Natural Language Processing and e-Government: Extracting Reusable Crime Report Information

Iriberri, Alicia; Leroy, Gondy

doi:10.1109/iri.2007.4296624

Cited by 17 publications

(13 citation statements)

References 13 publications

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“…An Online Crime Reporting System was developed in ref. [104] to extract relevant crime information from witness narratives and also to generate additional questions based on the extracted information. The proposed system combined natural language processing and an investigative interviewing technique (based on the cognitive interview principles) with the adoption of the General Architecture for Text Engineering System as the information extraction tool.…”

Section: Entity Extractionmentioning

confidence: 99%

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A review of data mining applications in crime

Hassani

Huang

Silva

et al. 2016

Statistical Analysis

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Crime continues to remain a severe threat to all communities and nations across the globe alongside the sophistication in technology and processes that are being exploited to enable highly complex criminal activities. Data mining, the process of uncovering hidden information from Big Data, is now an important tool for investigating, curbing and preventing crime and is exploited by both private and government institutions around the world. The primary aim of this paper is to provide a concise review of the data mining applications in crime. To this end, the paper reviews over 100 applications of data mining in crime, covering a substantial quantity of research to date, presented in chronological order with an overview table of many important data mining applications in the crime domain as a reference directory. The data mining techniques themselves are briefly introduced to the reader and these include entity extraction, clustering, association rule mining, decision trees, support vector machines, naive Bayes rule, neural networks and social network analysis amongst others

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Section: Entity Extractionmentioning

confidence: 99%

“…Density Density is defined as the number of edges in a portion of a social network to the maximum number of edges that theoretically make up the social network [104]. Assume C is the number of observed edges and n is the total number of nodes in the social network, then the formula of density is, Density = C n(n−1)/2 .…”

Section: Degreementioning

confidence: 99%

A review of data mining applications in crime

Hassani

Huang

Silva

et al. 2016

Statistical Analysis

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“…Within the context of e-government, supervised NLP models have been used for developing an online crime report system [19] and for classifying public comments. Iriberri and Leroy (2007) used NLP methods in building an Internet-based crime reporting system by extracting relevant crime information from witness' narratives and by asking additional questions based on the crime information.…”

Section: Statistical Natural Language Processing and Topic Modelingmentioning

confidence: 99%

Understanding Citizens' Direct Policy Suggestions to the Federal Government: A Natural Language Processing and Topic Modeling Approach

Hagen

Uzuner

Kotfila

et al. 2015

2015 48th Hawaii International Conference on System Sciences

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We report on our initial efforts to make sense of epetitions as policy suggestions by using the NLP technique of "topic modeling" to identify the "topics" that emerge in e-petitions. Using a sample of petitions submitted to the Obama Administration's WtP petitioning system as a case study, we produced 30 emergent topics. 21 out of the 30 topics were initially coded as high-quality topics. Upon qualitative investigation, all but one of these 21 topics were determined to have a coherent theme. Our results imply that topic modeling has the potential to enable the interpretation of large quantities of citizen generated policy suggestions through a largely automated process, with potential application to research on e-participation and policy informatics.

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“…In today's technologically advanced society, mechanisms for fighting crime are extremely advanced, from remote, automatic surveillance to sophisticated dedicated laboratories and evidence analysis, yet crime still has a significant presence in our world, both globally and in local communities, including sexual assault, drugs and violent crimes, all of which endanger the public. While some people may be willing to actively report illegal acts, others choose not to do so, as they are worried about the fallibility of the policing, reporting and criminal justice systems, based on previous failings in all three departments [1][2][3]. People are afraid for their own safety should those they report identify them, or they are worried that law enforcement officials may simply erase any case they report.…”

Section: Introductionmentioning

confidence: 99%

A Cloud-Based Crime Reporting System with Identity Protection

Shih

Syu

et al. 2019

Symmetry

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Criminal activities have always been a part of human society, and even today, in a world of extremely advanced surveillance and policing capabilities, many different kinds of crimes are still committed in almost every social environment. However, since those who commit crimes are not representative of the majority of their community, members of these communities tend to wish to report crime when they see it; however, they are often reluctant to do so for fear of their own safety should the people they report identify them. Thus, a great deal of crime goes unreported, and investigations fail to gain key evidence from witnesses, which serves only to foster an environment in which criminal activity is more likely to occur. In order to address this problem, this paper proposes an online illegal event reporting scheme based on cloud technology, which combines digital certificates, symmetric keys, asymmetric keys, and digital signatures. The proposed scheme can process illegal activity reports from the reporting event to the issuing of a reward. The scheme not only ensures informers’ safety, anonymity and non-repudiation, but also prevents cases and reports being erased, and ensures data integrity. Furthermore, the proposed scheme is designed to be robust against abusive use, and is able to preclude false reports. Therefore, it provides a convenient and secure platform for reporting and fighting crime.

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Natural Language Processing and e-Government: Extracting Reusable Crime Report Information

Abstract: Crime reporting needs to be possible

Cited by 17 publications

References 13 publications

A review of data mining applications in crime

A review of data mining applications in crime

Understanding Citizens' Direct Policy Suggestions to the Federal Government: A Natural Language Processing and Topic Modeling Approach

A Cloud-Based Crime Reporting System with Identity Protection

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