Cited by 72Advanced Database Systems and QueriesData Mining Algorithms and ApplicationsData Management and Algorithms

The DOI matches its Crossref record.

Introducing uncertainty in complex event processing: model, implementation, and validation

Open access

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1007/s00607-014-0404-y

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Still being checked.

Research works printed but not linked: 39

  1. Adi A, Etzion O (2004) Amit—the situation manager. VLDB J 13(2):177–203. doi: 10.1007/s00778-003-0108-y · DOI
  2. Agrawal J, Diao Y, Gyllstrom D, Immerman N (2008) Efficient pattern matching over event streams. In: SIGMOD, pp 147–160. ACM, New York. doi: 10.1145/1376616.1376634 · DOI
  3. Aguilera MK, Strom RE, Sturman DC, Astley M, Chandra TD (1999) Matching events in a content-based subscription system. In: Proceedings of the eighteenth annual ACM symposium on principles of distributed computing, PODC ’99. ACM, New York, pp 53–61. doi: 10.1145/301308.301326 · DOI
  4. Anicic D, Fodor P, Rudolph S, Stuhmer R, Stojanovic N, Studer R (2010) A rule-based language for complex event processing and reasoning. In: Hitzler P, Lukasiewicz T (eds) Web reasoning and rule systems. Lecture notes in computer science, vol 6333. Springer, Berlin, pp 42–57 · DOI
  5. Anicic D, Fodor P, Rudolph S, Stuhmer R, Stojanovic N, Studer R (2011) Etalis: rule-based reasoning in event processing. In: Helmer S, Poulovassilis A, Xhafa F (eds) Reasoning in event-based distributed systems. Studies in computational intelligence, vol 347. Springer, Berlin, pp 99–124 · DOI
  6. Arasu A, Babu S, Widom J (2006) The CQL continuous query language: semantic foundations and query execution. VLDB J 15(2):121–142 · DOI
  7. Artikis A, Etzion O, Feldman Z, Fournier F (2012) Event processing under uncertainty. In: Proceedings of the 6th ACM international conference on distributed event-based systems, DEBS ’12, Berlin, Germany. ACM, New York, pp 32–43. http://doi.acm.org/10.1145/2335484.2335488 · DOI
  8. Babcock B, Babu S, Datar M, Motwani R, Widom J (2002) Models and issues in data stream systems. In: PODS. ACM, New York, pp 1–16 · DOI
  9. Biswas R, Thrun S, Fujimura K (2007) Recognizing activities with multiple cues. In: Workshop on human motion, pp 255–270 · DOI
  10. Brenna L, Demers A, Gehrke J, Hong M, Ossher J, Panda B, Riedewald M, Thatte M, White W (2007) Cayuga: a high-performance event processing engine. In: SIGMOD. ACM, New York, pp 1100–1102 · DOI
  11. Broda K, Clark K, Miller R, Russo A (2009) SAGE: a logical agent-based environment monitoring and control system. In: Tscheligi M, Ruyter B, Markopoulus P, Wichert R, Mirlacher T, Meschterjakov A, Reitberger W (eds) Ambient intelligence, Lecture Notes in Computer Science, vol 5859. Springer, Berlin, Heidelberg, pp 112–117. http://dx.doi.org/10.1007/978-3-642-05408-2_14 · DOI
  12. Chakravarthy S, Krishnaprasad V, Anwar E, Kim SK (1994) Composite events for active databases: semantics, contexts and detection. In: Proceedings of the 20th international conference on very large data bases, VLDB ’94. Morgan Kaufmann Publishers Inc., San Francisco, pp 606–617
  13. Cugola G, Margara A (2010) Tesla: a formally defined event specification language. In: DEBS, pp 50–61 · DOI
  14. Cugola G, Margara A (2012) Complex event processing with T-Rex. J Syst Softw 85(8):1709–1728. doi: 10.1016/j.jss.2012.03.056 · DOI
  15. Cugola G, Margara A (2012) Low latency complex event processing on parallel hardware. J Parallel Distrib Comput 72(2):205–218. doi: 10.1016/j.jpdc.2011.11.002 · DOI
  16. Cugola G, Margara A (2012) Processing flows of information: from data stream to complex event processing. ACM Comput Surv 44(3):15:1–15:62. doi: 10.1145/2187671.2187677 · DOI
  17. Demers AJ, Gehrke J, Hong M, Riedewald M, White WM (2006) Towards expressive publish/subscribe systems. In: EDBT, pp 627–644 · DOI
  18. Diao Y, Li B, Liu A, Peng L, Sutton C, Tran TTL, Zink M (2009 Capturing data uncertainty in high-volume stream processing. In: CIDR 2009, fourth biennial conference on innovative data systems research, Asilomar, CA, USA, 4–7 January 2009. Online proceedings
  19. Etzion O, Niblett P (2010) Event processing in action. Manning Publications Co., Greenwich
  20. Gyllstrom D, Agrawal J, Diao Y, Immerman N (2008) On supporting Kleene closure over event streams. In: ICDE, pp 1391–1393 · DOI
  21. Helaoui R, Niepert M, Stuckenschmidt H (2011) Recognizing interleaved and concurrent activities: a statistical-relational approach. In: PerCom, pp 1–9 · DOI
  22. Jensen F (1996) An introduction to Bayesian networks, vol 36. UCL Press, London
  23. Kembhavi A, Yeh T, Davis LS (2010) Why did the person cross the road (there)? Scene understanding using probabilistic logic models and common sense reasoning. ECCV 2:693–706
  24. Li G, Jacobsen HA (2005) Composite subscriptions in content-based publish/subscribe systems. In: Middleware. Springer-Verlag New York Inc, New York, pp 249–269 · DOI
  25. Luckham DC (2001) The power of events: an introduction to complex event processing in distributed enterprise systems. Addison-Wesley Longman Publishing Co., Inc., Boston
  26. Margara A (2012) Combining expressiveness and efficiency in a complex event processing middleware. PhD thesis, Politecnico di Milano
  27. Morariu VI, Davis LS (2011) Multi-agent event recognition in structured scenarios. In: CVPR, pp 3289–3296
  28. Mühl G, Fiege L, Pietzuch P (2006) Distributed event-based systems. Springer-Verlag New York, Inc., Secaucus
  29. Pietzuch PR, Shand B, Bacon J (2003) A framework for event composition in distributed systems. In: Proceedings of the ACM/IFIP/USENIX 2003 international conference on middleware. Middleware ’03. Springer-Verlag New York, Inc., New York, pp 62–82 · DOI
  30. Ré C, Letchner J, Balazinksa M, Suciu D (2008) Event queries on correlated probabilistic streams. In: Proceedings of the 2008 ACM SIGMOD international conference on management of data, SIGMOD ’08. ACM, New York, pp 715–728. doi: 10.1145/1376616.1376688 · DOI
  31. Richardson M, Domingos P (2006) Markov logic networks. Mach Learn 62(1–2):107–136 · DOI · Paper page
  32. Sanghai S, Domingos P, Weld D (2005) Learning models of relational stochastic processes. In: Machine learning: ECML 2005. Springer, Berlin, pp 715–723 · DOI
  33. Schultz-Møller NP, Migliavacca M, Pietzuch PR (2009) Distributed complex event processing with query rewriting. In: DEBS, pp 4:1–4:12 · DOI
  34. Srivastava U, Widom J (2004) Flexible time management in data stream systems. In: PODS ’04. ACM, New York, pp 263–274. doi: 10.1145/1055558.1055596 · DOI
  35. Tran SD, Davis LS (2008) Event modeling and recognition using Markov logic networks. ECCV 2:610–623
  36. Wang F, Liu P (2005) Temporal management of RFID data. In: VLDB. VLDB endowment, pp 1128–1139
  37. Wasserkrug S, Gal A, Etzion O (2005) A model for reasoning with uncertain rules in event composition systems. In: Proceedings of the 21st annual conference on uncertainty in artificial intelligence, pp 599–606
  38. Wasserkrug S, Gal A, Etzion O, Turchin Y Complex event processing over uncertain data. In: Proceedings of the second international conference on distributed event-based systems, DEBS ’08. ACM, New York, pp 253–264 (2008). doi: 10.1145/1385989.1386022 · DOI
  39. Wasserkrug S, Gal A, Etzion O, Turchin Y (2012) Efficient processing of uncertain events in rule-based systems. IEEE Trans Knowl Data Eng 24(1):45–58. doi: 10.1109/TKDE.2010.204 · DOI

