000			04051cam a2200589M 4500
001			ocn969013612
003			OCoLC
005			20190328114816.0
006			m o d
007			cr |||||||||||
007			tz
008			160906s2016 xx o 000 0 eng d
040			_aFEM _beng _cFEM _dOCLCQ _dYDX _dOPELS _dTEFOD _dIDEBK _dOCLCF _dQCL _dUPM _dN$T _dGZM _dOCLCQ _dB@L _dD6H _dU3W
019			_a959273666 _a959329997 _a968010833
020			_a9780128045459 _q(electronic bk.)
020			_a0128045450
020			_z9780128045350
020			_z0128045353
035			_a(OCoLC)969013612 _z(OCoLC)959273666 _z(OCoLC)959329997 _z(OCoLC)968010833
050		4	_aLB1028.43 _b.M54 2017
072		7	_aEDU _x042000 _2bisacsh
072		7	_aEDU _x036000 _2bisacsh
072		7	_aEDU _x024000 _2bisacsh
082	0	4	_a370.72/7 _223
100	1		_aMiguel, Jorge, _eauthor.
245	1	0	_aIntelligent data analysis for e-learning / _h[electronic resource]
264		1	_a[Place of publication not identified] : _bElsevier Science, _c2016.
300			_a1 online resource
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _2rda
490	1		_aIntelligent data centric systems
520			_aIntelligent Data Analysis for e-Learning: Enhancing Security and Trustworthiness in Online Learning Systems addresses information security within e-Learning based on trustworthiness assessment and prediction. Over the past decade, many learning management systems have appeared in the education market. Security in these systems is essential for protecting against unfair and dishonest conduct--most notably cheating--however, e-Learning services are often designed and implemented without considering security requirements. This book provides functional approaches of trustworthiness analysis, modeling, assessment, and prediction for stronger security and support in online learning, highlighting the security deficiencies found in most online collaborative learning systems. The book explores trustworthiness methodologies based on collective intelligence than can overcome these deficiencies. It examines trustworthiness analysis that utilizes the large amounts of data-learning activities generate. In addition, as processing this data is costly, the book offers a parallel processing paradigm that can support learning activities in real-time. The book discusses data visualization methods for managing e-Learning, providing the tools needed to analyze the data collected. Using a case-based approach, the book concludes with models and methodologies for evaluating and validating security in e-Learning systems. Provides guidelines for anomaly detection, security analysis, and trustworthiness of data processing Incorporates state-of-the-art, multidisciplinary research on online collaborative learning, social networks, information security, learning management systems, and trustworthiness prediction Proposes a parallel processing approach that decreases the cost of expensive data processing Offers strategies for ensuring against unfair and dishonest assessments Demonstrates solutions using a real-life e-Learning context.
588	0		_aVendor-supplied metadata.
504			_aIncludes bibliographical references and index.
650		0	_aEducational statistics _xData processing.
650		7	_aEducational statistics _xData processing. _2fast _0(OCoLC)fst00903607
650		7	_aEDUCATION / Essays _2bisacsh
650		7	_aEDUCATION / Organizations & Institutions _2bisacsh
650		7	_aEDUCATION / Reference _2bisacsh
650		4	_aComputer Technology.
650		4	_aNonfiction.
655		4	_aSecurity.
700	1		_aSanti Caball�e _eauthor.
700	1		_aFatos Xhafa, _eauthor.
710	1		_aTotalBoox, _edistributor.
710	1		_aTBX, _edistributor.
776	0	8	_iPrint version: _z9780128045350 _z0128045353
830		0	_aIntelligent data centric systems.
856	4	0	_3ScienceDirect _uhttp://www.sciencedirect.com/science/book/9780128045350
999			_c247430 _d247430