Volume 11, Number 1, June 2009

Open source analytics

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  Robert L. Grossman: Open source analytics: an introduction to the special issue. 3-4
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  Robert L. Grossman: What is analytic infrastructure and why should you care? 5-9
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  Mark Hall, Eibe Frank, Geoffrey Holmes, Bernhard Pfahringer, Peter Reutemann, Ian H. Witten: The WEKA data mining software: an update. 10-18
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  Rick Pechter: What's PMML and what's new in PMML 4.0? 19-25
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  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
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  Alex Guazzelli, Kostantinos Stathatos, Michael Zeller: Efficient deployment of predictive analytics through open standards and cloud computing. 32-38
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  Peter Christen: Development and user experiences of an open source data cleaning, deduplication and record linkage system. 39-48

Reports

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  Aparna S. Varde: Challenging research issues in data mining, databases and information retrieval. 49-52

PhD dissertation abstracts

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  Arthur Zimek: Correlation clustering. 53-54
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  Albert Bifet: Adaptive learning and mining for data streams and frequent patterns. 55-56
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  Tarek Hamrouni: Mining concise representations of frequent patterns through conjunctive and disjunctive search spaces. 57-58

Volume 11, Number 2, December 2009

Visual analytics and knowledge discovery

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  Kai Puolamäki, Alessio Bertone: Introduction to the special issue on visual analytics and knowledge discovery. 3-4
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  Daniel A. Keim, Florian Mansmann, Jim Thomas: Visual analytics: how much visualization and how much analytics? 5-8
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  Enrico Bertini, Denis Lalanne: Investigating and reflecting on the integration of automatic data analysis and visualization in knowledge discovery. 9-18
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  Gennady L. Andrienko, Natalia V. Andrienko: Interactive cluster analysis of diverse types of spatiotemporal data. 19-28
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  Sara Johansson, Jimmy Johansson: Visual analysis of mixed data sets using interactive quantification. 29-38
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  Carson Kai-Sang Leung, Christopher L. Carmichael: FpVAT: a visual analytic tool for supporting frequent pattern mining. 39-48
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  Harald Piringer, Matthias Buchetics, Helwig Hauser, Eduard Gröller: Hierarchical difference scatterplots: interactive visual analysis of data cubes. 49-58

PhD dissertation abstracts

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  Niels Landwehr: Trading expressivity for efficiency in statistical relational learning: Ph.D. thesis abstract. 59-60
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  Aris Gkoulalas-Divanis: From itemsets through trajectories to location based services: a knowledge hiding privacy approach. 61-62

KDD 2009 reports

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  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
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  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
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  Chris H. Q. Ding, Tao Li: KDD2009 workshop report DMMT'09: data mining using matrices and tensors. 77-79
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  Panagiotis G. Ipeirotis, Raman Chandrasekar, Paul N. Bennett: A report on the human computation workshop (HComp 2009). 80-83
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  Olufemi A. Omitaomu, Ranga Raju Vatsavai, Auroop R. Ganguly, Nitesh V. Chawla, Joao Gama, Mohamed Medhat Gaber: Knowledge discovery from sensor data (SensorKDD). 84-87
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  Jan Ramon, Fabrizio Costa, Christophe Costa Florêncio, Joost N. Kok: StReBio'09: statistical relational learning and mining in bioinformatics. 88-89
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  Jian Pei, Lise Getoor, Ander de Keijzer: Summary of the first ACM SIGKDD workshop on knowledge discovery from uncertain data (U'09). 90-91

Selected article from KDD 2009 workshops

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  Gaston L'Huillier, Richard Weber, Nicolas Figueroa: Online phishing classification using adversarial data mining and signaling games. 92-99
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  Winter A. Mason, Duncan J. Watts: Financial incentives and the "performance of crowds". 100-108
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  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
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  Huma Lodhi, Stephen Muggleton, Michael J. E. Sternberg: Multi-Class protein fold recognition using large margin logic based divide and conquer learning. 117-122
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  Carson Kai-Sang Leung, Dale A. Brajczuk: Efficient algorithms for the mining of constrained frequent patterns from uncertain data. 123-130