Finding Frequent Items over General Update Streams
نویسندگان
چکیده
We present novel space and time-efficient algorithms for finding frequent items over general update streams. Our algorithms are based on a novel adaptation of the popular dyadic intervals method for finding frequent items. The algorithms improve upon existing algorithms in both theory and practice.
منابع مشابه
CR-precis: A Deterministic Summary Structure for Update Data Streams
We present deterministic sub-linear space algorithms for problems over update data streams, including, estimating frequencies of items and ranges, finding approximate frequent items and approximate φ-quantiles, estimating inner-products, constructing near-optimal B-bucket histograms and estimating entropy. We also present improved lower bound results for several problems over update data streams.
متن کاملcs . D S ] 1 7 Se p 20 06 CR - precis : A deterministic summary structure for update data streams
We present the CR-precis structure, that is a general-purpose, deterministic and sub-linear data structure for summarizing update data streams. The CR-precis structure yields the first deterministic sub-linear space/time algorithms for answering a variety of fundamental queries over update streams, such as, (a) point queries, (b) range queries, (c) finding approximate frequent items, (d) findin...
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متن کاملar X iv : c s / 06 09 03 2 v 1 [ cs . D S ] 7 S ep 2 00 6 CR - precis : A deterministic summary structure for update data streams
We present the CR-precis structure, that is a general-purpose, deterministic and sub-linear data structure for summarizing update data streams. The CR-precis structure yields the first deterministic sub-linear space/time algorithms for update streams for answering a variety of fundamental stream queries, such as, (a) point queries, (b) range queries, (c) finding approximate frequent items, (d) ...
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a r t i c l e i n f o a b s t r a c t In this paper, we consider the problem of finding-approximate frequent items over a sliding window of size N. A recent work by Lee and Ting (2006) [7] solves the problem by giving an algorithm that supports O (1) query and update time, and uses O (1) space. Their query time and memory usage are essentially optimal, but the update time is not. We give a new ...
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