Design and Study on Police Intelligence Analysis System Based on GIS

Author(s):  
Wen-you Fan ◽  
Ye Chen
Author(s):  
Ying Yuan

Abstract Psychological analysis of characters in ordinary novels is mainly a qualitative analysis, which is easily affected by the researchers’ reading level, theoretical literacy, subjective experience, and other factors. With the development of computer technology and big data, stable and systematic personality can more accurately describe the psychology of text characters. This article adopts the method of literary intelligence analysis based on data mining and statistics, through the Chinese psychological analysis system, the language of the characters in the novel of ordinary world can be counted, processed, and disposed, and then obtains the big five personality prediction scores of the characters. Furthermore, the validity of the intelligent analysis method is confirmed by examining the verification of the predictive scores in the text and literature. After verification by many parties, the predicted results of this article are supported by the text and literature, which shows that literary intelligence analysis of novel characters’ personalities is effective.


2011 ◽  
Vol 5 (1) ◽  
pp. 17-30 ◽  
Author(s):  
Tomasz D. Loboda ◽  
Peter Brusilovsky ◽  
Jonathan Grady

2022 ◽  
Vol 2022 ◽  
pp. 1-15
Author(s):  
Yinghai Zhou ◽  
Yi Tang ◽  
Ming Yi ◽  
Chuanyu Xi ◽  
Hai Lu

With the development of advanced persistent threat (APT) and the increasingly severe situation of network security, the strategic defense idea with the concept of “active defense, traceability, and countermeasures” arises at the historic moment, thus cyberspace threat intelligence (CTI) has become increasingly valuable in enhancing the ability to resist cyber threats. Based on the actual demand of defending against the APT threat, we apply natural language processing to process the cyberspace threat intelligence (CTI) and design a new automation system CTI View, which is oriented to text extraction and analysis for the massive unstructured cyberspace threat intelligence (CTI) released by various security vendors. The main work of CTI View is as follows: (1) to deal with heterogeneous CTI, a text extraction framework for threat intelligence is designed based on automated test framework, text recognition technology, and text denoising technology. It effectively solves the problem of poor adaptability when crawlers are used to crawl heterogeneous CTI; (2) using regular expressions combined with blacklist and whitelist mechanism to extract the IOC and TTP information described in CTI effectively; (3) according to the actual requirements, a model based on bidirectional encoder representations from transformers (BERT) is designed to complete the entity extraction algorithm for heterogeneous threat intelligence. In this paper, the GRU layer is added to the existing BERT-BiLSTM-CRF model, and we evaluate the proposed model on the marked dataset and get better performance than the current mainstream entity extraction mode.


2020 ◽  
pp. 136-173
Author(s):  
David Barno ◽  
Nora Bensahel

This chapter explores the role of technological adaptability during the wars in Afghanistan and Iraq. At the tactical level, it examines how soldiers in Iraq developed “hillbilly armor” to try to protect their vulnerable vehicles from roadside bombs, and how Apache helicopters were successfully adapted to conduct close air support missions in Afghanistan. It also argues, however, that technological adaptability at the institutional level involved disastrous failures. In Iraq, virtually all senior Pentagon officials repeatedly resisted providing adequate numbers of life-saving vehicles called MRAPs to deployed soldiers facing grave threats from improvised explosive devices. And in Afghanistan, the army stubbornly supported its poorly performing intelligence analysis system, called DCGS-A, for more than a decade, despite overwhelming evidence that commercially available software from Palantir would work better and save the lives of more soldiers.


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