidade do uso destes atributos como origem dos dados para definição de modelo comportamental. O melhor resultado obtido nesta pesquisa é que 100% dos usuários genuínos nunca são bloqueados inadvertidamente e 100% dos impostores são detectados após a média de três ações.

scholarly journals Human Sit Down Position Detection Using Data Classification and Dimensionality Reduction

2017 ◽  
Vol 2 (3) ◽  
pp. 749-754 ◽  
Author(s):  
Paul Rosero-Montalvo ◽  
Daniel Jaramillo ◽  
Stefany Flores ◽  
Diego Peluffo ◽  
Vanessa Alvear ◽  
...  
Keyword(s):  
Dimensionality Reduction ◽  
Data Classification ◽  
Position Detection ◽  
Using Data

Efficient Probabilistic Analysis and Design Optimization Using Data Classification Decision Boundaries

2010 ◽  
Author(s):  
Liping Wang ◽  
Arun K. Subramaniyan ◽  
Don Beeson
Keyword(s):  
Probabilistic Analysis ◽  
Adaptive Sampling ◽  
Optimization Design ◽  
Data Classification ◽  
Sampling Technique ◽  
Support Vector ◽  
Classification Methods ◽  
Analysis And Design ◽  
Using Data ◽  
Decision Boundaries

A new technique for performing probabilistic analysis and optimization design using data classification methods is investigated. The approach is based on nonlinear decision boundaries constructed from data classification methods. A statistical learning tool known as support vector machine (SVM) is used to construct the boundaries. An adaptive sampling technique is used to generate samples and update the approximated decision function. The proposed approach is demonstrated with several benchmark and engineering problems.

Human-sitting-pose detection using data classification and dimensionality reduction

2016 ◽  
Author(s):  
Santiago Nunez-Godoy ◽  
Vanessa Alvear-Puertas ◽  
Staling Realpe-Godoy ◽  
Edwin Pujota-Cuascota ◽  
Henry Farinango-Endara ◽  
...  
Keyword(s):  
Dimensionality Reduction ◽  
Data Classification ◽  
Pose Detection ◽  
Using Data
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