The paper presents three machine learning based keyphrase extraction methods that respectively use Decision Trees, Naïve Bayes, and Artificial Neural Networks for keyphrase extraction. We consider keyphrases as being phrases that consist of one or more words and as representing the important concepts in a text document. The three machine learning based keyphrase extraction methods that we use f...

In this paper, we compare the performance of three classifiers for Arabic text categorization. In particular, the naïve Bayes, k-nearest-neighbors (knn), and distance-based classifiers were used. Unclassified documents were preprocessed by removing punctuation marks and stopwords. Each document is then represented as a vector of words (or of words and their frequencies as in the case of the naï...

Exploratory data analysis over foreign language text presents virtually untapped opportunity. This work incorporates Naïve Bayes classifier with Case-Based Reasoning in order to classify and analyze Arabic texts related to fanaticism. The Arabic vocabularies are converted to equivalent English words using conceptual hierarchy structure. The understanding process operates at two phases. At the f...

Cost-sensitive decision tree and cost-sensitive naïve Bayes are both new cost-sensitive learning models proposed recently to minimize the total cost of test and misclassifications. Each of them has its advantages and disadvantages. In this paper, we propose a novel cost-sensitive learning model, a hybrid cost-sensitive decision tree, called DTNB, to reduce the minimum total cost, which integrat...

A Bayesian network (or a belief network) is a probabilistic graphical model that represents a set of variables and their probabilistic independencies. Some researches often involve continuous random variables. In order to apply these continuous variables to BN models, these variables should convert into discrete variables with limited states, often two. During the discretization process, one pr...

This paper examines how six online multiclass text classification algorithms perform in the domain of email tagging within the TaskTracer system. TaskTracer is a project-oriented user interface for the desktop knowledge worker. TaskTracer attempts to tag all documents, web pages, and email messages with the projects to which they are relevant. In previous work, we deployed an SVM email classifi...

Parkinson's disease (PD) has broadly been associated with mild cognitive impairment (PDMCI) and dementia (PDD). Researchers have studied surrogate, neuroanatomic biomarkers provided by magnetic resonance imaging (MRI) that may help in the early diagnosis of this condition. In this article, four classification models (naïve Bayes, multivariate filter-based naïve Bayes, filter selective naïve Bay...

Here we propose a probabilistic model for determining link formation, using Naïve Bayes Classifier on nontopological attribute values of nodes, in a social network. The proposed model gives a score which helps to determine the relationship strength in a non-formed link. In addition to Naïve Bayes Classifier, weighted Average of the Attribute value match helps to determine the friendship score o...

At present, most of the precipitation’s level predictions use the laws of nature to build the mathematical model which contains one or more series level to carry out the numerical simulation, as thus to analyze the causes and consequences of the evolution. Bayesian model is one kind of the foregoing said. In the Bayesian classification model, Naive Bayes model is known for its stability and eas...