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» Evaluating algorithms that learn from data streams
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ICNP
2003
IEEE
15 years 5 months ago
Resilient Peer-to-Peer Streaming
We consider the problem of distributing “live” streaming media content to a potentially large and highly dynamic population of hosts. Peer-to-peer content distribution is attr...
Venkata N. Padmanabhan, Helen J. Wang, Philip A. C...
AUSDM
2008
Springer
225views Data Mining» more  AUSDM 2008»
15 years 2 months ago
Evaluation of Malware clustering based on its dynamic behaviour
Malware detection is an important problem today. New malware appears every day and in order to be able to detect it, it is important to recognize families of existing malware. Dat...
Ibai Gurrutxaga, Olatz Arbelaitz, Jesús M. ...
ACL
2006
15 years 1 months ago
Weakly Supervised Named Entity Transliteration and Discovery from Multilingual Comparable Corpora
Named Entity recognition (NER) is an important part of many natural language processing tasks. Current approaches often employ machine learning techniques and require supervised d...
Alexandre Klementiev, Dan Roth
ADC
2008
Springer
112views Database» more  ADC 2008»
15 years 6 months ago
Semantics based Buffer Reduction for Queries over XML Data Streams
With respect to current methods for query evaluation over XML data streams, adoption of certain types of buffering techniques is unavoidable. Under lots of circumstances, the buff...
Chi Yang, Chengfei Liu, Jianxin Li, Jeffrey Xu Yu,...
PR
2007
81views more  PR 2007»
15 years 21 hour ago
Mining evolving data streams for frequent patterns
A data stream is a potentially uninterrupted flow of data. Mining this flow makes it necessary to cope with uncertainty, as only a part of the stream can be stored. In this pape...
Pierre-Alain Laur, Richard Nock, Jean-Emile Sympho...