Incorporating background knowledge into data mining algorithms is an important but challenging problem. Current approaches in semi-supervised learning require explicit knowledge p...
Samah Jamal Fodeh, William F. Punch, Pang-Ning Tan
Sensor networks usually generate continuous stream of data over time. Clustering sensor data as a core task of mining sensor data plays an essential role in analytical application...
Amirhosein Taherkordi, Reza Mohammadi, Frank Elias...
Named Entity Recognition is a relatively well-understood NLP task, with many publicly available training resources and software for English. Other languages tend to be underserved...
Keeping track of changes in user interests from a document stream with a few relevance judgments is not an easy task. To tackle this problem, we propose a novel method that integr...
We introduce a robust and efficient framework called CLUMP (CLustering Using Multiple Prototypes) for unsupervised discovery of structure in data. CLUMP relies on finding multip...