Finding it now: networked classifiers in real-time stream mining systems

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dc.citation.epage131en_US
dc.citation.spage87en_US
dc.contributor.authorDucasse, R.en_US
dc.contributor.authorTekin, Cemen_US
dc.contributor.authorvan der Schaaren_US
dc.contributor.editorBhattacharyya, S. S.
dc.contributor.editorDeprettere, Ed. F.
dc.contributor.editorLeupers, R.
dc.contributor.editorTakala, J.
dc.date.accessioned2019-05-17T07:04:46Z
dc.date.available2019-05-17T07:04:46Z
dc.date.issued2019en_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.description.abstractThe aim of this chapter is to describe and optimize the specifications of signal processing systems, aimed at extracting in real time valuable information out of large-scale decentralized datasets. A first section will explain the motivations and stakes and describe key characteristics and challenges of stream mining applications. We then formalize an analytical framework which will be used to describe and optimize distributed stream mining knowledge extraction from large scale streams. In stream mining applications, classifiers are organized into a connected topology mapped onto a distributed infrastructure. We will study linear chains and optimise the ordering of the classifiers to increase accuracy of classification and minimise delay. We then present a decentralized decision framework for joint topology construction and local classifier configuration. In many cases, accuracy of classifiers are not known beforehand. In the last section, we look at how to learn online the classifiers characteristics without increasing computation overhead. Stream mining is an active field of research, at the crossing of various disciplines, including multimedia signal processing, distributed systems, machine learning etc. As such, we will indicate several areas for future research and development.en_US
dc.description.provenanceSubmitted by Onur Emek (onur.emek@bilkent.edu.tr) on 2019-05-17T07:04:46Z No. of bitstreams: 1 Finding_It_Now_Networked_Classifiers_in_Real-Time_Stream_Mining_Systems.pdf: 1580270 bytes, checksum: 56a3dee86d0cf81c0c1eb43e9a679bb9 (MD5)en
dc.description.provenanceMade available in DSpace on 2019-05-17T07:04:46Z (GMT). No. of bitstreams: 1 Finding_It_Now_Networked_Classifiers_in_Real-Time_Stream_Mining_Systems.pdf: 1580270 bytes, checksum: 56a3dee86d0cf81c0c1eb43e9a679bb9 (MD5) Previous issue date: 2019en
dc.identifier.doi10.1007/978-3-319-91734-4_3en_US
dc.identifier.doi10.1007/978-3-319-91734-4en_US
dc.identifier.isbn9783319917337
dc.identifier.urihttp://hdl.handle.net/11693/51336
dc.language.isoEnglishen_US
dc.publisherSpringer, Chamen_US
dc.relation.ispartofHandbook of signal processing systemsen_US
dc.relation.isversionofhttps://doi.org/10.1007/978-3-319-91734-4_3en_US
dc.relation.isversionofhttps://doi.org/10.1007/978-3-319-91734-4en_US
dc.titleFinding it now: networked classifiers in real-time stream mining systemsen_US
dc.typeBook Chapteren_US

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