Existing graph mining algorithms typically assume that the dataset can fit into main memory. As many large graph datasets cannot satisfy this condition, truly scalable graph minin...
In recent years, many data mining methods have been proposed for finding useful and structured information from market basket data. The association rule model was recently propos...
Batched stream processing is a new distributed data processing paradigm that models recurring batch computations on incrementally bulk-appended data streams. The model is inspired...
Bingsheng He, Mao Yang, Zhenyu Guo, Rishan Chen, B...
Abstract. The development of scalable parallel database systems requires the design of efficient algorithms for the join operation which is the most frequent and expensive operatio...
A k-set structure over data streams is a bounded-space data structure that supports stream insertion and deletion operations and returns the set of (item, frequency) pairs in the s...