Finding persistent items in data streams
WebThis paper addresses the fundamental problem of finding persistent items and estimating the number of times each persistent item occurred in a given data stream during a …
Finding persistent items in data streams
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WebA persistent staging table records the full history of change of a source table or query. The source could a source table, a source query, or another staging, view or materialized … WebTo find periodic items in data streams, a baseline solution consists of many Bloom filters [20] and a Space-Saving [21]. These Bloom filters are used to record the historic appearances of items, and the Space-Saving is used to record top-K frequent items with the same intervals.
WebFinding Persistent Items in Data Streams Haipeng Dai, Muhammad Shahzad, Alex X. Liu, Yuankun Zhong Download: ICDCS '17: Fast and Accurate Tracking of Population Dynamics in RFID Systems Muhammad Shahzad, Alex X. Liu Acceptance rate: 16.9% Download: 2016. IEEE TMC '16: WebMay 2, 2024 · Persistent Items Tracking in Large Data Streams Based on Adaptive Sampling 10.1109/INFOCOM48880.2024.9796709 Conference: IEEE INFOCOM 2024 - …
WebJan 5, 2005 · This work presents a 1-pass algorithm for estimating the most frequent items in a data stream using limited storage space, which achieves better space bounds than the previously known best algorithms for this problem for several natural distributions on the item frequencies. 1,666 Highly Influential PDF WebTo find periodic items in real time, we propose a novel sketch, PeriodicSketch, aiming to accurately record top-Kperiodic items. To the best of our knowledge, this is the first …
WebNov 1, 2024 · In a data stream composed of an ordered sequence of data items, persistent items refer to those persisting to occur over a long timespan. Compared with ordinary items, persistent...
WebMay 5, 2024 · Tracking persistent items is an important and pivotal functionality for many networking and computing applications as persistent items, though not necessarily contributing significantly to the data volume, may convey valuable information on the data pattern about the stream. does etrade withhold taxesWebFinding top-k items in data streams is a fundamental problem in data mining. Existing algorithms that can achieve unbiased estimation suffer from poor accuracy. ... finding top-k frequent items, finding top-k heavy changes, finding top-k persistent items, and finding top-k Super-Spreaders. We theoretically prove that WavingSketch can provide ... f1 new motorsWebNov 9, 2024 · In a data stream composed of an ordered sequence of data items, persistent items refer to those persisting to occur over a long timespan. Compared with ordinary items, persistent ones, though not necessarily occurring more frequently, typically convey more valuable information. does etrade have money market accountsWebApr 11, 2024 · Finding top-k persistent items is a new issue, and has attracted increasing attention in recent years. In practice, users often want to know which items are significant, i.e., not only frequent but also persistent. No prior art can address both of the above two issues at the same time. does etrade have something like thinkorswimWebNov 1, 2016 · A simple persistence heuristic was proposed in [9]: an item in a data stream is considered persistent if it occurs at least once in a large number of predefined, … f1 new orleans street circuit usWebpersistent items. Persistent item mining finds applications in a variety of settings such as network security and click-frauddetection. Fornetworksecurity,persistentitemmin-ingcanbeusedtodetectstealthyDDoSattacks,wherean … does etsy accept afterpayWebfrequent items in data streams have been well studied by the research community [1]–[6]. Sketches, as a kind of proba-bilistic data structures, have gained widespread acceptance for these tasks because they can well handle large-scale and high-speed data streams with limited memory overhead and small errors [7]–[10]. does etrade offer forex trading