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Can I read A Probabilistic Framework to Learn from Multiple Annotators with Time-Varying Accuracy on EtoBox?
A Probabilistic Framework to Learn from Multiple Annotators with Time-Varying Accuracy by Parthasarathy, Srinivasan; Liu, Bing; Goethals, Bart; Pei, Jian; Kamath, Chandrika is a scholarly article available to read on EtoBox.
What is A Probabilistic Framework to Learn from Multiple Annotators with Time-Varying Accuracy about?
Welcome to the Tenth SIAM International Conference on Data Mining (SDM 2010). This year's conference is a continuation of the great success in the SDM conference series as one of the leading forums for data mining researchers, practitioners, developers, and users to exchange cutting-edge ideas, techniques, and experience. SDM 2010 received 344 submissions contributed by authors worldwide, from countries such as Australia, Belgium, Brazil, Canada, China, Denmark, Finland, France, Germany, Hong Kong, Hungary, India, Italy, Japan, Korea, Mexico, New Zealand, Portugal, the Republic of Serbia, Russia, San Marino, Sweden, Singapore, Spain, Taiwan, Thailand, Turkey, the United Kingdom, and the United States. This truly reflected the international character of this conference. Moreover, 198 submissions were claimed as student papers, a strong indication that SDM 2010 has attracted the upcoming generation of data miners. We did not have any target number of accepted papers in mind when we started the review process. Instead, we advocated both quality and novelty. We strongly encouraged new ideas and new applications. This year we implemented a new review protocol which divided the review pr
- Author
- Parthasarathy, Srinivasan; Liu, Bing; Goethals, Bart; Pei, Jian; Kamath, Chandrika
- Publisher
- Society for Industrial and Applied Mathematics (SIAM, 3600 Market Street, Floor 6, Philadelphia, PA 19104)
- Published
- 2010
- Language
- EN
- ISBN
- 9781611972801