AnyNovel: detection of novel concepts in evolving data streams: An application for activity recognition

Abdallah, Zahraa and Gaber, Mohamed Medhat and Srinivasan, Bala and Krishnaswamy, Shonali (2016) AnyNovel: detection of novel concepts in evolving data streams: An application for activity recognition. Evolving Systems, 7 (2). p. 73. ISSN 1868-6478

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Abstract

A data stream is a flow of unbounded data that arrives continuously at high speed. In a dynamic streaming
environment, the data changes over the time while stream
evolves. The evolving nature of data causes essentially the
appearance of new concepts. This novel concept could be
abnormal such as fraud, network intrusion, or a sudden
fall. It could also be a new normal concept that the system
has not seen/trained on before. In this paper we propose,
develop, and evaluate a technique for concept evolution in
evolving data streams. The novel approach continuously
monitors the movement of the streaming data to detect
any emerging changes. The technique is capable of detecting the emergence of any novel concepts whether they are normal or abnormal. It also applies a continuous and active learning for assimilating the detected concepts in real time. We evaluate our approach on activity recognition domain as an application of evolving data streams. The study of the novel technique on benchmarked datasets showed its efficiency
in detecting new concepts and continuous adaptation
with low computational cost.

Item Type: Article
Uncontrolled Keywords: Stream mining · Concept evolution · Activity recognition · Continuous learning · Active learning · Novelty detection
Subjects: G400 Computer Science
Divisions: Faculty of Computing, Engineering and the Built Environment
Faculty of Computing, Engineering and the Built Environment > School of Computing and Digital Technology
Faculty of Computing, Engineering and the Built Environment > School of Computing and Digital Technology > Enterprise Systems
UoA Collections > UoA11: Computer Science and Informatics
Depositing User: $ Ian McDonald
Date Deposited: 25 Jan 2017 15:42
Last Modified: 09 Aug 2017 14:41
URI: http://www.open-access.bcu.ac.uk/id/eprint/3825

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