An introduction to SIGKDD and a reflection on the term 'data mining'

  title={An introduction to SIGKDD and a reflection on the term 'data mining'},
  author={G. Piatetsky-Shapiro and U. Fayyad},
  journal={SIGKDD Explor.},
The primary focus of SIGKDD is to provide the premier forum for advancement and adoption of the "science" of knowledge discovery and data mining. SIGKDD main activity is to organize KDD, the leading conference on data mining and knowledge discovery , held since 1995. KDD conference is top-ranked in Data Mining, according to Microsoft Research Asia. KDD-2011 was held in San Diego, CA, USA was the largest data-mining meeting in the world, with over 1,100 participants from around the world. 
A Mining Approach to Evaluate Geoportals Usability
  • Esther Hochsztain
  • Computer Science
  • 2015 International Workshop on Data Mining with Industrial Applications (DMIA)
  • 2015
A framework is proposed based on several data sources in order to identify geoportals strengths and weaknesses affecting usability, and a case study is presented, performing web server logs analysis and System Usability Scale questionnaire experimental data analysis applying factor analysis and association rules. Expand
Combination of cognitive and HCI modeling for the design of KDD-based DSS used in dynamic situations
This work proposes to adapt the well-known Hoc and Amalberti model cognitive model under the KDD specificities and provides cognitive modeling application in visual KDD-based dynamic DSS for the fight against nosocomial infections in an intensive care unit. Expand
Intelligent big data analysis: a review
Open issues and future research trends using computational intelligence technologies are presented to show their potentials for big data. Expand
Mining Multiple Level Association Rules to Mining Multiple Level Correlations to Discover Complex Patterns
Mining multiple levels is explored and extended to mining cross levels in large database on the basis of user specified reduced support threshold constraint and identification of complex frequent patterns. Expand