Cited by

Sorted by citations

  • Prescriptive analytics: Literature review and research challenges

    Lepenioti, K., Bousdekis, A., Apostolou, D., & Mentzas, G. (2020) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2019.04.003 · Cited by 501

    “…attempts for coupling probabilistic logic and uncertainty into CEP engines in order to react to predictions about future events before they occur (Cugola, Margara, Matteucci, & Tamburrelli, 2015; Engel et al., 2012; Lee & Jung, 2017; Mousheimish, Taher, & Zeitouni, 2016; Wang, Cao, & Zhang,…”

See all 72

Metadata

Authors
Cugola, G., Margara, A., Matteucci, M., & Tamburrelli, G.
Affiliations
  • Politecnico di Milano (IT)
  • Vrije Universiteit Amsterdam (NL)
  • Università della Svizzera italiana (CH)
Corresponding author
Tamburrelli, Giordano
Venue
Computing
Published
2014-05-10
Volume
97
Issue
2
Pages
103-144
ISSN
  • 0010-485X (ISSN-L)
  • 1436-5057
OpenAlex
W2064352477
Cited by
72
References
0
Citations by year
2025: 1 · 2024: 2 · 2023: 2 · 2022: 3 · 2021: 6 · 2020: 5 · 2019: 10 · 2018: 15 · 2017: 9 · 2016: 8 · 2015: 9 · 2014: 2
FWCI
10.73
Type
journal article
Language
en
Open access
Locations
  • Computing (publishedVersion)
  • VU Research Portal (publishedVersion)
  • RERO DOC (Universität Bern) (submittedVersion)
  • Virtual Community of Pathological Anatomy (University of Castilla La Mancha) (submittedVersion, other-oa)
  • VU Research Portal (submittedVersion)
  • Data Archiving and Networked Services (DANS) (submittedVersion)
Topics
  • Physical Sciences › Computer Science › Information Systems › Advanced Database Systems and Queries
  • Physical Sciences › Computer Science › Information Systems › Data Mining Algorithms and Applications
  • Physical Sciences › Computer Science › Information Systems › Data Management and Algorithms
Keywords
complex event processing, uncertainty modeling, composite event detection, rule languages, error propagation

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Introducing uncertainty in complex event processing: model, implementation, and validation. https://app.cochat.ai/papers/10.1007/s00607-014-0404-y
The paper
Cugola, G., Margara, A., Matteucci, M., & Tamburrelli, G. (2015). Introducing uncertainty in complex event processing: model, implementation, and validation. Computing. https://doi.org/10.1007/s00607-014-0404-y