Spams are becoming a serious threat for the users of online social networks especially for the ones like of twitter. twitter’s structural features make it more volatile to spam attacks. In this paper, we propose a spam detection approach for twitter based on sentimental features. We perform our experiments on a data collection of 29K tweets with 1K tweets for 29 trending topics of 2012 on twitt...

System administrators have to analyze a number of system parameters to identify performance bottlenecks in a system. The major contribution of this paper is a utility – EvoPerf – which has the ability to autonomously monitor different system-wide parameters, requiring no user intervention, to accurately identify performance based anomalies (or bottlenecks). EvoPerf uses Windows Perfmon utility ...

Large computational value has always been a restraint in processing huge network intrusion data. This problem can be extenuated through feature selection to abbreviate the size of the network data involved. In this paper, we first deal existing feature selection methods that are computationally executable for processing vast network intrusion datasets. In this paper, we study and analysis of fo...

This paper reports on the empirical evaluation of five machine learning algorithm such as J48, BayesNet, OneR, NB and ZeroR using ten performance criteria: accuracy, precision, recall, F-Measure, incorrectly classified instances, kappa statistic, mean absolute error, root mean squared error, relative absolute error, root relative squared error. The aim of this paper is to find out which classif...

Flash flooding is a type of global devastating hydrometeorological disaster that seriously threatens people’s property and physical safety, as well the normal operation water conservancy facilities, such reservoirs, so an accurate assessment reservoir risk for certain areas necessary. Therefore, purpose this study was to propose novel methodological approach modelling based on feature selection...

This paper proposed a method using principle component analysis based on graph entropy (PCA-GE) and J48 decision tree on electroencephalogram (EEG) signals to predict whether a person is alcoholic or not. Analysis is performed in two stages: feature extraction and classification. The principle component analysis (PCA) chooses the optimal subset of channels based on graph entropy technique and t...

Data mining is a technique that involves the application of specific algorithms, which generate a list of patterns based on large volumes of information that is useful for decision making in wide fields of application, as detection of patterns in diseases. This paper proposes to carry out a cancer analysis by means of data mining techniques, applied on a sample of 3365 cases, using association ...

The role of technology in education industry is increasing day by day specially after reaching the growth rate of the IT industry to the saturation point. That is why, even AICTE has closed the affiliation of engineering colleges in number of states. So, education industry can change their plan to survive in this environment by using data mining techniques to identify the outstanding students a...

A lot of time is spent searching for the most performing data mining algorithms applied in clinical diagnosis. The study set out to identify the most performing predictive data mining algorithms applied in the diagnosis of Erythemato-squamous diseases. The study used Naive Bayes, Multilayer Perceptron and J48 decision tree induction to build predictive data mining models on 366 instances of Ery...