Finding persistent items in data streams
WebPersistent item mining is a special case of frequent item mining, which only counts once when an item occurs repeatedly over a measurement period. This study focuses on the problem of finding persistent items in the network-wide view. For an item, its occurrence frequency is the number of timeslots in which it appears. Webpersistent items. Persistent item mining finds applications in a variety of settings such as network security and click-frauddetection. Fornetworksecurity,persistentitemmin-ingcanbeusedtodetectstealthyDDoSattacks,wherean …
Finding persistent items in data streams
Did you know?
WebFinding persistent items in data streams Article Nov 2016 Haipeng Dai Muhammad Shahzad Alex X. Liu Yuankun Zhong Frequent item mining, which deals with finding items that occur frequently... WebFinding persistent items in data streams. H Dai, M Shahzad, AX Liu, Y Zhong. Proceedings of the VLDB Endowment 10 (4), 289-300, 2016. 64: 2016: Minimizing transient congestion during network update in data centers. J Zheng, H Xu, G Chen, H Dai. Proceedings of the 2014 CoNEXT on Student Workshop, 4-6, 2014. 63:
WebAug 13, 2024 · 4.2.1 Finding persistent items. Prior art In this paper we use the definition of persistent items from . Given a data stream \({\mathcal {S}}\) consisting of \({\mathcal {T'}}\) continuous equally sized measurement periods (periods for short), if an item e occurs in x periods, then x is the occurrence of e. If an item appears many times but ... 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 9, 2024 · A data item is called persistent if it occurs in all the epochs, where occurrence refers to an event that an item appears at least once within the considered … 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 …
WebSep 1, 2024 · Finding top- 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.
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... chia tai feedmill pte ltdWebFinding 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 ... chia s wifi iphoneWebMay 4, 2024 · 1.1 Background and motivation. Determining the number of distinct items, namely cardinality, is an important issue in many network applications, such as traffic management [7, 10], anomaly detection, etc.Many database applications, such as database query optimization [], require fast and accurate estimation of cardinality as well.There are … chiataigroup.comWebNov 1, 2016 · In this paper, we address the fundamental problem of finding persistent items in a given data stream during a given period of time at any given observation point. We … google ai corporate actionsWebpersistent items in a data stream. We divide the whole time interval into epochs, index from 0 to −1. A data item is called persistent if it occurs in all the epochs, where … chia tab trong wordWebNanjing University - Cited by 119 - Database - Data stream ... Finding persistent items in distributed datasets. H Dai, M Li, AX Liu, J Zheng, G Chen. IEEE/ACM Transactions on Networking 28 (1), 1-14, 2024. 39: 2024: Identifying and estimating persistent items in … chia taco georgetownWebfrequent 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]. chia tai bright global hk company limited