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Experiments on the Use of Feature Selection and Machine Learning Methods in Automatic Malay Text Categorization
2013
Procedia Technology - Elsevier
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Although, there is a wide range of supervised machine learning methods have been applied to categorize English, relatively, only a few studies have been done on Malay text categorization. ...
This paper reports our comparative evaluation of three machine learning methods on Malay text categorization. ...
FSS improves the performance of text categorization tasks in terms of learning speed and effectiveness. ...
doi:10.1016/j.protcy.2013.12.254
fatcat:lsvmumv5yndt3njtf3jkh6ltme
Information gain and divergence-based feature selection for machine learning-based text categorization
2006
Information Processing & Management
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In this paper, we introduce a new information gain and divergence-based feature selection method for statistical machine learning-based text categorization without relying on more complex dependence models ...
for text categorization. ...
A growing number of statistical classification methods and machine learning techniques have been applied to text categorization in recent years (Yang & Liu, 1999) . ...
doi:10.1016/j.ipm.2004.08.006
fatcat:tj6zfsx4yfaermm4odyvkvhs2e
Improving Text Categorization By Using A Topic Model
2011
Advanced Computing An International Journal
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Most text categorization algorithms represent a document collection as a Bag of Words (BOW).The BOW representation is unable to recognize synonyms from a given term set and unable to recognize semantic ...
Three text categorization algorithms: Naïve Bayes (NB), Support Vector Machines (SVM) and Decision tree, are used for evaluation. ...
Text categorization is a well-studied research area related to information retrieval, machine learning and text mining. ...
doi:10.5121/acij.2011.2603
fatcat:ut53yxpv5neynfnhdxjvv62l4i
Arabic Text Categorization Algorithm Using Vector Evaluation Method
2014
International Journal of Computer Science & Information Technology (IJCSIT)
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Text categorization is the process of grouping documents into categories based on their contents. ...
The main problem in text categorization is how to improve the classification accuracy. Although Arabic text categorization is a new promising field, there are a few researches in this field. ...
Its work as
replacing idf by the category-based term evaluation function tfidf .They applied it on standard
Reuters-21578.They experimented STW by support vector machines (SVM) and three term
selection ...
doi:10.5121/ijcsit.2014.6606
fatcat:2fcnfbx4irdojmer5qegkhccn4
Arabic Text Classification Based on Features Reduction Using Artificial Neural Networks
2013
2013 UKSim 15th International Conference on Computer Modelling and Simulation
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Text categorization is one solution to tackle this problem. ...
Methods of assigning weights and features reductions that reflect the importance of each term are discussed. Each Arabic document is represented by the term weighting scheme. ...
Hmeidi et al (2007) reported a comparative study of two machine learning methods on Arabic text categorization. ...
doi:10.1109/uksim.2013.135
dblp:conf/uksim/ZaghoulA13
fatcat:3h67ywpzhbdtrgey3stbuywhuu
Arabic Text Categorization using Machine Learning Approaches
2018
International Journal of Advanced Computer Science and Applications
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Arabic Text categorization is considered one of the severe problems in classification using machine learning algorithms. ...
Results show that the DMNBtext learning algorithm achieved higher performance compared to other machine learning algorithms in categorizing Arabic text. ...
In this paper, an automated categorization system has been introduced based on machine learning algorithms for Arabic text documents. ...
doi:10.14569/ijacsa.2018.090332
fatcat:ap477n2nzzcbvolrcbvmwnkolu
Index split decision tree and compositional deep neural network for text categorization
2017
International Journal of Engineering & Technology
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With this objective, a novel and efficient text categorization framework based on decision tree model is used in order to categorize text according to superior and subordinate level. ...
With the growing research work for text categorization, it has become important to categorize the research outcome and provide the learners with an effective machine learning method, a framework called ...
CT = Time (T cat correct ) * D size (16)
Results and analysis In the experiments, comparison of machine learning based text categorization method with two other text categorizations with machine learning ...
doi:10.14419/ijet.v7i1.1.9953
fatcat:uasnwovv4rfbhj26tvgznxd5km
Support Vector Machines based Arabic Language Text Classification System: Feature Selection Comparative Study
[chapter]
2008
Advances in Computer and Information Sciences and Engineering
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This paper investigates the effectiveness of six commonly used feature selection methods, Evaluation used an in-house collected Arabic text classification corpus, and classification is based on Support ...
