Currently, the rapid growth of information on the Internet makes automatic text classification play an important role to help people discovering desired information on enormous resources. Text mining, feature selection and classification algorithm have effect on the classification performance directly. In this paper, the comparative study of the text classification performance is proposed. It c...

The rule conflict is an important issue for associative classification due to a large set of rules. In this paper, a new approach called Associative Classification with Bayes (AC-Bayes) is proposed. To address rule conflicts, AC-Bayes has two distinguished features: (1) Associative classification is improved. (2) Naïve Bayesian model is applied in process of classification. A small set of high ...

In this work we are solving authorship attribution and author profiling tasks (by focusing on the age and gender dimensions) for the Lithuanian language. This paper reports the first results on literary texts, which we compared to the results, previously obtained with different functional styles and language types (i.e., parliamentary transcripts and forum posts). Using the Naïve Bayes Multinom...

Opinion Question Answering (Opinion QA) is the task of enabling users to explore others opinions toward a particular service of product in order to make decisions. Arabic Opinion QA is more challenging due to its complex morphology compared to other languages and has many varieties dialects. On the other hand, there are insignificant research efforts and resources available that focus on Opinio...

As part of the 2006 i2b2 NLP Shared Task, we explored two methods for determining the smoking status of patients from their hospital discharge summaries when explicit smoking terms were present and when those same terms were removed. We developed a simple keyword-based classifier to determine smoking status from de-identified hospital discharge summaries. We then developed a Naïve Bayes classif...

In the modern Digital Era, Data Mining is the powerful area for analyzing the large data sets to get unexpected relationships (models). The analysis of statistical data on sequential data points measured at regular time interval over a period of time is time series analysis. Time series analysis is used in predicting future occurrence of a time based event. One of the main areas where time seri...

Today microblogging has increasingly become a means of information diffusion via user's retweeting behavior. Since retweeting content, as context information of microblogging, is an understanding of microblogging, hence, user's retweeting sentiment tendency analysis has gradually become a hot research topic. Targeted at online microblogging, a dynamic social network, we investigate how to explo...

Security managers and network engineers are increasingly required to implant corporative spam-filtering services. End-users don't want to interact with spam-classify applications, so network engineers usually have to implement and manage the spam-filtering system at the e-mail server. Due to the processing speeds needed to put these solutions into work at the server level, the options at hand a...

Intrusion detection systems (IDSs) are currently drawing a great amount of interest as a key part of system defence. IDSs collect network traffic information from some point on the network or computer system and then use this information to secure the network. Recently, machine learning methodologies are playing an important role in detecting network intrusions (or attacks), which further helps...

The naïve Bayes classifier (NBC) is one of the most popular classifiers for class prediction or pattern recognition from microarray gene expression data (MGED). However, it is very much sensitive to outliers with the classical estimates of the location and scale parameters. It is one of the most important drawbacks for gene expression data analysis by the classical NBC. The gene expression data...