sequence content at an abstract level and offers novel ways to examine the information contained in them. Our approach is an information theoretic search process which uses patter...
This paper presents a prototype-driven framework for classifying evolving data streams. Our framework uses cluster prototypes to summarize the data and to determine whether the cur...
In this paper, we propose a new approach for the automatic audio-based out-of-scene detection of audio-visual data, recorded by different cameras, camcorders or mobile phones duri...
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...
We present a document-specific OCR system and apply it to a corpus of faxed business letters. Unsupervised classification of the segmented character bitmaps on each page, using a ...