Ingo Feinerer

Privatdoz. Dipl.-Ing. Dr.rer.soc.oec. Dr.techn.

Role

Affiliated
Databases and Artificial Intelligence, E192-02

Contact

ingo.feinerer@tuwien.ac.at
vCard from TISS

Publications

Note: Due to the rollout of TU Wien’s new publication database, the list below may be slightly outdated. Once the migration is complete, everything will be up to date again.

2015

On the undecidability of the equivalence of second-order tuple generating dependencies / Feinerer, I., Pichler, R., Sallinger, E., & Savenkov, V. (2015). On the undecidability of the equivalence of second-order tuple generating dependencies. Information Systems, 48, 113–129. https://doi.org/10.1016/j.is.2014.09.003 / Projects: HINT, SEE

2014

Numeric semantics of class diagrams with multiplicity and uniqueness constraints / Salzer, G., & Feinerer, I. (2014). Numeric semantics of class diagrams with multiplicity and uniqueness constraints. Software and Systems Modeling, 13(3), 1167–1187. https://doi.org/10.1007/s10270-012-0294-4

2013

Efficient large-scale configuration via integer linear programming / Feinerer, I. (2013). Efficient large-scale configuration via integer linear programming. Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 27(1), 37–49. https://doi.org/10.1017/s0890060412000376
Beyond the schools of psychology 1: A digital analysis of Psychological Review, 1894-1903 / Green, C., Feinerer, I., & Burman, J. (2013). Beyond the schools of psychology 1: A digital analysis of Psychological Review, 1894-1903. Journal of the History of the Behavioral Sciences, 49(2), 167–189. http://hdl.handle.net/20.500.12708/155581
The textcat package for n-gram based text categorization in R / Hornik, K., Mair, P., Rauch, J., Geiger, W., Buchta, C., & Feinerer, I. (2013). The textcat package for n-gram based text categorization in R. Journal of Statistical Software, 52(6), 1–17. http://hdl.handle.net/20.500.12708/155579
Class Diagrams with Equated Association Chains / Feinerer, I., Salzer, G., & Sisel, T. (2013). Class Diagrams with Equated Association Chains. In 2013 International Symposium on Theoretical Aspects of Software Engineering. 7th International Symposium on Theoretical Aspects of Software Engineering, Birmingham, EU. https://doi.org/10.1109/tase.2013.35
UMAP: A Universal Layer for Schema Mapping Languages / Chertes, F., & Feinerer, I. (2013). UMAP: A Universal Layer for Schema Mapping Languages. In H. Decker, L. Lhotská, S. Link, J. Basl, & A. M. Tjoa (Eds.), Lecture Notes in Computer Science (pp. 349–363). Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-642-40173-2_28
Lossless Horizontal Decomposition with Domain Constraints on Interpreted Attributes / Feinerer, I., Guagliardo, P., & Franconi, E. (2013). Lossless Horizontal Decomposition with Domain Constraints on Interpreted Attributes. In G. Gottlob, G. Grasso, D. Olteanu, & C. Schallhart (Eds.), Big Data (pp. 77–91). Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-642-39467-6_10

2012

Numeric semantics of class diagrams with multiplicity and uniqueness constraints / Feinerer, I., & Salzer, G. (2012). Numeric semantics of class diagrams with multiplicity and uniqueness constraints. Software and Systems Modeling, 13(3), 1167–1187. https://doi.org/10.1007/s10270-012-0294-4
A tm Plug-In for Distributed Text Mining in R / Theußl, S., Feinerer, I., & Hornik, K. (2012). A tm Plug-In for Distributed Text Mining in R. Journal of Statistical Software, 51(5), 1–31. http://hdl.handle.net/20.500.12708/164399
Spherical k-Means Clustering / Hornik, K., Feinerer, I., Kober, M., & Buchta, C. (2012). Spherical k-Means Clustering. Journal of Statistical Software, 50(10), 1–22. http://hdl.handle.net/20.500.12708/164398
Towards hybrid techniques for efficient declarative configuration / Feinerer, I. (2012). Towards hybrid techniques for efficient declarative configuration. In Proceedings of the Workshop on Configuration at ECAI 2012 (pp. 27–30). http://hdl.handle.net/20.500.12708/54424
Configuration Repair via Flow Networks / Salzer, G., Feinerer, I., & Sisel, T. (2012). Configuration Repair via Flow Networks. In C. Li & A. Felfernig (Eds.), Lecture Notes in Computer Science (pp. 321–330). https://doi.org/10.1007/978-3-642-34624-8_37

2011

Content-based social network analysis of mailing lists / Bohn, A., Feinerer, I., Hornik, K., & Mair, P. (2011). Content-based social network analysis of mailing lists. R Journal, 3(1), 11–18. http://hdl.handle.net/20.500.12708/162199
Reducing Multiplicities in Class Diagrams / Feinerer, I., Salzer, G., & Sisel, T. (2011). Reducing Multiplicities in Class Diagrams. In Model Driven Engineering Languages and Systems (pp. 379–393). https://doi.org/10.1007/978-3-642-24485-8_27
On the Undecidability of the Equivalence of Second-Order Tuple Generating Dependencies / Feinerer, I., Pichler, R., Sallinger, E., & Savenkov, V. (2011). On the Undecidability of the Equivalence of Second-Order Tuple Generating Dependencies. In P. Barceló & V. Tannen (Eds.), CEUR Workshop Proceedings (p. 13). http://hdl.handle.net/20.500.12708/53693
Efficient configuration and verification of software product lines / Feinerer, I. (2011). Efficient configuration and verification of software product lines. In I. Schäfer, I. John, & K. Schmid (Eds.), Proceedings of the 15th International Software Product Line Conference on - SPLC ’11. ACM. https://doi.org/10.1145/2019136.2019193

