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CIKM
2004
Springer
15 years 4 months ago
Hierarchical document categorization with support vector machines
Automatically categorizing documents into pre-defined topic hierarchies or taxonomies is a crucial step in knowledge and content management. Standard machine learning techniques ...
Lijuan Cai, Thomas Hofmann
ISCA
1993
IEEE
112views Hardware» more  ISCA 1993»
15 years 2 months ago
Working Sets, Cache Sizes, and Node Granularity Issues for Large-Scale Multiprocessors
The distribution of resources among processors, memory and caches is a crucial question faced by designers of large-scale parallel machines. If a machine is to solve problems with...
Edward Rothberg, Jaswinder Pal Singh, Anoop Gupta
BMCBI
2006
108views more  BMCBI 2006»
14 years 10 months ago
Gene function classification using Bayesian models with hierarchy-based priors
We investigate the application of hierarchical classification schemes to the annotation of gene function based on several characteristics of protein sequences including phylogenic ...
Babak Shahbaba, Radford M. Neal
CORR
1999
Springer
93views Education» more  CORR 1999»
14 years 10 months ago
On the Power of Positive Turing Reductions
: In the early 1980s, Selman's seminal work on positive Turing reductions showed that positive Turing reduction to NP yields no greater computational power than NP itself. Thu...
Edith Hemaspaandra
NAR
2002
164views more  NAR 2002»
14 years 10 months ago
SCOP database in 2002: refinements accommodate structural genomics
The SCOP (Structural Classification of Proteins) database is a comprehensive ordering of all proteins of known structure, according to their evolutionary and structural relationsh...
Loredana Lo Conte, Steven E. Brenner, Tim J. P. Hu...