SINDBAD

To fully support the analysis of complex and structured data, new efficient computational methods  and suitable interfaces for data exploration have to be developed. Moreover, it is desirable to perform all tasks in the knowledge discovery process, from pre-processing to post-processing, on the basis of query languages. Inductive query languages should allow handling patterns/models as first-class objects, provide the right level of abstraction to the user (i.e., meaningful building blocks of data analysis), and emphasize the compositionality of data mining tasks. In a major development and implementation effort, we created a research prototype of a working inductive database, SINDBAD (Structured Inductive Database Development), to explore research topics in the context of data mining query languages and inductive databases. SINDBAD is built on top of a relational database management system, offers an SQL extension for data pre-processing, mining, and post-processing, and achieves closure by successive transformation of tables.

2010

Wicker, Jörg; Richter, Lothar; Kramer, Stefan

SINDBAD and SiQL: Overview, Applications and Future Developments Incollection

Džeroski, Sašo; Goethals, Bart; Panov, Panče (Ed.): Inductive Databases and Constraint-Based Data Mining, pp. 289-309, Springer New York, 2010, ISBN: 978-1-4419-7737-3.

Abstract | Links | BibTeX | Altmetric

2008

Wicker, Jörg; Brosdau, Christoph; Richter, Lothar; Kramer, Stefan

SINDBAD SAILS: A service architecture for inductive learning schemes Inproceedings

Proceedings of the First Workshop on Third Generation Data Mining: Towards Service-Oriented Knowledge Discovery, 2008.

Abstract | BibTeX

Wicker, Jörg; Richter, Lothar; Kessler, Kristina; Kramer, Stefan

SINDBAD and SiQL: An Inductive Database and Query Language in the Relational Model Inproceedings

Daelemans, Walter; Goethals, Bart; Morik, Katharina (Ed.): Machine Learning and Knowledge Discovery in Databases, pp. 690-694, Springer Berlin Heidelberg, 2008, ISBN: 978-3-540-87480-5.

Abstract | Links | BibTeX | Altmetric

Richter, Lothar; Wicker, Jörg; Kessler, Kristina; Kramer, Stefan

An Inductive Database and Query Language in the Relational Model Inproceedings

Proceedings of the 11th International Conference on Extending Database Technology: Advances in Database Technology, pp. 740–744, ACM, Nantes, France, 2008, ISBN: 978-1-59593-926-5.

Abstract | Links | BibTeX | Altmetric

2006

Kramer, Stefan; Aufschild, Volker; Hapfelmeier, Andreas; Jarasch, Alexander; Kessler, Kristina; Reckow, Stefan; Wicker, Jörg; Richter, Lothar

Inductive Databases in the Relational Model: The Data as the Bridge Inproceedings

Bonchi, Francesco; Boulicaut, Jean-François (Ed.): Knowledge Discovery in Inductive Databases, pp. 124-138, Springer Berlin Heidelberg, 2006, ISBN: 978-3-540-33292-3.

Abstract | Links | BibTeX | Altmetric


SINDBAD and SiQL: Overview, Applications and Future Developments

Jörg Wicker, Lothar Richter, Stefan Kramer (2010): SINDBAD and SiQL: Overview, Applications and Future Developments. In: Džeroski, Sašo; Goethals, Bart; Panov, Panče (Ed.): Inductive Databases and Constraint-Based Data Mining, pp. 289-309, Springer New York, 2010, ISBN: 978-1-4419-7737-3.

Read more

An Inductive Database and Query Language in the Relational Model

Lothar Richter, Jörg Wicker, Kristina Kessler, Stefan Kramer (2008): An Inductive Database and Query Language in the Relational Model. In: Proceedings of the 11th International Conference on Extending Database Technology: Advances in Database Technology, pp. 740–744, ACM, Nantes, France, 2008, ISBN: 978-1-59593-926-5.

Read more

Inductive Databases in the Relational Model: The Data as the Bridge

Stefan Kramer, Volker Aufschild, Andreas Hapfelmeier, Alexander Jarasch, Kristina Kessler, Stefan Reckow, Jörg Wicker, Lothar Richter (2006): Inductive Databases in the Relational Model: The Data as the Bridge. In: Bonchi, Francesco; Boulicaut, Jean-François (Ed.): Knowledge Discovery in Inductive Databases, pp. 124-138, Springer Berlin Heidelberg, 2006, ISBN: 978-3-540-33292-3.

Read more