Intelligent data analytics for terror threat prediction: architectures, methodologies, techniques and applications
"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....
Gespeichert in:
| Weitere beteiligte Personen: | , , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Hoboken, NJ
John Wiley & Sons, Inc.
2021
|
| Schlagwörter: | |
| Links: | https://learning.oreilly.com/library/view/-/9781119711094/?ar |
| Zusammenfassung: | "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"-- |
| Beschreibung: | Includes bibliographical references and index. - Description based on online resource; title from digital title page (viewed on July 08, 2021) |
| Umfang: | 1 Online-Ressource |
| ISBN: | 9781119711629 1119711622 1119711517 9781119711612 1119711614 9781119711513 9781119711094 |
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| 245 | 0 | 0 | |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, and Xiaobo Zhang |
| 264 | 1 | |a Hoboken, NJ |b John Wiley & Sons, Inc. |c 2021 | |
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| 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"-- | ||
| 650 | 0 | |a Terrorism |x Prevention | |
| 650 | 0 | |a Computer networks | |
| 650 | 0 | |a Data mining | |
| 650 | 2 | |a Computer Communication Networks | |
| 650 | 2 | |a Data Mining | |
| 650 | 4 | |a Terrorisme ; Prévention | |
| 650 | 4 | |a Réseaux d'ordinateurs | |
| 650 | 4 | |a Exploration de données (Informatique) | |
| 650 | 4 | |a Computer networks | |
| 650 | 4 | |a Data mining | |
| 650 | 4 | |a Terrorism ; Prevention | |
| 700 | 1 | |a Pani, Subhendu Kumar |d 1980- |e HerausgeberIn |4 edt | |
| 700 | 1 | |a Singh, Sanjay Kumar |d 1963- |e HerausgeberIn |4 edt | |
| 700 | 1 | |a Garg, Lalit |d 1977- |e HerausgeberIn |4 edt | |
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| spelling | Intelligent data analytics for terror threat prediction architectures, methodologies, techniques and applications edited by Subhendu Kumar Pani, Sanjay Kumar Singh, Lalit Garg, Ram Bilas Pachori, and Xiaobo Zhang Hoboken, NJ John Wiley & Sons, Inc. 2021 ©2021 1 Online-Ressource Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Includes bibliographical references and index. - Description based on online resource; title from digital title page (viewed on July 08, 2021) "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"-- Terrorism Prevention Computer networks Data mining Computer Communication Networks Data Mining Terrorisme ; Prévention Réseaux d'ordinateurs Exploration de données (Informatique) Terrorism ; Prevention Pani, Subhendu Kumar 1980- HerausgeberIn edt Singh, Sanjay Kumar 1963- HerausgeberIn edt Garg, Lalit 1977- HerausgeberIn edt 9781119711094 Erscheint auch als Druck-Ausgabe 9781119711094 |
| spellingShingle | Intelligent data analytics for terror threat prediction architectures, methodologies, techniques and applications Terrorism Prevention Computer networks Data mining Computer Communication Networks Data Mining Terrorisme ; Prévention Réseaux d'ordinateurs Exploration de données (Informatique) Terrorism ; Prevention |
| title | Intelligent data analytics for terror threat prediction architectures, methodologies, techniques and applications |
| title_auth | Intelligent data analytics for terror threat prediction architectures, methodologies, techniques and applications |
| title_exact_search | Intelligent data analytics for terror threat prediction architectures, methodologies, techniques and applications |
| title_full | Intelligent data analytics for terror threat prediction architectures, methodologies, techniques and applications edited by Subhendu Kumar Pani, Sanjay Kumar Singh, Lalit Garg, Ram Bilas Pachori, and Xiaobo Zhang |
| title_fullStr | Intelligent data analytics for terror threat prediction architectures, methodologies, techniques and applications edited by Subhendu Kumar Pani, Sanjay Kumar Singh, Lalit Garg, Ram Bilas Pachori, and Xiaobo Zhang |
| title_full_unstemmed | Intelligent data analytics for terror threat prediction architectures, methodologies, techniques and applications edited by Subhendu Kumar Pani, Sanjay Kumar Singh, Lalit Garg, Ram Bilas Pachori, and Xiaobo Zhang |
| title_short | Intelligent data analytics for terror threat prediction |
| title_sort | intelligent data analytics for terror threat prediction architectures methodologies techniques and applications |
| title_sub | architectures, methodologies, techniques and applications |
| topic | Terrorism Prevention Computer networks Data mining Computer Communication Networks Data Mining Terrorisme ; Prévention Réseaux d'ordinateurs Exploration de données (Informatique) Terrorism ; Prevention |
| topic_facet | Terrorism Prevention Computer networks Data mining Computer Communication Networks Data Mining Terrorisme ; Prévention Réseaux d'ordinateurs Exploration de données (Informatique) Terrorism ; Prevention |
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