Awards: Merit award for PhD viva-voce examination, 2011. Chancellor's award (Gold Medal) 2011, based on excellent academic achievement, from University, 2011, Technology Malaysia (Universiti Teknologi Malaysia-UTM). Postgraduate best student award (Gold Medal) 2011, based on excellent academic achievement, 2011 from School of Graduate studies, University Technology Malaysia (Universiti Teknologi Malaysia-UTM). Silver award for invention of Cross Language Plagiarism Detection at the 12th Industrial Art, 2010 and Technology Exhibition 2010, UTM, Johor, Malaysia. Microsoft award for best paper presented in the 9th Postgraduate Annual Research Seminar, 2008.
EDUCATION
• PhD (Computer Science) - passed with Merit, Universiti Teknologi Malaysia (UTM), Johor (2008 –2011).
Thesis Title: Fuzzy Swarm Diversity based Text Summarization (Text Summarization).
• M. Sc. (Computer Science) - Universiti Teknologi Malaysia (UTM), Johor (2004 –2006).
Thesis Title: Comparison and Fusion of Retrieval Schemes based on Different Structures, Similarity Measures and Weighting Schemes (Information Retrieval).
• B. Sc. (Computer Science), Hadhramout University (HU), Hadhramout (1996 – 2000).
Statistical Features and PageRank Scoring Fusion for Arabic Text Summarization Omer Salim Bahakam, Mohammed Salem Farag Binwahlan, Hassen A. Mogaibel International Conference on Intelligent Technology System and Service for Internet of Everything Itss Ioe 2022, 2022 online text content is increasing daily, making it a big challenge for readers to find the required information. So, providing a gist of the available text content can help those readers save their time and effort. This operation is completed by Automatic Text Summarization (ATS), which creates a summary for the entire text. Automatic Text Summarization can be achieved by many techniques, such as graph theory, statistics, machine learning, and clustering methods. Each of the above techniques takes care of a specific issue of text which other techniques do not. Text summarization for the Arabic language suffers from a lack of resources and language complexity. So, it is worthwhile to take the advantages of two or more text summarization techniques and fuse them together to improve their performance and enhance their summary quality. This study proposes a method that combines two of the ATS methods, which are the statistical based method and the graph-based modified PageRank algorithm. Graph-based techniques take care of relationships among document sentences, whereas statistical-based techniques take care of signalizing important sentences. Experiment results show that proposed method achieved a good performance. The Essex Arabic Summaries Corpus (EASC) was used as evaluation data.
Event-Based Rumor Detection using LSTM Models For Arabic Content on Twitter Arwa AlAttas, Hassen A. Mogaibel, Mohammed Salem BinWahlan International Conference on Intelligent Technology System and Service for Internet of Everything Itss Ioe 2022, 2022 Due to the flexibility of sharing and exchanging information, Microblogging networks such as Twitter have become more and more popular over the last few years. The nature of social media as well provides a rich and facilitated ground for rumormongers to spread false stories and information that may result in major mess and unpredictable reactions from involved individuals. Detecting rumors automatically at their early formative and diffusion phases is particularly crucial to minimize their negative and catastrophic effects. Many effective solutions to detect rumors on Twitter have been presented over the last few years. However, most of the researches were limited to certain languages, such as English and Chinese. Few studies focused on the Arabic Language; Most of those studies were concerned only to detect rumors at the tweet-level and neglecting event-level based detection. In this paper, we built two RNN-LSTM deep learning models to classify Arabic Twitter content as rumor or non-rumor more efficiently utilizing linguistic features. The constructed models are capable to detect rumor events on Twitter. An attention mechanism was embedded to optimize the performance of these models where they achieved accuracy above 93%.
Differential evolution cluster-based text summarization methods Albaraa Abuobieda, Naomie Salim, Mohammed Salem Binwahlan, Ahmed Hamza Osman Proceedings 2013 International Conference on Computer Electrical and Electronics Engineering Research Makes A Difference Icceee 2013, 2013 In this paper, three similarity measures; Normalized Google Distance (NGD), Jaccard and Cosine Similarity measures were employed and tested for textual based clustering problem. A robust evolutionary algorithm called Differential Evolution algorithm was also used to optimize the data clustering process and increase the quality of the generated text summaries. The Recall Oriented Under Gisting Evaluation (ROUGE) was used as an evaluation measure toolkit to assess the quality of the summaries. Experimental results showed that all of our proposed methods outperformed the benchmark methods. More importantly, the Jaccard-similarity based method surpassed all the other proposed methods in this study.
Plagiarism detection scheme based on semantic role labeling Ahmed Hamza Osman, Naomie Salim, Mohammed Salem Binwahlan, Ssennoga Twaha, Yogan Jaya Kumar, Albaraa Abuobieda Proceedings 2012 International Conference on Information Retrieval and Knowledge Management CAMP 12, 2012 Nowadays, many documents are available on the internet and are easy to access. Due to this wide availability, users can easily create a new document by copying and pasting. Plagiarism occurs when the content is copied without permission or citation. This paper introduces a plagiarism detection technique based on the Semantic Role Labeling (SRL). The technique analyses and compares text based on the semantic allocation for each term inside the sentence. SRL is superior in generating arguments for each sentence semantically. In addition, experimental results on PAN-PC-09 data sets showed that our method outperforms the modern methods for plagiarism detection in terms of Recall, Precision and F-measure.
Fuzzy genetic semantic based text summarization Ladda Suanmali, Naomie Salim, Mohammed Salem Binwahlan Proceedings IEEE 9th International Conference on Dependable Autonomic and Secure Computing Dasc 2011, 2011 Automatic text summarization is a data reduction process to exclude unnecessary details and present important information in a shorter version. One way to summarize document is by extracting important sentences in the document. To select suitable sentences, a numerical rank is assigned to each sentence based on a sentence scoring approach. Highly ranked sentences are used for the summary. This paper proposed an automatic text summarization approach based on sentence extraction using fuzzy logic, genetic algorithm, semantic role labeling and their combinations to generate high quality summaries. This study explored the benefits of the genetic algorithm in the optimization problem in for feature selection during the training phase and adjusts feature weights during the testing phase. Fuzzy IF-THEN rules were used to balance the weights between important and unimportant features. Conventional extraction methods cannot capture semantic relations between concepts in a text. Therefore, this research investigates the use of the semantic role labeling to capture the semantic contents in sentences and incorporate it into the summarization method. This paper is evaluated in terms of performance using ROUGE toolkit. Experimental results showed that the summaries produced by the proposed approaches are better than other approaches produced by Microsoft Word 2007, Copernic Summarizer, and MANYASPECTS summarizers.
Conceptual similarity and graph-based method for plagiarism detection Journal of Theoretical and Applied Information Technology, 2011
Pseudo genetic and probabilistic-based feature selection method for extractive single document summarization Journal of Theoretical and Applied Information Technology, 2011
The development of cross-language plagiarism detection tool utilising fuzzy swarm-based summarisation Salha Alzahrani, Naomie Salim, Chow Kok Kent, Mohammed Salem Binwahlan, Ladda Suanmali Proceedings of the 2010 10th International Conference on Intelligent Systems Design and Applications Isda 10, 2010 This work presents the design and development of a web-based system that supports cross-language similarity analysis and plagiarism detection. A suspicious document dq in a language Lq is to be submitted to the system via a PHP web-based interface. The system will accept the text through either uploading or pasting it directly to a text-area. In order to lighten large texts and provide an ideal set of queries, we introduce the idea of query document reduction via summarisation. Our proposed system utilised a fuzzy swarm-based summarisation tool originally built in Java. Then, the summary is used as a query to find similar web resources in languages Lx other than Lq via a dictionary-based translation. Thereafter, a detailed similarity analysis across the languages Lq and Lx is performed and friendly report of results is produced. Such report has global similarity score on the whole document, which assures high flexibility of utilisation.
Swarm diversity based text summarization Mohammed Salem Binwahlan, Naomie Salim, Ladda Suanmali Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2009
Swarm Based Text Summarization Mohammed Salem Binwahlan, Naomie Salim, Ladda Suanmali 2009 International Association of Computer Science and Information Technology Spring Conference Iacsit Sc 2009, 2009
Polynomial Networks Model for Arabic Text Summarization MS Binwahlan International Journal of Research and Scientific Innovation 10 (2), 74-84 , 2023 2023
Event-Based Rumor Detection using LSTM Models For Arabic Content on Twitter A AlAttas, HA Mogaibel, MS BinWahlan 2022 International Conference on Intelligent Technology, System and Service … , 2022 2022 Citations: 3
Statistical Features and PageRank Scoring Fusion for Arabic Text Summarization OS Bahakam, MSF Binwahlan, HA Mogaibel 2022 International Conference on Intelligent Technology, System and Service … , 2022 2022 Citations: 3
Differential evolution cluster-based text summarization methods A Abuobieda, N Salim, MS Binwahlan, AH Osman Computing, Electrical and Electronics Engineering (ICCEEE), 2013 … , 2013 2013 Citations: 21
An improved plagiarism detection scheme based on semantic role labeling AH Osman, N Salim, MS Binwahlan, R Alteeb, A Abuobieda Applied Soft Computing 12 (5), 1493-1502 , 2012 2012 Citations: 128
Plagiarism detection scheme based on Semantic Role Labeling AH Osman, N Salim, MS Binwahlan, S Twaha, YJ Kumar, A Abuobieda Information Retrieval & Knowledge Management (CAMP), 2012 International … , 2012 2012 Citations: 27
Fuzzy genetic semantic based text summarization L Suanmali, N Salim, MS Binwahlan Dependable, Autonomic and Secure Computing (DASC), 2011 IEEE Ninth … , 2011 2011 Citations: 49
Conceptual similarity and graph-based method for plagiarism detection N Salim, MS Binwahlan, H Hentably, AM Ali Journal of Theoretical and Applied Information Technology 32 (2), 135-145 , 2011 2011 Citations: 27
Genetic algorithm based sentence extraction for text summarization L Suanmali, N Salim, MS Binwahlan International Journal of Innovative Computing 1 (1) , 2011 2011 Citations: 25
FUZZY SWARM DIVERSITY BASED TEXT SUMMARIZATION MSF BINWAHLAN Universiti Teknologi Malaysia , 2011 2011 Citations: 3
The development of cross-language plagiarism detection tool utilising fuzzy swarm-based summarisation S Alzahrani, N Salim, CK Kent, MS Binwahlan, L Suanmali 2010 10th International Conference on Intelligent Systems Design and … , 2010 2010 Citations: 7
Fuzzy swarm diversity hybrid model for text summarization MS Binwahlan, N Salim, L Suanmali Information processing & management 46 (5), 571-588 , 2010 2010 Citations: 94
Plagiarism detection using graph-based representation AH Osman, N Salim, MS Binwahlan arXiv preprint arXiv:1004.4449 , 2010 2010 Citations: 24
A hybrid approach based on semantic role labeling and general statistic method for test summarization L Suanmali, N Salim, MS Binwahlan Applied Sciences 10 (3), 166-173 , 2010 2010 Citations: 29
Swarm diversity based text summarization MS Binwahlan, N Salim, L Suanmali International Conference on Neural Information Processing, 216-225 , 2009 2009 Citations: 10
Sentence features fusion for text summarization using fuzzy logic L Suanmali, MS Binwahlan, N Salim Hybrid Intelligent Systems, 2009. HIS'09. Ninth International Conference on … , 2009 2009 Citations: 102
Fuzzy logic based method for improving text summarization L Suanmali, N Salim, MS Binwahlan arXiv preprint arXiv:0906.4690 , 2009 2009 Citations: 156
Integrating of the diversity and swarm based methods for text summarization MS Binwahlan, N Salim, L Suanmali The 5th postgraduate annual research seminar (PARS), 17-19 , 2009 2009 Citations: 5
Feature-Based Sentence Extraction Using Fuzzy Inference rules L Suanmali, N Salim, MS Binwahlan 2009 International Conference on Signal Processing Systems, 511-515 , 2009 2009 Citations: 43
Fuzzy Swarm Based Text Summarization 1 MS Binwahlan, N Salim, L Suanmali 2009 Citations: 42
MOST CITED SCHOLAR PUBLICATIONS
Fuzzy logic based method for improving text summarization L Suanmali, N Salim, MS Binwahlan arXiv preprint arXiv:0906.4690 , 2009 2009.0 Citations: 156
An improved plagiarism detection scheme based on semantic role labeling AH Osman, N Salim, MS Binwahlan, R Alteeb, A Abuobieda Applied Soft Computing 12 (5), 1493-1502 , 2012 2012.0 Citations: 128
Sentence features fusion for text summarization using fuzzy logic L Suanmali, MS Binwahlan, N Salim Hybrid Intelligent Systems, 2009. HIS'09. Ninth International Conference on … , 2009 2009.0 Citations: 102
Fuzzy swarm diversity hybrid model for text summarization MS Binwahlan, N Salim, L Suanmali Information processing & management 46 (5), 571-588 , 2010 2010.0 Citations: 94
Swarm based text summarization MS Binwahlan, N Salim, L Suanmali Computer Science and Information Technology-Spring Conference, 2009 … , 2009 2009.0 Citations: 79
Fuzzy genetic semantic based text summarization L Suanmali, N Salim, MS Binwahlan Dependable, Autonomic and Secure Computing (DASC), 2011 IEEE Ninth … , 2011 2011.0 Citations: 49
Swarm based features selection for text summarization MS Binwahlan, N Salim, L Suanmali IJCSNS International Journal of Computer Science and Network Security 9 (1 … , 2009 2009.0 Citations: 47
Feature-Based Sentence Extraction Using Fuzzy Inference rules L Suanmali, N Salim, MS Binwahlan 2009 International Conference on Signal Processing Systems, 511-515 , 2009 2009.0 Citations: 43
Fuzzy Swarm Based Text Summarization 1 MS Binwahlan, N Salim, L Suanmali 2009.0 Citations: 42
Automatic text summarization using feature-based fuzzy extraction L Suanrnali, N Salim, MS Binwahlan 2008.0 Citations: 31
A hybrid approach based on semantic role labeling and general statistic method for test summarization L Suanmali, N Salim, MS Binwahlan Applied Sciences 10 (3), 166-173 , 2010 2010.0 Citations: 29
Plagiarism detection scheme based on Semantic Role Labeling AH Osman, N Salim, MS Binwahlan, S Twaha, YJ Kumar, A Abuobieda Information Retrieval & Knowledge Management (CAMP), 2012 International … , 2012 2012.0 Citations: 27
Conceptual similarity and graph-based method for plagiarism detection N Salim, MS Binwahlan, H Hentably, AM Ali Journal of Theoretical and Applied Information Technology 32 (2), 135-145 , 2011 2011.0 Citations: 27
Genetic algorithm based sentence extraction for text summarization L Suanmali, N Salim, MS Binwahlan International Journal of Innovative Computing 1 (1) , 2011 2011.0 Citations: 25
Plagiarism detection using graph-based representation AH Osman, N Salim, MS Binwahlan arXiv preprint arXiv:1004.4449 , 2010 2010.0 Citations: 24
Differential evolution cluster-based text summarization methods A Abuobieda, N Salim, MS Binwahlan, AH Osman Computing, Electrical and Electronics Engineering (ICCEEE), 2013 … , 2013 2013.0 Citations: 21
MMI diversity based text summarization MS Binwahlan, N Salim, L Suanmali International Journal of Computer Science and Security 3 (1), 23-33 , 2009 2009.0 Citations: 14
Swarm diversity based text summarization MS Binwahlan, N Salim, L Suanmali International Conference on Neural Information Processing, 216-225 , 2009 2009.0 Citations: 10
Extractive Summarization Method for Arabic Text-ESMAT MS Binwahlan Citations: 9
The development of cross-language plagiarism detection tool utilising fuzzy swarm-based summarisation S Alzahrani, N Salim, CK Kent, MS Binwahlan, L Suanmali 2010 10th International Conference on Intelligent Systems Design and … , 2010 2010.0 Citations: 7
Publications
Total of Impact Factor: 5.384
Fully Refereed Articles: 15
Conferences Articles: 13
Book Chapters: 2
Total of Publication: 30
GRANT DETAILS
UTM Cross Language Plagiarism Detection System, Copyright Agent: RMC-UTM
RESEARCH OUTPUTS (PATENTS, SOFTWARE, PUBLICATIONS, PRODUCTS)
Patent holder:
Diversified and Importance Centralized Text Summarization, Patent No. PI2011001276, Patent Agent: Pintas IP, 2011.
Fuzzy Swarm-based Model for Text Summarization, Patent No. PI2011001277, Patent Agent: Pintas IP, 2011.
