KACST Arabic Text Classification Project: Overview and Preliminary Results
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Summary
An overview of King Abdulaziz City for Science and Technology (KACST) Arabic Text Classification Project will be illustrated along with some preliminary results, which will contribute to the better understanding and elaboration of Arabic text classification techniques.
- Type
- article
- Published
- 2008-01-01
- Cited by
- 15
- References
- 24
- Access
- Open access
- OpenAlex
- https://openalex.org/W50597791
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:59739079
Keywords
Computer science, Arabic, Categorization, Natural language processing, Process (computing)
References
- Arabic Text Classification Using N-Gram Frequency Statistics A Comparative Study
- A Neural Network Based Method for Text Classification using Root Words to Form Pattern Vectors
- An empirical study of the naive Bayes classifier
- Programs for Machine Learning
- Fast Algorithms for Mining Association Rules in Large Databases
- A comparison of event models for naive bayes text classification
- Text Classification in Asian Languages without Word Segmentation
- Authorship Attribution with Support Vector Machines
- Using text mining to infer semantic attributes for retail data mining
- Improved Use of Continuous Attributes in C4.5
- Text classification by boosting weak learners based on terms and concepts
- Chi Square Feature Extraction Based Svms Arabic Language Text Categorization System
- The use of bigrams to enhance text categorization
- Text classification using ESC-based stochastic decision lists
- Automatic Arabic Document Categorization Based on the Naïve Bayes Algorithm
- Improving a Page Classifier with Anchor Extraction and Link Analysis
- Machine learning in automated text categorization
- C4.5: Programs for Machine Learning
- YALE: rapid prototyping for complex data mining tasks
- Feature selection using linear classifier weights: interaction with classification models
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- Naïve Bayesian Based on Chi Square to Categorize Arabic Data
- Rational Kernels for Arabic Stemming and Text Classification
- Subsequence kernels-based Arabic text classification
- Weirdness Coefficient as a Feature Selection Method for Arabic Special Domain Text Classification
- Prediction Phase in Associative Classification Mining
- Rational kernels for Arabic Root Extraction and Text Classification
- Classification of Arabic Twitter Users: A Study Based on User Behaviour and Interests
- Language Independent n-Gram-Based Text Categorization with Weighting Factors: A Case Study
- Stemming impact on Arabic text categorization performance: A survey
- Integrating associative rule-based classification with Naïve Bayes for text classification
- Automatic Arabic Document Classification Based on the HRWiTD Algorithm
- Arabic text classification methods: Systematic literature review of primary studies
- Rational Kernels for Arabic Text Classification
- Using Word N-Grams as Features in Arabic Text Classification
- TEXT ANALYSIS ON TWITTER DATASET USING NEURAL NETWORK AND BAYESIAN CLASSIFIER
- Classification Methods : Systematic Literature Review of Primary Studies
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