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03432aam a22004098i 4500 001 0A4E307C177D11EC850ADFAD22ECA4DB 003 SILO 005 20210917010313 008 210106s2021 njua b 001 0 eng 010 $a 2021000196 020 $a 1119711096 020 $a 9781119711094 035 $a (OCoLC)1230251451 040 $a DLC $b eng $e rda $c DLC $d OCLCO $d BDX $d OCLCF $d UKMGB $d GSU $d OCLCO $d SILO 042 $a pcc 050 00 $a HV6431 $b .I4878 2021 245 00 $a Intelligent data analytics for terror threat prediction : $b architectures, methodologies, techniques and applications / $c edited by Subhendu Kumar Pani, Sanjay Kumar Singh, Lalit Garg, Ram Bilas Pachori, Xiaobo Zhang. 263 $a 2104 264 1 $a Hoboken, NJ : $b John Wiley & Sons ; $c 2021. 300 $a xix, 319 pages : $b illustrations ; $c 24 cm 504 $a Includes bibliographical references and index. 520 $a "Intelligent data analytics for terror threat prediction is an emerging field of research at the intersection of information science and computer science, bringing with it a new era of tremendous opportunities and challenges due to plenty of easily available criminal data for further analysis. The aim of data analytics is to prevent threats before they happen using classical statistical issues, machine learning, artificial intelligence, rule induction methods, neural networks, fuzzy logic, and stochastic search methods on various data sources, including social media, GPS devices, video feed from street cameras; and license plate readers, travel and credit card records and the news media, as well as government and proprietary systems. Intelligent data analytics ensures efficient data mining techniques to solve criminal investigations. Prediction of future terrorist attacks according to city, type of attack, target and weapon, claim mode, and motive for attack through classification techniques will facilitate the decision-making process of security organizations so as to learn from previously stored attack information; and then rate the targeted sectors/areas accordingly for security measures. By using intelligent data analytics models with multiple levels of representation, raw to higher abstract level representation can be learned at each level of the system. Algorithms based on intelligent data analytics have demonstrated great performance in a variety of areas, including data visualization, data pre-processing (fusion, editing, transformation, filtering, and sampling), data engineering, database mining techniques, tools and applications, etc"-- $c Provided by publisher. 650 0 $a Terrorism $x Prevention. 650 0 $a Computer networks. 650 0 $a Data mining. 650 7 $a Computer networks. $2 fast $0 (OCoLC)fst00872297 650 7 $a Data mining. $2 fast $0 (OCoLC)fst00887946 650 7 $a Terrorism $x Prevention. $2 fast $0 (OCoLC)fst01148123 700 1 $a Pani, Subhendu Kumar, $d 1980- $e editor. 700 1 $a Singh, Sanjay Kumar, $d 1963- $e editor. 700 1 $a Garg, Lalit, $d 1977- $e editor. 700 1 $a Pachori, Ram Bilas, $d 1979- $e editor. 700 1 $a Zhang, Xiaobo, $c Dr., $e editor. 776 08 $i Online version: $t Intelligent data analytics for terror threat prediction $b First edition. $d Hoboken : Wiley, 2021. $z 9781119711612 $w (DLC) 2021000197 941 $a 1 952 $l OVUX522 $d 20220526013756.0 956 $a http://locator.silo.lib.ia.us/search.cgi?index_0=id&term_0=0A4E307C177D11EC850ADFAD22ECA4DBInitiate Another SILO Locator Search