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2015 | OriginalPaper | Buchkapitel

Web Stream Reasoning in Practice: On the Expressivity vs. Scalability Tradeoff

verfasst von : Stefano Germano, Thu-Le Pham, Alessandra Mileo

Erschienen in: Web Reasoning and Rule Systems

Verlag: Springer International Publishing

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Abstract

Advances in the Internet of Things and the Web of Data created huge opportunities for developing applications that can generate actionable knowledge out of streaming data. The trade-off between scalability and expressivity is a key challenge in this setting, and more investigation is required to identify what are the relevant features in optimizing this trade-off, and what role do they have in the optimization. In this paper we motivate the need for heuristics to design adaptive solutions and, following an empirical approach, we highlight some key concepts and ideas that can guide the design of heuristics for adaptive optimization of Web Stream Reasoning.

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Vorheriges Kapitel A Rule-based Framework for Creating Instance Data from OpenStreetMap

Nächstes Kapitel A Procedure for an Event-Condition-Transaction Language

Note that in ASP, the expressivity of the language is strictly related to the computational complexity, therefore we refer to expressivity and (computational) complexity interchangeably throughout the paper.

In this paper we only consider non-overlapping windows. For overlapping windows, the formula \( T_\omega (S, W) \) should hold also when duplicating events in overlapping parts.

Note that this is different from the total processing time, which includes the time required for query processing (first tier). In this paper, we mainly focus on the reasoning time only, relying on the extensive evaluation of query processing engines for the query processing time [1].

Note that this is different from the streaming size.

In the current implementation we evaluate criticality mainly based on how close an event is to the user location, and how fast is the user moving. In future work we plan to extend this contextual characterization to consider not only location but also other features such as the user transportation type, user’s health condition etc.

Algorithms to perform such splits are under investigation and will be the subject of future work.

Note that our goal is not to find the minimum, we just want to find one split.

Note that this assumption needs to be formally characterized and more investigation is ongoing in this direction.

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Calbimonte, J.-P., Corcho, O., Gray, A.J.G.: Enabling ontology-based access to streaming data sources. In: Patel-Schneider, P.F., Pan, Y., Hitzler, P., Mika, P., Zhang, L., Pan, J.Z., Horrocks, I., Glimm, B. (eds.) ISWC 2010, Part I. LNCS, vol. 6496, pp. 96–111. Springer, Heidelberg (2010) CrossRef

Baral, C.: Knowledge representation, reasoning and declarative problem solving. Cambridge University Press, Cambridge (2003) CrossRef

Gebser, M., Grote, T., Kaminski, R., Obermeier, P., Sabuncu, O., Schaub, T.: Stream reasoning with answer set programming: preliminary report. In: KR, vol. 12, pp. 613–617 (2012)

Gebser, M., Grote, T., Kaminski, R., Obermeier, P., Sabuncu, O., Schaub, T.: Answer set programming for stream reasoning. CoRR (2013)

Beck, H., Dao-Tran, M., Eiter, T., Fink, M.: Lars: A logic-based framework for analyzing reasoning over streams. In: AAAI (2015)

Do, T.M., Loke, S.W., Liu, F.: Answer set programming for stream reasoning. In: Butz, C., Lingras, P. (eds.) Canadian AI 2011. LNCS, vol. 6657, pp. 104–109. Springer, Heidelberg (2011) CrossRef

Mileo, A., Abdelrahman, A., Policarpio, S., Hauswirth, M.: StreamRule: a nonmonotonic stream reasoning system for the semantic web. In: Faber, W., Lembo, D. (eds.) RR 2013. LNCS, vol. 7994, pp. 247–252. Springer, Heidelberg (2013) CrossRef

Titel: Web Stream Reasoning in Practice: On the Expressivity vs. Scalability Tradeoff
verfasst von: Stefano Germano
Thu-Le Pham
Alessandra Mileo
Verlag: Springer International Publishing
Buch: Web Reasoning and Rule Systems
Print ISBN: 978-3-319-22001-7

Electronic ISBN: 978-3-319-22002-4

Copyright-Jahr: 2015
DOI: https://doi.org/10.1007/978-3-319-22002-4_9

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