Automated crime report analysis and classification for e-government and decision support

Authors:
Chih-Hao Ku;Gondy Leroy
Affiliations:
School of Information Technology, Middle Georgia State College;Claremont Graduate University
Venue:
Proceedings of the 14th Annual International Conference on Digital Government Research
Year:
2013

Citing 38
Cited 0

An investigation of linguistic features and clustering algorithms for topical document clustering

SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Document Ranking and the Vector-Space Model

IEEE Software
A Comparative Study of Classification Based Personal E-mail Filtering

PADKK '00 Proceedings of the 4th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Current Issues and New Applications
A machine learning approach to coreference resolution of noun phrases

Computational Linguistics - Special issue on computational anaphora resolution
Evaluating WordNet-based Measures of Lexical Semantic Relatedness

Computational Linguistics
Detection of Duplicate Defect Reports Using Natural Language Processing

ICSE '07 Proceedings of the 29th international conference on Software Engineering
Declarative information extraction using datalog with embedded extraction predicates

VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Natural language processing and e-Government: crime information extraction from heterogeneous data sources

dg.o '08 Proceedings of the 2008 international conference on Digital government research
An approach to detecting duplicate bug reports using natural language and execution information

Proceedings of the 30th international conference on Software engineering
Document similarity based on concept tree distance

Proceedings of the nineteenth ACM conference on Hypertext and hypermedia
Multi-document summarization via sentence-level semantic analysis and symmetric matrix factorization

Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Rule based synonyms for entity extraction from noisy text

Proceedings of the second workshop on Analytics for noisy unstructured text data
Decision trees for hierarchical multi-label classification

Machine Learning
An efficient document classification model using an improved back propagation neural network and singular value decomposition

Expert Systems with Applications: An International Journal
A collaborative anti-spam system

Expert Systems with Applications: An International Journal
Feature selection for text classification with Naïve Bayes

Expert Systems with Applications: An International Journal
Information Extraction

Foundations and Trends in Databases
A new sentence similarity measure and sentence based extractive technique for automatic text summarization

Expert Systems with Applications: An International Journal
Using the self organizing map for clustering of text documents

Expert Systems with Applications: An International Journal
Automatic classification of Tamil documents using vector space model and artificial neural network

Expert Systems with Applications: An International Journal
Using Wikipedia knowledge to improve text classification

Knowledge and Information Systems
Using IM and SMS for emergency text communications

Proceedings of the 3rd International Conference on Principles, Systems and Applications of IP Telecommunications
A machine learning approach to sentiment analysis in multilingual Web texts

Information Retrieval
Two learning approaches for protein name extraction

Journal of Biomedical Informatics
A News Analysis and Tracking System

PReMI '09 Proceedings of the 3rd International Conference on Pattern Recognition and Machine Intelligence
An effective refinement strategy for KNN text classifier

Expert Systems with Applications: An International Journal
Two-level hierarchical combination method for text classification

Expert Systems with Applications: An International Journal
Improving the performance of Naive Bayes multinomial in e-mail foldering by introducing distribution-based balance of datasets

Expert Systems with Applications: An International Journal
Language-Independent Clone Detection Applied to Plagiarism Detection

SCAM '10 Proceedings of the 2010 10th IEEE Working Conference on Source Code Analysis and Manipulation
An alternative approach for statistical single-label document classification of newspaper articles

Journal of Information Science
A crime reports analysis system to identify related crimes

Journal of the American Society for Information Science and Technology
Information retrieval techniques for corpus filtering applied to external plagiarism detection

NLDB'11 Proceedings of the 16th international conference on Natural language processing and information systems
A Rules and Statistical Learning Based Method for Chinese Patent Information Extraction

WISA '11 Proceedings of the 2011 Eighth Web Information Systems and Applications Conference
New methods for text categorization based on a new feature selection method and a new similarity measure between documents

IEA/AIE'06 Proceedings of the 19th international conference on Advances in Applied Artificial Intelligence: industrial, Engineering and Other Applications of Applied Intelligent Systems
An improved method of feature selection based on concept attributes in text classification

ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part I
Review: SMS spam filtering: Methods and data

Expert Systems with Applications: An International Journal
Automated text classification using a dynamic artificial neural network model

Expert Systems with Applications: An International Journal
A hybrid text classification approach with low dependency on parameter by integrating K-nearest neighbor and support vector machine

Expert Systems with Applications: An International Journal

Quantified Score

Hi-index	0.00

Visualization

Abstract

With an increasing number of anonymous crime tips and reports being filed and digitized, it is generally difficult for crime analysts to process and analyze crime reports efficiently. We are developing a decision support system (DSS), combining Natural Language Processing (NLP) techniques, a document similarity measure, and machine learning, i.e., a Naïve Bayes' classifier, to support crime analysis and classify which crime reports discuss the same and different crime. The DSS is developed with text mining techniques and evaluated with an active crime analyst. We report here on an experiment that includes two datasets with 40 and 60 crime reports and 16 different types of crimes for each dataset. The results show that our system achieved the highest classification accuracy (94.82%), while the crime analyst's classification accuracy (93.74%) is slightly lower.