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» Evaluating algorithms that learn from data streams
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ACL
2006
14 years 11 months ago
Learning Transliteration Lexicons from the Web
This paper presents an adaptive learning framework for Phonetic Similarity Modeling (PSM) that supports the automatic construction of transliteration lexicons. The learning algori...
Jin-Shea Kuo, Haizhou Li, Ying-Kuei Yang
ICDM
2006
IEEE
227views Data Mining» more  ICDM 2006»
15 years 4 months ago
Incremental Mining of Sequential Patterns over a Stream Sliding Window
Incremental mining of sequential patterns from data streams is one of the most challenging problems in mining data streams. However, previous work of mining sequential patterns fr...
Chin-Chuan Ho, Hua-Fu Li, Fang-Fei Kuo, Suh-Yin Le...
AIED
2009
Springer
15 years 4 months ago
I learn from you, you learn from me: How to make iList learn from students
We developed a new model for iList, our system that helps students learn linked list. The model is automatically extracted from past student data, and allows iList to track student...
Davide Fossati, Barbara Di Eugenio, Stellan Ohlsso...
ICDM
2010
IEEE
115views Data Mining» more  ICDM 2010»
14 years 8 months ago
Polishing the Right Apple: Anytime Classification Also Benefits Data Streams with Constant Arrival Times
Classification of items taken from data streams requires algorithms that operate in time sensitive and computationally constrained environments. Often, the available time for class...
Jin Shieh, Eamonn J. Keogh
CIKM
2006
Springer
15 years 1 months ago
Adaptive non-linear clustering in data streams
Data stream clustering has emerged as a challenging and interesting problem over the past few years. Due to the evolving nature, and one-pass restriction imposed by the data strea...
Ankur Jain, Zhihua Zhang, Edward Y. Chang