A Survey of Arabic Text Mining

Recently, text mining has become an interesting research field due to the huge amount of existing text on the web. Text mining is an essential field in the context of data mining for discovering interesting patterns in textual data. Examining and extracting of such information patterns from huge datasets is considered as a crucial process. A lot of survey studies were conducted for the purpose of using various text mining methods for unstructured datasets. It has been noticed that comprehensive survey studies in the Arabic context were neglected. This study aims to give a broad review of various studies related to the Arabic text mining with more focus on the Holy Quran, sentiment analysis, and web documents. Furthermore, the synthesis of the research problems and methodologies of the surveyed studies will help the text mining scholars in pursuing their future studies.

[1]  Khaled Shaalan,et al.  NERA 2.0: Improving coverage and performance of rule-based named entity recognition for Arabic* , 2016, Natural Language Engineering.

[2]  Ali Selamat,et al.  Arabic script web page language identifications using decision tree neural networks , 2011, Pattern Recognit..

[3]  Said A. Salloum,et al.  A Survey of Lexical Functional Grammar in the Arabic Contex , 2016 .

[4]  Walid Cherif,et al.  A new modeling approach for Arabic opinion mining recognition , 2015, 2015 Intelligent Systems and Computer Vision (ISCV).

[5]  Xin Chen,et al.  Mining Social Media Data for Understanding Students’ Learning Experiences , 2014, IEEE Transactions on Learning Technologies.

[6]  Sohail Iqbal Malik,et al.  The Impact of Google Apps at Work: Higher Educational Perspective , 2016, Int. J. Interact. Mob. Technol..

[7]  Jason Q. Zhang,et al.  When does electronic word-of-mouth matter? A study of consumer product reviews☆ , 2010 .

[8]  Gurpreet Singh Lehal,et al.  A Survey of Text Mining Techniques and Applications , 2009 .

[9]  Mostafa Al-Emran,et al.  Mining and Exploration of Credit Cards Data in UAE , 2015, 2015 Fifth International Conference on e-Learning (econf).

[10]  Aqil M. Azmi,et al.  Arabic tweets sentiment analysis – a hybrid scheme , 2016, J. Inf. Sci..

[11]  Khaled Shaalan,et al.  Parsing modern standard Arabic using Treebank resources , 2015, 2015 International Conference on Information and Communication Technology Research (ICTRC).

[12]  Ahmed Ech-Cherif,et al.  Arabic texts analysis for topic modeling evaluation , 2011, Information Retrieval.

[13]  Zakaria Suliman Zubi.  Using some web content mining techniques for Arabic text classification , 2009 .

[14]  Ralf Steinberger,et al.  A survey of methods to ease the development of highly multilingual text mining applications , 2011, Language Resources and Evaluation.

[15]  Rolf Ingold,et al.  Text Detection in Arabic News Video Based on SWT Operator and Convolutional Auto-Encoders , 2016, 2016 12th IAPR Workshop on Document Analysis Systems (DAS).

[16]  Mohammad S. Khorsheed,et al.  Comparative evaluation of text classification techniques using a large diverse Arabic dataset , 2013, Language Resources and Evaluation.

[17]  Taisir Eldos,et al.  Arabic Text Data Mining: a Root-Based Hierarchical Indexing Model , 2003 .

[18]  Lillian Lee,et al.  Opinion Mining and Sentiment Analysis , 2008, Found. Trends Inf. Retr..

[19]  Luis Alfonso Ureña López,et al.  OCA: Opinion corpus for Arabic , 2011, J. Assoc. Inf. Sci. Technol..

[20]  Khaled Shaalan,et al.  A Survey of Intelligent Language Tutoring Systems , 2014, 2014 International Conference on Advances in Computing, Communications and Informatics (ICACCI).

[21]  F ya David,et al.  Data Warehousing and Data Mining , 2015 .

[22]  Ke Zhang,et al.  Examining mobile learning trends 2003–2008: a categorical meta-trend analysis using text mining techniques , 2011, Journal of Computing in Higher Education.

[23]  Khaled Shaalan,et al.  Arabic Natural Language Processing: Challenges and Solutions , 2009, TALIP.

[24]  Khaled Shaalan,et al.  A Review and Future Perspectives of Arabic Question Answering Systems , 2016, IEEE Transactions on Knowledge and Data Engineering.

[25]  Djelloul Ziadi,et al.  Subsequence kernels-based Arabic text classification , 2014, 2014 IEEE/ACS 11th International Conference on Computer Systems and Applications (AICCSA).

[26]  A. SalloumSaid,et al.  A survey of text mining in social media facebook and twitter perspectives , 2017 .

[27]  Fawaz S. Al-Anzi,et al.  Toward an enhanced Arabic text classification using cosine similarity and Latent Semantic Indexing , 2017, J. King Saud Univ. Comput. Inf. Sci..

[28]  Abdul Baquee Muhammad,et al.  Annotation of conceptual co-reference and text Mining the Qur'an , 2012 .

[29]  Eric Atwell,et al.  Knowledge representation of the Quran through frame semantics: a corpus-based approach , 2009 .

[30]  Khaled Shaalan,et al.  Learners and educators attitudes towards mobile learning in higher education: State of the art , 2015, 2015 International Conference on Advances in Computing, Communications and Informatics (ICACCI).

[31]  Qasem A. Al-Radaideh,et al.  Rough Set Theory for Arabic Sentiment Classification , 2014, 2014 International Conference on Future Internet of Things and Cloud.

[32]  Rehab Duwairi,et al.  Arabic Sentiment Analysis Using Supervised Classification , 2014, 2014 International Conference on Future Internet of Things and Cloud.

[33]  Mostafa Al-Emran,et al.  Hierarchical Reinforcement Learning: A Survey , 2015 .

[34]  Abdel-Rahman Hedar,et al.  Sentiment Analysis of Arabic Slang Comments on Facebook , 2014, BIOINFORMATICS 2014.

[35]  Philip Shapira,et al.  Use of web mining in studying innovation , 2014, Scientometrics.

[36]  Masao Fuketa,et al.  A new approach for Arabic text classification using Arabic field-association terms , 2011, J. Assoc. Inf. Sci. Technol..

[37]  Khaled Shaalan,et al.  A Survey of Arabic Named Entity Recognition and Classification , 2014, CL.

[38]  Fouzi Harrag.  Text mining approach for knowledge extraction in Sahîh Al-Bukhari , 2014, Comput. Hum. Behav..

[39]  Muazzam Ahmed Siddiqui,et al.  Building an Arabic Sentiment Lexicon Using Semi-supervised Learning , 2014, J. King Saud Univ. Comput. Inf. Sci..

[40]  S. Biruntha,et al.  Techniques on text mining , 2012, 2012 IEEE International Conference on Advanced Communication Control and Computing Technologies (ICACCCT).

[41]  Lei Zhang,et al.  Sentiment Analysis and Opinion Mining , 2017, Encyclopedia of Machine Learning and Data Mining.

[42]  Ali Selamat,et al.  Arabic web pages clustering and annotation using semantic class features , 2014, Journal of King Saud University: Computer and Information Sciences.

[43]  Mohamed Osman Hegazi,et al.  Processing the Text of the Holy Quran: a Text Mining Study , 2015 .

[44]  Heider A. Wahsheh,et al.  Analyzing the Popular Words to Evaluate Spam in Arabic Web Pages , 2012 .