Advances in software inspections
IEEE Transactions on Software Engineering
C4.5: programs for machine learning
C4.5: programs for machine learning
Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Wrappers for feature subset selection
Artificial Intelligence - Special issue on relevance
Detecting change in categorical data: mining contrast sets
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Software Cost Estimation with Cocomo II with Cdrom
Software Cost Estimation with Cocomo II with Cdrom
Heuristic Risk Assessment Using Cost Factors
IEEE Software
Converging on the Optimal Attainment of Requirements
RE '02 Proceedings of the 10th Anniversary IEEE Joint International Conference on Requirements Engineering
Combining the Best Attributes of Qualitative and Quantitative Risk Management Tool Support
ASE '00 Proceedings of the 15th IEEE international conference on Automated software engineering
Practical Large Scale What-if Queries: Case Studies with Software Risk Assessment
ASE '00 Proceedings of the 15th IEEE international conference on Automated software engineering
Proceedings of the 17th IEEE international conference on Automated software engineering
Mining Association Rules with Weighted Items
IDEAS '98 Proceedings of the 1998 International Symposium on Database Engineering & Applications
The Strangest Thing About Software
Computer
The business case for automated software engineering
Proceedings of the twenty-second IEEE/ACM international conference on Automated software engineering
Just enough learning (of association rules): the TAR2 "Treatment" learner
Artificial Intelligence Review
Optimizing requirements decisions with keys
Proceedings of the 4th international workshop on Predictor models in software engineering
ISSTA '08 Proceedings of the 2008 international symposium on Software testing and analysis
Mining decision rules on data streams in the presence of concept drifts
Expert Systems with Applications: An International Journal
Supporting the discovery and labeling of non-taxonomic relationships in ontology learning
Expert Systems with Applications: An International Journal
Automatically finding the control variables for complex system behavior
Automated Software Engineering
The inductive software engineering manifesto: principles for industrial data mining
Proceedings of the International Workshop on Machine Learning Technologies in Software Engineering
Group SAX: extending the notion of contrast sets to time series and multimedia data
PKDD'06 Proceedings of the 10th European conference on Principle and Practice of Knowledge Discovery in Databases
Multiclass credit cardholders’ behaviors classification methods
ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part IV
Symbolic execution enhanced system testing
VSTTE'12 Proceedings of the 4th international conference on Verified Software: theories, tools, experiments
International Journal of Multimedia Data Engineering & Management
| Hi-index | 4.10 |
Most modern businesses can access mountains of data electronically驴the trick is effectively using that data. In practice, this means summarizing large data sets to find the data that really matters. Most data miners are zealous hunters seeking detailed summaries and generating extensive and lengthy descriptions. The authors take a different approach and assume that busy people don't need驴or can't use驴complex models. Rather, they want only the data they need to achieve the most benefits.Instead of finding extensive descriptions of things, their data mining tool hunts for a minimal difference set between things because they believe a list of essential differences is easier to read and understand than detailed descriptions.