LEADER 01484nas# 22003011i 450 001 UON00089841 005 20231205102504.967 100 $a20020107a1979 |0itac50 ba 101 $aita 102 $aIT 105 $a|||| ||||| 110 $aaA||||||||| 200 1 $aQuaderni dell'Istituto di Lingua e Letteratura Latina$fUniversità degli Studi di Roma, Facoltà di Magistero 205 $a1(1979)- 207 $aRoma : Edizioni dell'Ateneo & Bizzarri, 1979- 210 $a v.$a24 cm 215 $aAnnuale 606 $aLINGUE CLASSICHE$xSTUDI ETIMOLOGICI E GRAMMATICALI$3UONC027018$2FI 620 $aIT$dRoma$3UONL000004 676 $a7-41$cLINGUISTICA GENERALE$v21 712 02$aUniversità degli Studi$cRoma$3UONV001565 712 $aEdizioni dell'Ateneo & Bizzarri$3UONV260948$4650 801 $aIT$bSOL$c20240220$gRICA 899 $aSIBA - SISTEMA BIBLIOTECARIO DI ATENEO$2UONSI$41(1979)-4(1982).$cPER Q 0250 ; 912 $aUON00089841 950 $aSIBA - SISTEMA BIBLIOTECARIO DI ATENEO$bSI 1(1979)-4(1982).$dSI PER Q 0250 01 1979 $eSI MC 4089 7 1979 $dSI PER Q 0250 02-03 1980-1981 $eSI MC 7639 7 1980-1981 $dSI PER Q 0250 04 1982 $eSI MC 9451 7 1982 996 $aQuaderni dell'Istituto di Lingua e Letteratura Latina$9893611 997 $aUNIOR LEADER 03974nam 22007095 450 001 9911015852703321 005 20250702130248.0 010 $a3-031-93174-2 024 7 $a10.1007/978-3-031-93174-1 035 $a(MiAaPQ)EBC32189448 035 $a(Au-PeEL)EBL32189448 035 $a(CKB)39567915300041 035 $a(DE-He213)978-3-031-93174-1 035 $a(OCoLC)1527809868 035 $a(EXLCZ)9939567915300041 100 $a20250702d2025 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMachine Learning Techniques to Predict Terrorist Attacks $eExemplified by Jama'at Nasr al-Islam wal Muslimin /$fby Laura Mostert, Roy Lindelauf, Chiara Pulice, Marnix Provoost, Priyanka Amin, V.S. Subrahmanian 205 $a1st ed. 2025. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2025. 215 $a1 online resource (157 pages) 225 1 $aTerrorism, Security, and Computation,$x2197-8786 311 08$a3-031-93173-4 327 $aChapter 1 Introduction -- Chapter 2 Jama'at Nasr al-Islam wal Muslimin (JNIM) -- Chapter 3 Temporal Probabilistic Rules and Policy Computation Algorithms -- Chapter 4 Abduction and Release of Abductees -- Chapter 5 Attacks on and Targeting of Public Sites -- Chapter 6 Targeting of Security Professionals and Security Installations -- Chapter 7 Targeting of Civilians -- Chapter 8 Other types of attacks -- Chapter 9 Reflections & Implications for military decision making. 330 $aOne of the most influential actors in spreading Islamist violence across the Sahel is Jama?at Nasr Al Islam Wal Muslimin (JNIM).This book provides the first systematic quantitative analysis of JNIM?s behavior by analyzing a 12-year database of JNIM?s attacks and the environment surrounding JNIM. This book leverages AI/ML predictive models to accurately predict almost 40 types of attacks using over 80 independent variables. This book describes a set of temporal probabilistic rules that state that when the environment in which the group operates satisfies some conditions, then an attack of a certain type will likely occur in the next N months. This provides a deep, easy to comprehend understanding of the conditions under which JNIM carries various kinds of attacks up to 6 months into the future. This book will serve as an invaluable guide to scholars (computer scientists, political scientists, policy makers). Military officers, intelligence personnel, and government employees, who seek to understand, predict, and eventually mitigate attacks by JNIM and bring peace to the nations of Mali, Burkina Faso, and Niger will want to purchase this book as well. 410 0$aTerrorism, Security, and Computation,$x2197-8786 606 $aMachine learning 606 $aArtificial intelligence 606 $aPolitics and war 606 $aTerrorism 606 $aPolitical violence 606 $aMachine Learning 606 $aArtificial Intelligence 606 $aMilitary and Defence Studies 606 $aTerrorism and Political Violence 615 0$aMachine learning. 615 0$aArtificial intelligence. 615 0$aPolitics and war. 615 0$aTerrorism. 615 0$aPolitical violence. 615 14$aMachine Learning. 615 24$aArtificial Intelligence. 615 24$aMilitary and Defence Studies. 615 24$aTerrorism and Political Violence. 676 $a006.31 700 $aMostert$b Laura$01833062 701 $aLindelauf$b Roy$01833063 701 $aPulice$b Chiara$01833064 701 $aProvoost$b Marnix$01833065 701 $aAmin$b Priyanka$01833066 701 $aSubrahmanian$b V. S$0542368 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911015852703321 996 $aMachine Learning Techniques to Predict Terrorist Attacks$94407893 997 $aUNINA