SIGKDD 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 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, Jim 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, 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, Joao 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, Nicolas 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 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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