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ORCIDSIGKDD Explorations, Volume 11
Volume 11, Number 1, June 2009
- Robert L. Grossman:
Open source analytics: an introduction to the special issue. 3-4 - Robert L. Grossman:
What is analytic infrastructure and why should you care? 5-9 - Mark A. Hall, Eibe Frank, Geoffrey Holmes, Bernhard Pfahringer, Peter Reutemann
, Ian H. Witten:
The WEKA data mining software: an update. 10-18 - Rick Pechter:
What's PMML and what's new in PMML 4.0? 19-25 - Michael R. Berthold, Nicolas Cebron, Fabian Dill, Thomas R. Gabriel, Tobias Kötter, Thorsten Meinl, Peter Ohl, Kilian Thiel, Bernd Wiswedel:
KNIME - the Konstanz information miner: version 2.0 and beyond. 26-31 - Alex Guazzelli, Kostantinos Stathatos, Michael Zeller:
Efficient deployment of predictive analytics through open standards and cloud computing. 32-38 - Peter Christen:
Development and user experiences of an open source data cleaning, deduplication and record linkage system. 39-48
- Aparna S. Varde:
Challenging research issues in data mining, databases and information retrieval. 49-52
- Arthur Zimek:
Correlation clustering. 53-54 - Albert Bifet:
Adaptive learning and mining for data streams and frequent patterns. 55-56 - Tarek Hamrouni:
Mining concise representations of frequent patterns through conjunctive and disjunctive search spaces. 57-58
Volume 11, Number 2, December 2009
- Kai Puolamäki, Alessio Bertone:
Introduction to the special issue on visual analytics and knowledge discovery. 3-4 - Daniel A. Keim, Florian Mansmann, James J. Thomas:
Visual analytics: how much visualization and how much analytics? 5-8 - Enrico Bertini, Denis Lalanne:
Investigating and reflecting on the integration of automatic data analysis and visualization in knowledge discovery. 9-18 - Gennady L. Andrienko, Natalia V. Andrienko:
Interactive cluster analysis of diverse types of spatiotemporal data. 19-28 - Sara Johansson, Jimmy Johansson:
Visual analysis of mixed data sets using interactive quantification. 29-38 - Carson Kai-Sang Leung, Christopher L. Carmichael:
FpVAT: a visual analytic tool for supporting frequent pattern mining. 39-48 - Harald Piringer, Matthias Buchetics, Helwig Hauser, M. Eduard Gröller:
Hierarchical difference scatterplots: interactive visual analysis of data cubes. 49-58
- Niels Landwehr:
Trading expressivity for efficiency in statistical relational learning: Ph.D. thesis abstract. 59-60 - Aris Gkoulalas-Divanis:
From itemsets through trajectories to location based services: a knowledge hiding privacy approach. 61-62
- Peter A. Flach, Sebastian Spiegler, Bruno Golénia, Simon Price, John Guiver, Ralf Herbrich, Thore Graepel, Mohammed J. Zaki:
Novel tools to streamline the conference review process: experiences from SIGKDD'09. 63-67 - Isabelle Guyon, Vincent Lemaire, Marc Boullé, Gideon Dror, David Vogel:
Design and analysis of the KDD cup 2009: fast scoring on a large orange customer database. 68-76 - Chris H. Q. Ding, Tao Li:
KDD2009 workshop report DMMT'09: data mining using matrices and tensors. 77-79 - Panagiotis G. Ipeirotis, Raman Chandrasekar, Paul N. Bennett:
A report on the human computation workshop (HComp 2009). 80-83 - Olufemi A. Omitaomu, Ranga Raju Vatsavai, Auroop R. Ganguly, Nitesh V. Chawla, João Gama, Mohamed Medhat Gaber:
Knowledge discovery from sensor data (SensorKDD). 84-87 - Jan Ramon, Fabrizio Costa, Christophe Costa Florêncio, Joost N. Kok:
StReBio'09: statistical relational learning and mining in bioinformatics. 88-89 - Jian Pei, Lise Getoor, Ander de Keijzer:
Summary of the first ACM SIGKDD workshop on knowledge discovery from uncertain data (U'09). 90-91
- Gaston L'Huillier, Richard Weber, Nicolás Figueroa:
Online phishing classification using adversarial data mining and signaling games. 92-99 - Winter A. Mason, Duncan J. Watts:
Financial incentives and the "performance of crowds". 100-108 - Mykola Pechenizkiy, Jorn Bakker, Indre Zliobaite, Andriy Ivannikov, Tommi Kärkkäinen:
Online mass flow prediction in CFB boilers with explicit detection of sudden concept drift. 109-116 - Huma Lodhi, Stephen H. Muggleton, Michael J. E. Sternberg:
Multi-Class protein fold recognition using large margin logic based divide and conquer learning. 117-122 - Carson Kai-Sang Leung, Dale A. Brajczuk:
Efficient algorithms for the mining of constrained frequent patterns from uncertain data. 123-130
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