Artificial intelligence and statistics
Task-structure analysis for knowledge modeling
Communications of the ACM - Special issue on analysis and modeling in software development
Generalizing from case studies: a case study
ML92 Proceedings of the ninth international workshop on Machine learning
The cost structure of sensemaking
INTERCHI '93 Proceedings of the INTERCHI '93 conference on Human factors in computing systems
Consultant-2: pre- and post-processing of machine learning applications
International Journal of Human-Computer Studies
Machine learning, neural and statistical classification
Machine learning, neural and statistical classification
Hierarchical task network planning: formalization, analysis, and implementation
Hierarchical task network planning: formalization, analysis, and implementation
Fast planning through planning graph analysis
Artificial Intelligence
KDD-Cup 2000 organizers' report: peeling the onion
ACM SIGKDD Explorations Newsletter - Special issue on “Scalable data mining algorithms”
A perspective view and survey of meta-learning
Artificial Intelligence Review
What Are Ontologies, and Why Do We Need Them?
IEEE Intelligent Systems
Estimating the Predictive Accuracy of a Classifier
EMCL '01 Proceedings of the 12th European Conference on Machine Learning
Ranking with Predictive Clustering Trees
ECML '02 Proceedings of the 13th European Conference on Machine Learning
Meta-Learning by Landmarking Various Learning Algorithms
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Towards Process-Oriented Tool Support for Knowledge Discovery in Databases
PKDD '97 Proceedings of the First European Symposium on Principles of Data Mining and Knowledge Discovery
AST: Support for Algorithm Selection with a CBR Approach
PKDD '99 Proceedings of the Third European Conference on Principles of Data Mining and Knowledge Discovery
Fusion of Meta-knowledge and Meta-data for Case-Based Model Selection
PKDD '01 Proceedings of the 5th European Conference on Principles of Data Mining and Knowledge Discovery
METALA: A Meta-learning Architecture
Proceedings of the International Conference, 7th Fuzzy Days on Computational Intelligence, Theory and Applications
Improved Dataset Characterisation for Meta-learning
DS '02 Proceedings of the 5th International Conference on Discovery Science
Intelligent Data Analysis: Issues and Opportunities
IDA '97 Proceedings of the Second International Symposium on Advances in Intelligent Data Analysis, Reasoning about Data
A survey of data mining and knowledge discovery software tools
ACM SIGKDD Explorations Newsletter
IEEE Transactions on Knowledge and Data Engineering
The Data Mining Advisor: Meta-learning at the Service of Practitioners
ICMLA '05 Proceedings of the Fourth International Conference on Machine Learning and Applications
YALE: rapid prototyping for complex data mining tasks
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Spss Programming And Data Management: A Guide for Spss And Sas Users
Spss Programming And Data Management: A Guide for Spss And Sas Users
Introduction to Data Mining Using SAS Enterprise Miner
Introduction to Data Mining Using SAS Enterprise Miner
Pellet: A practical OWL-DL reasoner
Web Semantics: Science, Services and Agents on the World Wide Web
Intelligent Data Analysis - Philosophies and Methodologies for Knowledge Discovery
The NExT System: Towards True Dynamic Adaptations of Semantic Web Service Compositions
ESWC '07 Proceedings of the 4th European conference on The Semantic Web: Research and Applications
Experiment Databases: Towards an Improved Experimental Methodology in Machine Learning
PKDD 2007 Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases
Cross-disciplinary perspectives on meta-learning for algorithm selection
ACM Computing Surveys (CSUR)
Future Generation Computer Systems
Ontology-Driven KDD Process Composition
IDA '09 Proceedings of the 8th International Symposium on Intelligent Data Analysis: Advances in Intelligent Data Analysis VIII
A planning approach for message-oriented semantic web service composition
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
The FF planning system: fast plan generation through heuristic search
Journal of Artificial Intelligence Research
PDDL2.1: an extension to PDDL for expressing temporal planning domains
Journal of Artificial Intelligence Research
Layered concept-learning and dynamically variable bias management
IJCAI'87 Proceedings of the 10th international joint conference on Artificial intelligence - Volume 1
The WEKA data mining software: an update
ACM SIGKDD Explorations Newsletter
KNIME - the Konstanz information miner: version 2.0 and beyond
ACM SIGKDD Explorations Newsletter
Towards an Ontology of Data Mining Investigations
DS '09 Proceedings of the 12th International Conference on Discovery Science
HTN planning for Web Service composition using SHOP2
Web Semantics: Science, Services and Agents on the World Wide Web
An iterative process for building learning curves and predicting relative performance of classifiers
EPIA'07 Proceedings of the aritficial intelligence 13th Portuguese conference on Progress in artificial intelligence
Meta-learning experiences with the mindful system
CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part I
Meta-data: characterization of input features for meta-learning
MDAI'05 Proceedings of the Second international conference on Modeling Decisions for Artificial Intelligence
Machine Learning
Pairwise meta-rules for better meta-learning-based algorithm ranking
Machine Learning
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Research and industry increasingly make use of large amounts of data to guide decision-making. To do this, however, data needs to be analyzed in typically nontrivial refinement processes, which require technical expertise about methods and algorithms, experience with how a precise analysis should proceed, and knowledge about an exploding number of analytic approaches. To alleviate these problems, a plethora of different systems have been proposed that “intelligently” help users to analyze their data. This article provides a first survey to almost 30 years of research on intelligent discovery assistants (IDAs). It explicates the types of help IDAs can provide to users and the kinds of (background) knowledge they leverage to provide this help. Furthermore, it provides an overview of the systems developed over the past years, identifies their most important features, and sketches an ideal future IDA as well as the challenges on the road ahead.