Text Mining and Recommender Systems for Predictive Policing

被引：1

作者：

Percy, Isabelle ^{[1
]}

Balinsky, Alexander ^{[1
]}

Balinsky, Helen ^{[2
]}

Simske, Steve ^{[3
]}

机构：

[1] Cardiff Univ, Cardiff Sch Math, Cardiff, S Glam, Wales

[2] Hewlett Packard Labs, Bristol, Avon, England

[3] Colorado State Univ, Dept Mech Engn, Ft Collins, CO 80523 USA

来源：

PROCEEDINGS OF THE ACM SYMPOSIUM ON DOCUMENT ENGINEERING (DOCENG 2018) | 2018年

基金：

英国工程与自然科学研究理事会;

关键词：

Measure of similarity; TF-IDF; clustering; affinity propagation; silhouette score;

D O I：

10.1145/3209280.3229112

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

We present some results from a joint project between HP Labs, Cardiff University and Dyfed Powys Police on predictive policing. Applications of the various techniques from recommender systems and text mining to the problem of crime patterns recognition are demonstrated. Our main idea is to consider crime records for different regions and time period as a corpus of text documents with words being crime types. We apply tools from NLP and text documents classifications to analyse different regions in time and space. We evaluate performance of several measures of similarity for texts and documents clustering algorithms.

引用

页数：4

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