找回密碼
 To register

QQ登錄

只需一步,快速開始

掃一掃,訪問微社區(qū)

打印 上一主題 下一主題

Titlebook: Counterterrorism and Open Source Intelligence; Uffe Kock Wiil Book 2011 Springer-Verlag/Wien 2011 Counterterrorism.Data Mining.Open Source

[復(fù)制鏈接]
樓主: Grant
21#
發(fā)表于 2025-3-25 03:24:20 | 只看該作者
22#
發(fā)表于 2025-3-25 07:52:21 | 只看該作者
Deduktion und Umkehrung des Idealismusse learners. Then we have applied boosting algorithm with suitable weak learners and parameter settings such as the number of boosting iterations. We propose a Naive Bayes classifier as a suitable weak learner for the boosting algorithm. It achieves maximum performance with very few boosting iterations.
23#
發(fā)表于 2025-3-25 13:21:43 | 只看該作者
Die historische Dimension der Dialektikoutperforms the existing classification models for the task of suspicious email detection and topic categorization on the Reuters-21578 and 20 Newsgroups datasets. Our model also outperforms A Decision Cluster Classification (ADCC) and the Decision Cluster Forest Classification (DCFC) models on the Reuters-21578 dataset.
24#
發(fā)表于 2025-3-25 18:45:42 | 只看該作者
Understanding Terrorist Network Topologies and Their Resilience Against Disruptiony the resilience properties of secrecy versus information balanced networks. This provides an explanation of the survival of global terrorist networks and food for thought on counterterrorism strategy policy.
25#
發(fā)表于 2025-3-25 20:55:51 | 只看該作者
Co-offending Network Miningny such data set and link the data model to the analysis techniques. We contend that central aspects considered in the work presented here carry over to a wide range of large data sets studied in intelligence and security informatics to better serve law enforcement and intelligence agencies.
26#
發(fā)表于 2025-3-26 03:02:36 | 只看該作者
The Use of Open Source Intelligence in the Construction of Covert Social Networks into the structure of covert social networks from the limited and fragmentary data gathered from intelligence operations or open sources. A protocol for predicting the existence of hidden “key-players” covert in social networks is given.
27#
發(fā)表于 2025-3-26 07:13:44 | 只看該作者
Retracted: A Novel Method to Analyze the Importance of Links in Terrorist Networksa novel method to analyze the importance of links in terrorist networks inspired by research on transportation networks. The12.6pc]The first author has been considered as corresponding author. Please check. link importance measure is implemented in CrimeFighter Assistant and evaluated on known terrorist networks harvested from open sources.
28#
發(fā)表于 2025-3-26 11:01:05 | 只看該作者
29#
發(fā)表于 2025-3-26 14:26:10 | 只看該作者
Cluster Based Text Classification Modeloutperforms the existing classification models for the task of suspicious email detection and topic categorization on the Reuters-21578 and 20 Newsgroups datasets. Our model also outperforms A Decision Cluster Classification (ADCC) and the Decision Cluster Forest Classification (DCFC) models on the Reuters-21578 dataset.
30#
發(fā)表于 2025-3-26 18:36:48 | 只看該作者
 關(guān)于派博傳思  派博傳思旗下網(wǎng)站  友情鏈接
派博傳思介紹 公司地理位置 論文服務(wù)流程 影響因子官網(wǎng) 吾愛論文網(wǎng) 大講堂 北京大學(xué) Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點評 投稿經(jīng)驗總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學(xué) Yale Uni. Stanford Uni.
QQ|Archiver|手機版|小黑屋| 派博傳思國際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-5 03:29
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權(quán)所有 All rights reserved
快速回復(fù) 返回頂部 返回列表
南宫市| 筠连县| 库伦旗| 墨玉县| 河南省| 高尔夫| 舟山市| 隆化县| 孙吴县| 太保市| 临西县| 宿州市| 泊头市| 花莲县| 无极县| 高安市| 正镶白旗| 石泉县| 正蓝旗| 潼南县| 都江堰市| 旌德县| 黔江区| 潮安县| 中西区| 广宗县| 贵南县| 文水县| 新绛县| 隆林| 乌兰县| 麻阳| 山阳县| 桂林市| 筠连县| 大庆市| 报价| 阳原县| 西吉县| 吉安县| 清徐县|