2010

Computing Product Configurations via UML and Integer Linear Programming / Falkner, A., Feinerer, I., Salzer, G., & Schenner, G. (2010). Computing Product Configurations via UML and Integer Linear Programming. International Journal of Mass Customisation, 3(4), 351. https://doi.org/10.1504/ijmassc.2010.037650
Kernel-based machine learning for fast text mining in R / Karatzoglou, A., & Feinerer, I. (2010). Kernel-based machine learning for fast text mining in R. Computational Statistics & Data Analysis, 54(2), 290–297. https://doi.org/10.1016/j.csda.2009.09.023
Support Vector Machines for Large Scale Text Mining in R / Feinerer, I., & Karatzoglou, A. (2010). Support Vector Machines for Large Scale Text Mining in R. In Y. Lechevallier & G. Saporta (Eds.), Proceedings of COMPSTAT’2010 19th International Conference on Computational StatisticsParis France, August 22-27, 2010 Keynote, Invited and Contributed Papers (pp. 991–998). Physica. http://hdl.handle.net/20.500.12708/53342
A New SNA Centrality Measure Quantifying the Distance to the Nearest Center / Bohn, A., Theußl, S., Feinerer, I., Hornik, K., Mair, P., & Walchhofer, N. (2010). A New SNA Centrality Measure Quantifying the Distance to the Nearest Center. In H. Locarek-Junge & C. Weihs (Eds.), Studies in Classification, Data Analysis, and Knowledge Organization (pp. 579–586). Springer. https://doi.org/10.1007/978-3-642-10745-0_63
Analysis and Algorithms for Stemming Inversion / Feinerer, I. (2010). Analysis and Algorithms for Stemming Inversion. In P.-J. Cheng, M.-Y. Kan, W. Lam, & P. Nakov (Eds.), Information Retrieval Technology (pp. 290–299). Springer. https://doi.org/10.1007/978-3-642-17187-1_28

2009

A Comparison of Tools for Teaching Formal Software Verification / Feinerer, I., & Salzer, G. (2009). A Comparison of Tools for Teaching Formal Software Verification. Formal Aspects of Computing, 21(3), 293–301. https://doi.org/10.1007/s00165-008-0084-5
Nonparametric Distribution Analysis for Text Mining / Karatzoglou, A., Feinerer, I., & Hornik, K. (2009). Nonparametric Distribution Analysis for Text Mining. In Advances in Data Analysis, Data Handling and Business Intelligence (pp. 295–305). Springer. https://doi.org/10.1007/978-3-642-01044-6_27

2008

Text Mining Infrastructure in R / Feinerer, I., Hornik, K., & Meyer, D. (2008). Text Mining Infrastructure in R. Journal of Statistical Software, 25(5), 54. http://hdl.handle.net/20.500.12708/170772
Fast text mining using kernels in R / Feinerer, I., & Karatzoglou, A. (2008). Fast text mining using kernels in R. In COMPSTAT 2008-Proceedings in Computational Statistics (p. 8). http://hdl.handle.net/20.500.12708/52445
Solving Practical Configuration Problems using UML / Falkner, A., Feinerer, I., Salzer, G., & Schenner, G. (2008). Solving Practical Configuration Problems using UML. In Proceedings of ECAI 2008 Workshop on Configuration Systems (p. 6). http://hdl.handle.net/20.500.12708/52363
Text Mining of Supreme Administrative Court Jurisdictions / Feinerer, I., & Hornik, K. (2008). Text Mining of Supreme Administrative Court Jurisdictions. In Data Analysis, Machine Learning and Applications (pp. 569–576). Springer. https://doi.org/10.1007/978-3-540-78246-9_67

2007

A formal treatment of UML class diagrams as an efficient method for configuration management / Feinerer, I. (2007). A formal treatment of UML class diagrams as an efficient method for configuration management [Dissertation, Technische Universität Wien]. reposiTUm. https://resolver.obvsg.at/urn:nbn:at:at-ubtuw:1-14264
Consistency and Minimality of UML Class Specifications with Multiplicities and Uniqueness Constraints / Salzer, G., & Feinerer, I. (2007). Consistency and Minimality of UML Class Specifications with Multiplicities and Uniqueness Constraints. In J. He & J. Sanders (Eds.), Proceedings 1st IEEE/IFIP International Symposium on Theoretical Aspects of Software Engineering (pp. 411–420). http://hdl.handle.net/20.500.12708/52120

2006

Automated Tools for Teaching Formal Software Verification / Feinerer, I., & Salzer, G. (2006). Automated Tools for Teaching Formal Software Verification. In P. Boca (Ed.), Proceedings of Teaching Formal Methods 2006 (p. 5). BCS. http://hdl.handle.net/20.500.12708/51752

2005

Formal program verification : a comparison of selected tools and their theoretical foundations / Feinerer, I. (2005). Formal program verification : a comparison of selected tools and their theoretical foundations [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://resolver.obvsg.at/urn:nbn:at:at-ubtuw:1-12860

Supervisions