A Preliminary Investigation of a Semi-Automatic Criminology Intelligence Extraction Method: A Big Data Approach

M. Trovati, P. Hodgson, C. Hargreaves
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Abstract

The aim of any science is to advance the state-of-the-art knowledge via a rigorous investigation and analysis of empirical observations, as well as the development of new theoretical frameworks. Data acquisition and ultimately the extraction of novel knowledge, is therefore the foundation of any scientific advance. However, with the increasing creation of data in various forms and shapes, identifying relevant information from structured and unstructured data sets raises several challenges, as well as opportunities. In this paper, we discuss a semi-automatic method to identify, analyse and generate knowledge specifically focusing on Criminology. The main motivation is to provide a toolbox to help criminology experts, which would potentially lead to a better understanding and prediction of the properties to facilitate the decision making process. Our initial validation shows the potential of our method providing relevant and accurate results.
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基于大数据的半自动犯罪学情报提取方法初探
任何科学的目标都是通过严格的调查和实证观察的分析,以及新的理论框架的发展来推进最先进的知识。因此,数据的获取以及最终的新知识的提取是任何科学进步的基础。然而,随着各种形式和形状的数据的不断增加,从结构化和非结构化数据集中识别相关信息提出了一些挑战,同时也带来了机遇。在本文中,我们讨论了一种半自动的方法来识别,分析和产生知识,特别是专注于犯罪学。主要的动机是提供一个工具箱来帮助犯罪学专家,这可能会导致更好地理解和预测属性,以促进决策过程。我们的初步验证显示了我们的方法提供相关和准确结果的潜力。
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