Skip to main content
SpringerLink
Log in
SpringerLink
Log in

A Tour from Regularities to Exceptions

  • Chapter
  • First Online:
A Comprehensive Guide Through the Italian Database Research Over the Last 25 Years

Part of the book series: Studies in Big Data ((SBD,volume 31))

  • 1957 Accesses

Abstract

The enormous growth of information available in database systems has led to a significant development of techniques for knowledge discovery. At the heart of the knowledge discovery process is the application of data mining algorithms in charge of extracting hidden relationships among pieces of stored information. Information thus extracted from databases have widespread use in great many application domains and contexts.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. C. Aggarwal, Outlier Analysis (Springer, Berlin, 2013)

    Book  MATH  Google Scholar 

  2. L. Akoglu, H. Tong, D. Koutra, Graph based anomaly detection and description: a survey. Data Min. Knowl. Discov. 29(3), 626–688 (2015)

    Article  MathSciNet  Google Scholar 

  3. L. Akoglu, F. Bell, E. Müller, T.E. Senator (eds.), ACM KDD Workshop on Outlier Definition, Detection and Description on Demand, San Francisco, USA (2016)

    Google Scholar 

  4. F. Angiulli, Condensed nearest neighbor data domain description. IEEE Trans. Pattern Anal. Mach. Intell. 29(10), 1746–1758 (2007)

    Article  Google Scholar 

  5. F. Angiulli, Prototype-based domain description for one-class classification. IEEE Trans. Pattern Anal. Mach. Intell. 34(6), 1131–1144 (2012)

    Article  Google Scholar 

  6. F. Angiulli, F. Fassetti, An efficient method for outlier detection, in SEBD (2008), pp. 326–333

    Google Scholar 

  7. F. Angiulli, F. Fassetti, DOLPHIN: an efficient algorithm for mining distance-based outliers in very large datasets. ACM Trans. Know. Discov. Data 3(1), 4:1–4:57 (2009)

    Google Scholar 

  8. F. Angiulli, F. Fassetti, Distance-based outlier queries in data streams: the novel task and algorithms. Data Min. Knowl. Discov. 20(2), 290–324 (2010)

    Article  MathSciNet  Google Scholar 

  9. F. Angiulli, C. Pizzuti, Fast outlier detection in high dimensional spaces, in PKDD (2002), pp. 15–26

    Google Scholar 

  10. F. Angiulli, C. Pizzuti, Outlier mining in large high-dimensional data sets. IEEE Trans. Knowl. Data Eng. 17(2), 203–215 (2005)

    Article  MATH  Google Scholar 

  11. F. Angiulli, R. Ben-Eliyahu-Zohary, G. Ianni, L. Palopoli, Computational properties of metaquerying problems, in PODS (2000), pp. 237–244

    Google Scholar 

  12. F. Angiulli, G. Ianni, L. Palopoli, Metaquerying: proprietà e tecniche di implementazione, in SEBD (2000), pp. 317–330

    Google Scholar 

  13. F. Angiulli, G. Ianni, L. Palopoli, On the complexity of mining association rules, in SEBD (2001), pp. 177–184

    Google Scholar 

  14. F. Angiulli, R. Ben-Eliyahu-Zohary, G. Ianni, L. Palopoli, Computational properties of metaquerying problems. ACM Trans. Comput. Log. 4(2), 149–180 (2003)

    Article  MathSciNet  Google Scholar 

  15. F. Angiulli, G. Ianni, L. Palopoli, On the complexity of inducing categorical and quantitative association rules. Theor. Comput. Sci. 314(1–2), 217–249 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  16. F. Angiulli, S. Basta, C. Pizzuti, Distance-based detection and prediction of outliers. IEEE Trans. Knowl. Data Eng. 18(2), 145–160 (2006)

    Article  MATH  Google Scholar 

  17. F. Angiulli, F. Fassetti, L. Palopoli, Un metodo per la scoperta di proprietà inattese, in SEBD (2006), pp. 321–328

    Google Scholar 

  18. F. Angiulli, F. Fassetti, L. Palopoli, Detecting outlying properties of exceptional objects. ACM Trans. Database Syst. 34(1), 1–62 (2009)

    Article  Google Scholar 

  19. F. Angiulli, S. Basta, S. Lodi, C. Sartori, Distributed strategies for mining outliers in large data sets. IEEE Trans. Knowl. Data Eng. 25(7), 1520–1532 (2013)

    Article  Google Scholar 

  20. F. Angiulli, F. Fassetti, L. Palopoli, Discovering characterizations of the behavior of anomalous subpopulations. IEEE Trans. Knowl. Data Eng. 25(6), 1280–1292 (2013)

    Article  Google Scholar 

  21. F. Angiulli, S. Basta, S. Lodi, C. Sartori, GPU strategies for distance-based outlier detection. IEEE Trans. Parallel Distrib. Syst. 27(11), 3256–3268 (2016)

    Article  Google Scholar 

  22. F. Angiulli, F. Fassetti, E. Narvaez, Anomaly detection in networks with temporal information, in Discovery Science (Italy, Bari, 2016), pp. 359–375

    Google Scholar 

  23. F. Angiulli, F. Fassetti, G. Manco, L. Palopoli, Outlying property detection with numerical attributes. Data Min. Knowl. Discov. 31(1), 134–163 (2017)

