Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-s...
Discriminative training for structured outputs has found increasing applications in areas such as natural language processing, bioinformatics, information retrieval, and computer ...
Previous work on text mining has almost exclusively focused on a single stream. However, we often have available multiple text streams indexed by the same set of time points (call...
Xuanhui Wang, ChengXiang Zhai, Xiao Hu, Richard Sp...
Summarization is an important task in data mining. A major challenge over the past years has been the efficient construction of fixed-space synopses that provide a deterministic q...
In many text classification applications, it is appealing to take every document as a string of characters rather than a bag of words. Previous research studies in this area mostl...