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Enhancing Stream Reasoning by Modeling the Importance of the Streaming Data

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자료유형E-Book
개인저자Yan, Rui.
단체저자명Rensselaer Polytechnic Institute. Computer Science.
서명/저자사항Enhancing Stream Reasoning by Modeling the Importance of the Streaming Data.
발행사항[S.l.] : Rensselaer Polytechnic Institute., 2018
발행사항Ann Arbor : ProQuest Dissertations & Theses, 2018
형태사항184 p.
소장본 주기School code: 0185.
ISBN9780438206533
일반주기 Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B.
Adviser: Deborah L. McGuinness.
요약The requirement to extract the hidden information out of the data stream is rising, however, traditional stream processing systems cannot meet this requirement as they are not designed to do so. This gives birth to the new research domain of str
요약Streaming data is boundless, enormous, and heterogeneous, which adds extra dimensions to the challenges of realizing the vision of stream reasoning, in addition to temporal constraints. A widely-adopted way to process the streams is via leveragi
요약Streaming data intrinsically has many different orderings, such as temporarily, precision, provenance, and trust, etc. If diverse data orderings can be utilized to model the data importance, stream reasoning can be benefited by being data-discri
요약Generally speaking, this dissertation delivers a conceptual model, and a set of infrastructure that can facilitate its general application in stream reasoning. Specifically, the first contribution is an innovative notion of semantic importance.
일반주제명Computer science.
언어영어
기본자료 저록Dissertation Abstracts International79-12B(E).
Dissertation Abstract International
대출바로가기http://www.riss.kr/pdu/ddodLink.do?id=T14997364

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