    Article  MathSciNet  Google Scholar 

  24. M.R. Garey, D.S. Johnson, Computers and Intractability: A Guide to the Theory of NP-Completeness (W.H. Freeman, New York, 1979)

    MATH  Google Scholar 

  25. M. Gupta, J. Gao, C. Aggarwal, J. Han, Outlier detection for temporal data: a survey. IEEE Trans. Knowl. Data Eng. 26(9), 2250–2267 (2014)

    Article  MATH  Google Scholar 

  26. E. Knorr, R. Ng, A unified notion of outliers: properties and computation, in KDD (1997), pp. 219–222

    Google Scholar 

  27. M. Lenzerini, L. Lepore, A. Poggi, Answering metaqueries over hi (OWL 2 QL) ontologies, in IJCAI, New York, USA (2016), pp. 1174–1180

    Google Scholar 

  28. L. Palopoli, D. Saccà, D. Ursino, DL\(_P\): a description logic for extracting and managing complex terminological and structural properties from database schemes. Inf. Syst. 24(5), 410–424 (1999)

    Article  Google Scholar 

  29. L. Palopoli, D. Saccà, D. Ursino, Semi-automatic techniques for deriving interscheme properties from database schemes. Data Knowl. Eng. 30(4), 239–273 (1999)

    Article  MATH  Google Scholar 

  30. L. Palopoli, G. Terracina, D. Ursino, A graph-based approach for extracting terminological properties of elements of XML documents, in ICDE (IEEE Computer Society, Heidelberg, Germany, 2001), pp. 330–337

    Google Scholar 

  31. L. Palopoli, D. Saccà, G. Terracina, D. Ursino, A technique for deriving hyponymies and overlappings from database schemes. Data Knowl. Eng. 40(3), 285–314 (2002)

    Article  MATH  Google Scholar 

  32. L. Palopoli, D. Saccà, G. Terracina, D. Ursino, Uniform techniques for deriving similarities of objects and subschemes in heterogeneous databases. IEEE Trans. Knowl. Data Eng. 15(2), 271–294 (2003)

    Article  Google Scholar 

  33. L. Palopoli, G. Terracina, D. Ursino, Dike: a system supporting the semi-automatic construction of cooperative information systems from heterogeneous databases. Softw. Pract. Exp. 33(9), 847–884 (2003)

    Article  Google Scholar 

  34. L. Palopoli, G. Terracina, D. Ursino, Experiences using DIKE, a system for supporting cooperative information system and data warehouse design. Inf. Syst. 28(7), 835–865 (2003)

    Article  Google Scholar 

  35. L. Palopoli, G. Terracina, D. Ursino, A plausibility description logic for handling information sources with heterogeneous data representation formats. Ann. Math. Artif. Intell. 39(4), 385–430 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  36. L. Pontieri, D. Ursino, E. Zumpano, An approach for the extensional integration of data sources with heterogeneous representation formats. Data Knowl. Eng. 45(3), 291–331 (2003)

    Article  MATH  Google Scholar 

  37. L. Palopoli, D. Rosaci, G. Terracina, D. Ursino, A graph-based approach for extracting terminological properties from information sources with heterogeneous formats. Knowl. Inf. Syst. 8(4), 462–497 (2005)

    Article  Google Scholar 

  38. E. Rahm, P. Bernstein, A survey of approaches to automatic schema matching. VLDB J. 10(4), 334–350 (2001)

    Article  MATH  Google Scholar 

  39. D. Rosaci, G. Terracina, D. Ursino, An approach for deriving a global representation of data sources having different formats and structures. Knowl. Inf. Syst. 6(1), 42–82 (2004)

    Article  Google Scholar 

  40. G. Terracina, D. Ursino, A uniform methodology for extracting type conflicts and subscheme similarities from heterogeneous databases. Inf. Syst. 25(8), 527–552 (2000)

    Article  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. DIMES, University of Calabria, Calabria, Italy

    Fabrizio Angiulli, Fabio Fassetti & Luigi Palopoli

  2. DICEAM, University “Mediterranea” of Reggio Calabria, Calabria, Italy

    Domenico Ursino

Authors
  1. Fabrizio Angiulli
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Fabio Fassetti
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Luigi Palopoli
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Domenico Ursino
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Fabrizio Angiulli .

Editor information

Editors and Affiliations

  1. University of Calabria, Rende, Italy

    Sergio Flesca

  2. University of Calabria, Rende, Italy

    Sergio Greco

  3. ICAR-CNR, Rende, Italy

    Elio Masciari

  4. University of Calabria, Rende, Italy

    Domenico Saccà

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG

About this chapter

Cite this chapter

Angiulli, F., Fassetti, F., Palopoli, L., Ursino, D. (2018). A Tour from Regularities to Exceptions. In: Flesca, S., Greco, S., Masciari, E., Saccà, D. (eds) A Comprehensive Guide Through the Italian Database Research Over the Last 25 Years. Studies in Big Data, vol 31. Springer, Cham. https://doi.org/10.1007/978-3-319-61893-7_18

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-61893-7_18

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-61892-0

  • Online ISBN: 978-3-319-61893-7

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation