Text Mining and Knowledge Discovery from Big Data: Challenges and Promise
With the fast development of networking, data storage, and the data collection capacity, Big Data is now rapidly expanding in all science and engineering domains, including physical, biological and biomedical sciences. This paper presents text mining and the ways used to categorize document structure techniques in big data. This subject poses a big challenge when it comes to guaranteeing the quality of extracted features in text documents to describe user interests or preferences due to large amounts of noise. This subject has many models and algorithms but still needs more to achieve best results for users, making this an open issue that needs more research.
Keywords: Text mining - Big Data - Knowledge Discovery
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ABOUT THE AUTHORS
Amal Mahmoud Yehia
a PhD student in Department of Computer Science and Information Institute of Statistical Studies and Research Cairo University, Cairo, Egypt.
Lamiaa Fattouh Ibrahim
a Professor in the Faculty of Computing and Information Technology at King Abdulaziz University in Jeddah and in the Institute of Statistical Studies and Research at Cairo University. She obtained a PhD from the Faculty of Engineering, Cairo University in 1999, Master’s degree from the Computer and Systems Engineering Department in the Faculty of Engineering, Ain Shams University in 1993, Master’s degree from the Ecole National Superieur de Telecommunication, ENST Paris in 1987, and a BSc from the Computer and Automatic Control Department, Faculty of Engineering, Ain Shams University in 1984. She has over 32 years of experience in the fields of network engineering and artificial intelligence, focusing on applying knowledge base and data mining techniques in wired and wireless network planning. She has published papers in many journals and international conferences in the areas of networks, data mining, and wired and mobile network planning
Maysoon Fouad Abulkhair
an Assistant Professor and Supervisor of IT department at King Abdulaziz University, Jeddah, KSA. She is a member of ACM. Her main interest in the research field is HCI, associating it with different knowledge areas such as artificial intelligent, machine learning, and data mining.
Amal Mahmoud Yehia
a PhD student in Department of Computer Science and Information Institute of Statistical Studies and Research Cairo University, Cairo, Egypt.
Lamiaa Fattouh Ibrahim
a Professor in the Faculty of Computing and Information Technology at King Abdulaziz University in Jeddah and in the Institute of Statistical Studies and Research at Cairo University. She obtained a PhD from the Faculty of Engineering, Cairo University in 1999, Master’s degree from the Computer and Systems Engineering Department in the Faculty of Engineering, Ain Shams University in 1993, Master’s degree from the Ecole National Superieur de Telecommunication, ENST Paris in 1987, and a BSc from the Computer and Automatic Control Department, Faculty of Engineering, Ain Shams University in 1984. She has over 32 years of experience in the fields of network engineering and artificial intelligence, focusing on applying knowledge base and data mining techniques in wired and wireless network planning. She has published papers in many journals and international conferences in the areas of networks, data mining, and wired and mobile network planning
Maysoon Fouad Abulkhair
an Assistant Professor and Supervisor of IT department at King Abdulaziz University, Jeddah, KSA. She is a member of ACM. Her main interest in the research field is HCI, associating it with different knowledge areas such as artificial intelligent, machine learning, and data mining.
