Results 21 to 30 of about 24,371,806 (309)
Context-aware adaptive data stream mining [PDF]
, 2009 In resource-constrained devices, adaptation of data stream processing to variations of data rates and availability of resources is crucial for consistency and continuity of running applications. However, to enhance and maximize the benefits of adaptation,
Zaslavsky, Arkady +9 more
core +1 more source
Homogeneous and heterogeneous distributed classification for pocket data mining [PDF]
, 2012 Pocket Data Mining (PDM) describes the full process of analysing data streams in mobile ad hoc distributed environments. Advances in mobile devices like smart phones and tablet computers have made it possible for a wide range of applications to run in ...
May, D. +18 more
core +1 more source
Ubiquitous data stream mining [PDF]
, 2004 The dissemination of data stream systems, wireless networks and mobile devices motivates the need for an efficient data analysis tool capable of gaining insights about these continuous data streams.
Zaslavsky, Arkady +5 more
core +2 more sources
Pocket data mining: towards collaborative data mining in mobile computing environments [PDF]
, 2010 Pocket Data Mining (PDM) is our new term describing collaborative mining of streaming data in mobile and distributed computing environments. With sheer amounts of data streams are now available for subscription on our smart mobile phones, the potential ...
Frederic Stahl +11 more
core +1 more source
Distributed classification for pocket data mining [PDF]
, 2011 Distributed and collaborative data stream mining in a mobile computing environment is referred to as Pocket Data Mining PDM. Large amounts of available data streams to which smart phones can subscribe to or sense, coupled with the increasing ...
Philip S. Yu +14 more
core +1 more source
Ontology of core data mining entities [PDF]
, 2014 In this article, we present OntoDM-core, an ontology of core data mining entities. OntoDM-core defines themost essential datamining entities in a three-layered ontological structure comprising of a specification, an implementation and an application ...
Dzeroski, S, Soldatova, L, Panov, P
core +1 more source
Hybridizing data stream mining and technical indicators in automated trading systems [PDF]
, 2011 Automated trading systems for financial markets can use data mining techniques for future price movement prediction. However, classifier accuracy is only one important component in such a system: the other is a decision procedure utilizing the prediction
Michael Mayo, Mayo, Michael
core +1 more source
Data stream analytics and mining in the cloud
4th IEEE International Conference on Cloud Computing Technology and Science Proceedings, 2012 Due to prevalent use of sensors and network monitoring tools, big volumes of data or “big data” today traverse the enterprise data processing pipelines in a streaming fashion. While some companies prefer to deploy their data processing infrastructures and services as private clouds, others completely outsource these services to public clouds. In either
Ari, Ismail +2 more
openaire +4 more sources
Concept Drift Detection in Data Stream Mining : A literature review
Journal of King Saud University: Computer and Information Sciences, 2022 In recent years, the availability of time series streaming information has been growing enormously. Learning from real-time data has been receiving increasingly more attention since the last decade.
Supriya Agrahari, Anil Kumar Singh
doaj +1 more source
eRules: a modular adaptive classification rule learning algorithm for data streams [PDF]
, 2012 Advances in hardware and software in the past decade allow to capture, record and process fast data streams at a large scale. The research area of data stream mining has emerged as a consequence from these advances in order to cope with the real time ...
Salvador, M. M. +10 more
core +1 more source