Advances in knowledge discovery and data mining
Advances in knowledge discovery and data mining
From data mining to knowledge discovery: an overview
Advances in knowledge discovery and data mining
A statistical perspective on knowledge discovery in databases
Advances in knowledge discovery and data mining
Bayesian networks for knowledge discovery
Advances in knowledge discovery and data mining
Fast discovery of association rules
Advances in knowledge discovery and data mining
Automating the analysis and cataloging of sky surveys
Advances in knowledge discovery and data mining
Knowledge Discovery in Databases
Knowledge Discovery in Databases
Knowledge Discovery in Personal Data vs. Privacy: A mini-symposium
IEEE Expert: Intelligent Systems and Their Applications
Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
Machine Learning - Special issue on applications of machine learning and the knowledge discovery process
ACM Computing Surveys (CSUR)
intelligence
Interactive mining and knowledge reuse for the closed-itemset incremental-mining problem
ACM SIGKDD Explorations Newsletter
Accuracy of software quality models over multiple releases
Annals of Software Engineering
Balancing Misclassification Rates in Classification-TreeModels of Software Quality
Empirical Software Engineering
Data Mining of Software Development Databases
Software Quality Control
A Knowledge Discovery by Fuzzy Rule Based Hopfield Network
IDEAL '02 Proceedings of the Third International Conference on Intelligent Data Engineering and Automated Learning
Investigating and Evaluating Behavioural Profiling and Intrusion Detection Using Data Mining
MMM-ACNS '01 Proceedings of the International Workshop on Information Assurance in Computer Networks: Methods, Models, and Architectures for Network Security
Integrated Architectures for Machine Learning
Machine Learning and Its Applications, Advanced Lectures
Data mining tasks and methods: Classification: nearest-neighbor approaches
Handbook of data mining and knowledge discovery
A survey of data mining and knowledge discovery software tools
ACM SIGKDD Explorations Newsletter
Classification Tree Models of Software Quality Over Multiple Releases
ISSRE '99 Proceedings of the 10th International Symposium on Software Reliability Engineering
Improving Tree-Based Models of Software Quality with Principal Components Analysis
ISSRE '00 Proceedings of the 11th International Symposium on Software Reliability Engineering
Analogy-Based Practical Classification Rules for Software Quality Estimation
Empirical Software Engineering
Comparative Assessment of Software Quality Classification Techniques: An Empirical Case Study
Empirical Software Engineering
Enhancing OLAP functionality using self-organizing neural networks
Neural, Parallel & Scientific Computations - Special issue: Computing intelligence in management
Assessment of a New Three-Group Software Quality Classification Technique: An Empirical Case Study
Empirical Software Engineering
An empirical study of predicting software faults with case-based reasoning
Software Quality Control
The impact of sample reduction on PCA-based feature extraction for supervised learning
Proceedings of the 2006 ACM symposium on Applied computing
A machine learning method with hybrid neural networks for spectrum analysis
Proceedings of the 44th annual Southeast regional conference
Knowledge reduction based on the equivalence relations defined on attribute set and its power set
Information Sciences: an International Journal
Systematic development of data mining-based data quality tools
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Feature Extraction for Dynamic Integration of Classifiers
Fundamenta Informaticae
Focusing solutions for data mining: analytical studies and experimental results in real-world domains
Towards the Generic Framework for Utility Considerations in Data Mining Research
Proceedings of the 2010 conference on Data Mining for Business Applications
Data mining applications in hydrocarbon exploration
Artificial Intelligence Review
Product development with data mining techniques: A case on design of digital camera
Expert Systems with Applications: An International Journal
Positional and confidence voting-based consensus functions for fuzzy cluster ensembles
Fuzzy Sets and Systems
The impact of feature extraction on the performance of a classifier: kNN, Naïve Bayes and C4.5
AI'05 Proceedings of the 18th Canadian Society conference on Advances in Artificial Intelligence
Using data mining technique to enhance tax evasion detection performance
Expert Systems with Applications: An International Journal
More than modelling and hiding: towards a comprehensive view of Web mining and privacy
Data Mining and Knowledge Discovery
Feature Extraction for Dynamic Integration of Classifiers
Fundamenta Informaticae
Study of Sensitive Parameters of PSO Application to Clustering of Texts
International Journal of Applied Evolutionary Computation
Journal of Information Science
| Hi-index | 0.00 |
THE RAPIDLY EMERGING FIELD OF knowledge discovery in databases (KDD) has grown significantly in the past few years. This growth is driven by a mix of daunting practical needs and strong research interest. The technology for computing and storage has enabled people to collect and store information from a wide range of sources at rates that were, only a few years ago, considered unimaginable. Although modern database technology enables economical storage of these large streams of data, we do not yet have the technology to help us analyze, understand, or even visualize this stored data.Examples of this phenomenon abound in a wide spectrum of fields: finance, banking, retail sales, manufacturing, monitoring and diagnosis (be it of humans or machines), health care, marketing, and science data acquisition, among others. In science, modern instruments can easily measure and collect terabytes (1012 bytes) of data. For example, NASA's Earth Observing System is expected to return data at rates of several gigabytes per hour by the end of the century. Quite appropriately, the problem of how to put the torrent of data to use in analysis is often called "drinking from the fire hose." What we mean by analysis is not well-defined because it is highly context- and goal-dependent. However, as I argue, it typically transcends by far anything achievable via simple queries, simple string matching, or mechanisms for displaying the data.Prolific sources of data are not restricted to esoteric endeavors involving spacecraft or sophisticated scientific instruments. Imagine a database receiving transactions from common daily activities such as supermarket or department store checkout-register sales, or credit card charges. Or think of the information reaching your home television set as a stream of signals that, to be properly managed, need to be cataloged and indexed, and perhaps searched for interesting content at a higher level--channels, programs, genre, or mood, for example. The explosion in the number of resources available on the global computer network--the World Wide Web--is another challenge for indexing and searching through a continually changing and growing "database."