Similarity-based reasoning about diagnosis of analog circuits
IEA/AIE '88 Proceedings of the 1st international conference on Industrial and engineering applications of artificial intelligence and expert systems - Volume 1
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
Neural Networks
Temporal reasoning and planning
Reasoning about plans
Tolerating noisy, irrelevant and novel attributes in instance-based learning algorithms
International Journal of Man-Machine Studies - Special issue: symbolic problem solving in noisy and novel task environments
Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Knowledge acquisition and learning by experience—the role of case-specific knowledge
Machine learning and knowledge acquisition
The KDD process for extracting useful knowledge from volumes of data
Communications of the ACM
Reasoning with complex cases
Data mining and KDD: promise and challenges
Future Generation Computer Systems - Special double issue on data mining
Predictive data mining: a practical guide
Predictive data mining: a practical guide
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
Causality: models, reasoning, and inference
Causality: models, reasoning, and inference
Data mining: concepts and techniques
Data mining: concepts and techniques
Knowledge discovery for decision support in law
ICIS '00 Proceedings of the twenty first international conference on Information systems
Data mining case study: modeling the behavior of offenders who commit serious sexual assaults
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Artificial Neural Networks: Theory and Applications
Artificial Neural Networks: Theory and Applications
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Introduction to Bayesian Networks
Introduction to Bayesian Networks
Probabilistic Networks and Expert Systems
Probabilistic Networks and Expert Systems
Representing Uncertain Knowledge: An Artificial Intelligence Approach
Representing Uncertain Knowledge: An Artificial Intelligence Approach
BAYES AND EMPIRICAL BAYES METHODS FOR DATA ANALYSIS
Statistics and Computing
Investigative Data Mining for Security and Criminal Detection
Investigative Data Mining for Security and Criminal Detection
COPLINK: managing law enforcement data and knowledge
Communications of the ACM
Intelligent Indexing of Crime Scene Photographs
IEEE Intelligent Systems
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Explanation-Driven Case-Based Reasoning
EWCBR '93 Selected papers from the First European Workshop on Topics in Case-Based Reasoning
Data Clustering and Rule Abduction to Facilitate Crime Hot Spot Prediction
Proceedings of the International Conference, 7th Fuzzy Days on Computational Intelligence, Theory and Applications
GIS: A Weapon to Combat the Crime
ISAS-SCI '01 Proceedings of the World Multiconference on Systemics, Cybernetics and Informatics: Information Systems Development-Volume I - Volume I
Case-base maintenance: the husbandry of experience
Case-base maintenance: the husbandry of experience
Computational Statistics & Data Analysis - Data visualization
Learner: a system for acquiring commonsense knowledge by analogy
Proceedings of the 2nd international conference on Knowledge capture
Towards systematic design of distance functions for data mining applications
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Human Problem Solving
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Prioritizing of offenders in networks
SMO'06 Proceedings of the 6th WSEAS International Conference on Simulation, Modelling and Optimization
Criminal Cross Correlation Mining and Visualization
PAISI '09 Proceedings of the Pacific Asia Workshop on Intelligence and Security Informatics
Mining top-k and Bottom-k correlative crime patternsthrough graph representations
ISI'09 Proceedings of the 2009 IEEE international conference on Intelligence and security informatics
Compositional Bayesian modelling for computation of evidence collection strategies
Applied Intelligence
Hi-index | 0.00 |
The paper sets out the challenges facing the Police in respect of the detection and prevention of the volume crime of burglary. A discussion of data mining and decision support technologies that have the potential to address these issues is undertaken and illustrated with reference the authors' work with three Police Services. The focus is upon the use of "soft" forensic evidence which refers to modus operandi and the temporal and geographical features of the crime, rather than "hard" evidence such as DNA or fingerprint evidence. Three objectives underpin this paper. First, given the continuing expansion of forensic computing and its role in the emergent discipline of Crime Science, it is timely to present a review of existing methodologies and research. Second, it is important to extract some practical lessons concerning the application of computer science within this forensic domain. Finally, from the lessons to date, a set of conclusions will be advanced, including the need for multidisciplinary input to guide further developments in the design of such systems. The objectives are achieved by first considering the task performed by the intended systems users. The discussion proceeds by identifying the portions of these tasks for which automation would be both beneficial and feasible. The knowledge discovery from databases process is then described, starting with an examination of the data that police collect and the reasons for storing it. The discussion progresses to the development of crime matching and predictive knowledge which are operationalised in decision support software. The paper concludes by arguing that computer science technologies which can support criminal investigations are wide ranging and include geographical information systems displays, clustering and link analysis algorithms and the more complex use of data mining technology for profiling crimes or offenders and matching and predicting crimes. We also argue that knowledge from disciplines such as forensic psychology, criminology and statistics are essential to the efficient design of operationally valid systems.