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Definition
Stream reasoning refers to inference approaches and deduction mechanisms which are concerned with providing continuous inference capabilities over dynamic data. The paradigm shift from current batch-like approaches toward timely and scalable stream reasoning leverages the natural temporal order in data streams and applies windows-based processing to complex deduction tasks that go beyond continuous query processing such as those involving preferential reasoning, constraint optimization, planning, uncertainty, non-monotonicity, non-determinism, and solution enumeration.
Historical Background
We are witnessing an unprecedented shift in the available quantity and quality of data drawn from all aspects of our lives, opening tremendous new opportunities but also significant challenges for scalable decision analytics due to its dynamicity. This makes it harder to go from data to insightand support effective decision-making. Such...
Recommended Reading
Valle ED, Ceri S, van Harmelen F, Fensel D. It’s a streaming world! Reasoning upon rapidly changing information. IEEE Intell Syst. 2009;24:83–9.
Babcock B, Babu S, Datar M, Motwani R, Widom J. Models and issues in data stream systems. In: Proceedings of the Twenty-First ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems (PODS’02). New York: ACM; 2002. p. 1–16.
Arasu A, Babu S, Widom J. The CQL continuous query language: semantic foundations and query execution. VLDB J. 2006;15:121–42.
Phuoc DL, Nguyen-Mau HQ, Parreira JX, Hauswirth M. A middleware framework for scalable management of linked streams. J Web Sem. 2012;16:42–51.
Phuoc DL, Dao-Tran M, Parreira JX, Hauswirth M. A native and adaptive approach for unified processing of linked streams and linked data. In: International Semantic Web Conference; 2011. vol. 1, p. 370–88.
Barbieri DF, Braga D, Ceri S, Valle ED, Grossniklaus M. C-SPARQL: a continuous query language for RDF data streams. Int J Semantic Comput. 2010;4:3–25.
Wasserkrug S, Gal A, Etzion O, Turchin Y. Efficient processing of uncertain events in rule-based systems. IEEE Trans Knowl Data Eng. 2012;24;45–58.
Cugola G, Margara A. Processing flows of information: from data stream to complex event processing. ACM Comput Surv. 2012;44:15:1–15:62.
Valle ED, Schlobach S, Krötzsch M, Bozzon A, Ceri S, Horrocks I. Order matters! Harnessing a world of orderings for reasoning over massive data. Semantic Web. 2013;4:219–31.
Brewka G, Eiter T. Equilibria in heterogeneous nonmonotonic multi-context systems. In: AAAI; 2007. p. 385–90.
Ghanem TM, Hammad MA, Mokbel MF, Aref WG, Elmagarmid AK. Incremental evaluation of sliding-window queries over data streams. IEEE Trans Knowl Data Eng. 2007;19:57–72.
Tatbul N, Zdonik S. Window-aware load shedding for aggregation queries over data streams. In: Proceedings of the 32nd International Conference on Very Large Data Bases (VLDB’06). VLDB Endowment; 2006. p. 799–810.
Dantsin E, Eiter T, Gottlob G, Voronkov A. Complexity and expressive power of logic programming. ACM Comput Surv. 2001;33:374–425.
Arasu A, Cherniack M, Galvez EF, Maier D, Maskey A, Ryvkina E, Stonebraker M, Tibbetts R. Linear road: a stream data management benchmark. In: VLDB; 2004. p. 480–91.
Phuoc DL, Dao-Tran M, Pham MD, Boncz PA, Eiter T, Fink M. Linked stream data processing engines: facts and figures. In: International Semantic Web Conference; 2012. vol. 2, p. 300–12.
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Mileo, A., Dao-Tran, M., Eiter, T., Fink, M. (2017). Stream Reasoning. In: Liu, L., Özsu, M. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4899-7993-3_80715-1
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DOI: https://doi.org/10.1007/978-1-4899-7993-3_80715-1
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