Traditional text classification algorithms are based on a basic assumption: the training and test data should hold the same distribution. However, this identical distribution assum...
Classification fusion combines multiple classifications of data into a single classification solution of greater accuracy. Feature extraction aims to reduce the computational cost ...
Behrouz Minaei-Bidgoli, Gerd Kortemeyer, William F...
In the intellectual property field two tasks are of high relevance: prior art searching and patent classification. Prior art search is fundamental for many strategic issues such as...
Douglas Teodoro, Julien Gobeill, Emilie Pasche, Di...
Background: Feature selection techniques are critical to the analysis of high dimensional datasets. This is especially true in gene selection from microarray data which are common...
Pengyi Yang, Bing Bing Zhou, Zili Zhang, Albert Y....
Packet Classification (PC) has been a critical data path function for many emerging networking applications. An interesting approach is the use of TCAM to achieve deterministic, hi...