Mining frequent itemsets from data streams has proved to be very difficult because of computational complexity and the need for real-time response. In this paper, we introduce a no...
In this paper we investigate algorithms and lower bounds for summarization problems over a single pass data stream. In particular we focus on histogram construction and K-center c...
Preference queries have received considerable attention in the recent past, due to their use in selecting the most preferred objects, especially when the selection criteria are con...
Maria Kontaki, Apostolos N. Papadopoulos, Yannis M...
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...
Abstract. We present a new method for voting exponential (in the number of attributes) size sets of Bayesian classifiers in polynomial time with polynomial memory requirements. Tra...