Feature selection is essential for effective and accurate text classification systems. ...
[40] by a filter-based method which selects a subset of features by filtering based on the scores which were assigned by a specific weighting method, by a wrapper approach, where the subset of features ...
doi:10.1007/978-1-4020-8741-7_3
dblp:conf/cisse/Mesleh07
fatcat:o7zi45wsnvc6ddxxj3qlr3s5b4
English poems categorization using text mining and rough set theory
2020
Bulletin of Electrical Engineering and Informatics
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predefined the category based on the text content in a document. ...
In this paper we will solve the problem of how to categorize the English poem into one of the English Poems categorizations by using text mining technique and machine learning algorithm, Our data set consist ...
Text representation By using machine learning methods for text categorization and text mining, we need to represent the text document in one forms that make learning algorithm easy to work and applies ...
doi:10.11591/eei.v9i4.1898
fatcat:wt5hxbkd2jct3hiedt426h3gb4
Profile Categorization System based on Features Reduction
2018
International Symposium on Artificial Intelligence and Mathematics
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In this regard, author profiling tries to determine the profile category of authors by analysing their published texts. ...
In the first module TF-IDF with threshold filtering method are used to extract the relevant terms. While support vector machine (SVM) is used in the classifying module. ...
TF-IDF was used by (Cossu & al. 2014) in the task of profile categorization by assigning a weight for each term and then creating a term model for each category. ...
dblp:conf/isaim/MabroukHO18
fatcat:fp4hwacat5cidps3irztw2aibq
A hybrid BSO-Chi2-SVM approach to Arabic text categorization
2013
2013 ACS International Conference on Computer Systems and Applications (AICCSA)
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In this paper, we present the results of Arabic text categorization based on three different approaches: artificial neural networks, support vector machines (SVMs) and a hybrid approach BSO-CHI-SVM. ...
Automatic categorization of documents consists in assigning a category to a text based on the information it contains. It aims to automate the association of a document with a category. ...
One way to approach the problem of automatic text categorization is by means of supervised machine learning techniques. ...
doi:10.1109/aiccsa.2013.6616437
dblp:conf/aiccsa/BelkebirG13
fatcat:eja6fh6pwzhfbiawt4a2m5qnge
A Review of Different Text Categorization Techniques
2018
International Journal of Engineering & Technology
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In this paper, we focus on a major internet problem which is a huge amount of uncategorized text. We review existing techniques used for feature selection and categorization. ...
After reviewing the existing literature, it was found that there exist some gaps in existing algorithms, one of which is a requirement of the labeled dataset for the training of the classifier. ...
The text categorization problem can be achieved using the machine learning process. The term Machine learning refers to the automated detection of the meaningful patterns in data. ...
doi:10.14419/ijet.v7i3.8.15210
fatcat:2axkrrhiuzcltlojexx4abmb2m
Empirical Evaluations of Automatic Forum Selector
2012
International Journal of Computer and Communication Engineering
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In this study, we propose the use of text categorization approach to automatically select a target forum category. The empirical evaluations demonstrate the utility of text categorization approach. ...
We also found that decision tree outperformed other machine classifiers. ...
Text Categorization Text categorization (also called text classification) is to predict a category from a pre-defined set based on the characteristics of natural language texts (Sebastiani 2002) . ...
doi:10.7763/ijcce.2012.v1.16
fatcat:b74drzjo3bclfe5r6zgysxgu6q
A Comparative Study on Different Types of Approaches to Text Categorization
2012
International Journal of Machine Learning and Computing
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Text Categorization is a pattern classification task for text mining and necessary for efficient management of textual information systems. ...
This paper presents a comparative study on different types of approaches to text categorization. ...
Therefore, machine learning based approaches are replacing rule based one for text categorization. ...
doi:10.7763/ijmlc.2012.v2.158
fatcat:aum7nxk3kba75h4liw53u554bu
Hybrid Machine Learning Approach For Text Categorization
2007
Zenodo
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Text categorization - the assignment of natural language documents to one or more predefined categories based on their semantic content - is an important component in many information organization and ...
This paper discusses the use multilayer neural network initialization with decision tree classifier for improving text categorization accuracy. ...
However there is still need more accurate text classifiers based on new learning machine learning approaches. ...
doi:10.5281/zenodo.1073114
fatcat:bjtl2are5zflvolubi3vgg6f2i
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