Detecting duplicates in data streams is an important problem that has a wide range of applications. In general, precisely detecting duplicates in an unbounded data stream is not fe...
Dynamic data streams are those whose underlying distribution changes over time. They occur in a number of application domains, and mining them is important for these applications....
Events and stories can be characterized by a set of descriptive, collocated keywords. Intuitively, documents describing the same event will contain similar sets of keywords, and t...
Discovering associations between elements occurring in a stream is applicable in numerous applications, including predictive caching and fraud detection. These applications requir...
Supporting continuous mining queries on data streams requires algorithms that (i) are fast, (ii) make light demands on memory resources, and (iii) are easily to adapt to concept dr...