A Comparative Survey on Arabic Stemming: Approaches and Challenges

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Intelligent Information Management

ISSN Print: 2160-5912
ISSN Online: 2160-5920
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"A Comparative Survey on Arabic Stemming: Approaches and Challenges"
written by Mohammad Mustafa, Afag Salah Eldeen, Sulieman Bani-Ahmad, Abdelrahman Osman Elfaki,
published by Intelligent Information Management, Vol.9 No.2, 2017

has been cited by the following article(s):

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[8]	Exploiting discourse relations to produce Arabic extracts
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[9]	Sentiment Analysis of Political Post Classification Based on XGBoost
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[10]	Computer and Information Sciences
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[11]	Arabic light-based stemming: a comparative study among ligh10 stemmer, P-stemmer, and Conditional light stemmer
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[12]	Political Arabic Articles Orientation Using Rough Set Theory with Sentiment Lexicon
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[13]	Arabic question answering system: a survey
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[14]	Comparative Analysis of Nine Arabic Stemmers on Microblog Information Retrieval
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[15]	Political Arabic Articles Classification Based on Machine Learning and Hybrid Vector
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[16]	A study on Arabic sign language recognition for differently abled using advanced machine learning classifiers
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[17]	Enhanced Arabic Root-Based Lemmatizer ةيبرعلا روذجلل نسحم رزيتيميل‎
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[18]	Sentiment Analysis for Arabic Reviews using Machine Learning Classification Algorithms
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[19]	Extractive Multi-Document Arabic Text Summarization Using Evolutionary Multi-Objective Optimization With K-Medoid Clustering
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[20]	Comparing the Effectiveness of the Improved ARLSTem Algorithm with Existing Arabic Light Stemmers
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[21]	Arabic Multi-Objective Optimization with K-mediod Clustering for Multi-Document Summarization
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[22]	Improving Arabic Stemmer: ISRI Stemmer
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[23]	An efficient single document Arabic text summarization using a combination of statistical and semantic features
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[24]	ASA: A framework for Arabic sentiment analysis
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[25]	Out of vocabulary word detection and recovery in Arabic handwritten text recognition
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[26]	Developing Two Different Novel Techniques for Arabic Text Stemming
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[27]	CLASSIFYING ARABIC TEXT USING DEEP LEARNING
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[28]	Classifying Political Arabic Articles Using Support Vector Machine with Different Feature Extraction
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[29]	Arabic Document Indexing for Improved Text Retrieval
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[30]	Arabic Light Stemming: A Comparative Study between P-Stemmer, Khoja Stemmer, and Light10 Stemmer
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[31]	P-Stemmer or NLTK Stemmer for Arabic Text Classification?
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[32]	Political Articles Categorization Based on Different Naïve Bayes Models
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[33]	Elaboration d'un corpus de test pour un système d'évaluation automatique des réponses courtes
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[34]	Improving Sentiment Analysis of Moroccan Tweets Using Ensemble Learning
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[35]	Arabic Sign Language Recognition: A Review

[1]	Multi-class sentiment classification on Bengali social media comments using machine learning International Journal of Cognitive Computing in Engineering, 2023 DOI:10.1016/j.ijcce.2023.01.001

[2]	Arabic Text Detection Using Rough Set Theory: Designing a Novel Approach IEEE Access, 2023 DOI:10.1109/ACCESS.2023.3278272

[3]	Automatic sarcasm detection in Arabic tweets: resources and approaches Journal of Intelligent & Fuzzy Systems, 2023 DOI:10.3233/JIFS-224514

[4]	Meta-search based approach for Arabic information retrieval Online Information Review, 2022 DOI:10.1108/OIR-11-2020-0515

[5]	Political Arabic Articles Orientation Using Rough Set Theory With Sentiment Lexicon IEEE Access, 2021 DOI:10.1109/ACCESS.2021.3054919

[6]	Arabic light-based stemming: a comparative study among ligh10 stemmer, P-stemmer, and Conditional light stemmer 2021 2nd Information Technology To Enhance e-learning and Other Application (IT-ELA), 2021 DOI:10.1109/IT-ELA52201.2021.9773743

[7]	Extractive Multi-Document Arabic Text Summarization Using Evolutionary Multi-Objective Optimization With K-Medoid Clustering IEEE Access, 2020 DOI:10.1109/ACCESS.2020.3046494

[8]	Comparative Analysis of Nine Arabic Stemmers on Microblog Information Retrieval 2020 International Conference on Asian Language Processing (IALP), 2020 DOI:10.1109/IALP51396.2020.9310456

[9]	Political Arabic Articles Classification Based on Machine Learning and Hybrid Vector 2020 5th International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications (CITISIA), 2020 DOI:10.1109/CITISIA50690.2020.9371791

[10]	Sentiment Analysis for Arabic Reviews using Machine Learning Classification Algorithms 2020 International Conference on Innovative Trends in Communication and Computer Engineering (ITCE), 2020 DOI:10.1109/ITCE48509.2020.9047822

[11]	Developing Two Different Novel Techniques for Arabic Text Stemming Intelligent Information Management, 2019 DOI:10.4236/iim.2019.111001

[12]	Arabic Light Stemming: A Comparative Study between P-Stemmer, Khoja Stemmer, and Light10 Stemmer 2019 Sixth International Conference on Social Networks Analysis, Management and Security (SNAMS), 2019 DOI:10.1109/SNAMS.2019.8931842

[13]	P-Stemmer or NLTK Stemmer for Arabic Text Classification? 2019 Sixth International Conference on Social Networks Analysis, Management and Security (SNAMS), 2019 DOI:10.1109/SNAMS.2019.8931818

[14]	Improving Arabic Stemmer: ISRI Stemmer 2019 IEEE 5th International Conference on Wireless and Telematics (ICWT), 2019 DOI:10.1109/ICWT47785.2019.8978248

[15]	Comparing the Effectiveness of the Improved ARLSTem Algorithm with Existing Arabic Light Stemmers 2019 International Conference on Theoretical and Applicative Aspects of Computer Science (ICTAACS), 2019 DOI:10.1109/ICTAACS48474.2019.8988118

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