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CIKM
2009
Springer
15 years 4 months ago
On domain similarity and effectiveness of adapting-to-rank
Adapting to rank address the the problem of insufficient domainspecific labeled training data in learning to rank. However, the initial study shows that adaptation is not always...
Keke Chen, Jing Bai, Srihari Reddy, Belle L. Tseng
KDD
2005
ACM
147views Data Mining» more  KDD 2005»
15 years 3 months ago
Combining proactive and reactive predictions for data streams
Mining data streams is important in both science and commerce. Two major challenges are (1) the data may grow without limit so that it is difficult to retain a long history; and (...
Ying Yang, Xindong Wu, Xingquan Zhu
SIAMCOMP
2008
167views more  SIAMCOMP 2008»
14 years 10 months ago
Approximation Algorithms for Data Placement Problems
We develop approximation algorithms for the problem of placing replicated data in arbitrary networks, where the nodes may both issue requests for data objects and have capacity fo...
Ivan D. Baev, Rajmohan Rajaraman, Chaitanya Swamy
CATE
2004
190views Education» more  CATE 2004»
14 years 11 months ago
Enhancing Online Learning Performance: An Application of Data Mining Methods
Recently web-based educational systems collect vast amounts of data on user patterns, and data mining methods can be applied to these databases to discover interesting associations...
Behrouz Minaei-Bidgoli, Gerd Kortemeyer, William F...
WSC
1998
14 years 11 months ago
Adaptive Stochastic Manpower Scheduling
Bayesian forecasting models provide distributional estimates for random parameters, and relative to classical schemes, have the advantage that they can rapidly capture changes in ...
Elmira Popova, David P. Morton