Publications

Export 186 results:
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z 
Ontology Alignment
K. Sengupta, Hitzler, P., and Janowicz, K., Revisiting default description logics – and their role in aligning ontologies, in Semantic Technology, 4th Joint International Conference, JIST 2014, Chiang Mai, Thailand, 2014, vol. 8943, pp. 3-18.PDF icon 2014-Kunal-defaults.pdf (308.62 KB)
M. Cheatham and Hitzler, P., Conference v2.0: An uncertain version of the OAEI Conference benchmark, in 13th International Semantic Web Conference (ISWC 2014), Riva del Garda, Italy, 2014, vol. 8797, pp. 148-163.PDF icon iswc14-Michelle-conferenceV2.pdf (347.31 KB)
ontology
C. Shimizu, Eberhart, A., Karima, N., Hirt, Q., Krisnadhi, A., and Hitzler, P., A Method for Automatically Generating Schema Diagrams for OWL Ontologies, in 1st Iberoamerican Knowledge Graph and Semantic Web Conference (KGSWC), Villa Clara, Cuba, 2019.PDF icon paper.pdf (386.54 KB)
OAEI
M. Cheatham and Hitzler, P., Conference v2.0: An uncertain version of the OAEI Conference benchmark, in 13th International Semantic Web Conference (ISWC 2014), Riva del Garda, Italy, 2014, vol. 8797, pp. 148-163.PDF icon iswc14-Michelle-conferenceV2.pdf (347.31 KB)
Nominal Schemas
D. Carral, Wang, C., and Hitzler, P., Towards an Efficient Algorithm to Reason over Description Logics Extended with Nominal Schemas, in Web Reasoning and Rule Systems - 7th International Conference, {RR} 2013, Mannheim, Germany, July 27-29, 2013. Proceedings, 2013, pp. 65–79.PDF icon Towards an Efficient Algorithm to Reason over Description Logics extended with Nominal Schemas.pdf (327.39 KB)
Neurobiology
B. Hammer, Hitzler, P., Maass, W., and Toussaint, M., 10302 Abstracts Collection - Learning paradigms in dynamic environments, Learning paradigms in dynamic environments. Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, Germany, Dagstuhl, Germany, 2010.
Neural-symbolic integration
B. Hammer, Hitzler, P., Maass, W., and Toussaint, M., 10302 Abstracts Collection - Learning paradigms in dynamic environments, Learning paradigms in dynamic environments. Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, Germany, Dagstuhl, Germany, 2010.
Neural Network
M. Labaf, Propositional rule extraction from neural networks under background knowledge, in Twelfth International Workshop on Neural-Symbolic Learning and Reasoning, 2017.PDF icon main.pdf (270.11 KB)
NeSy
A. Eberhart, Ebrahimi, M., Zhou, L., Shimizu, C., and Hitzler, P., Completion Reasoning Emulation for the Description Logic EL+, Proceedings of the AAAI 2020 Spring Symposium on Combining Machine Learning and Knowledge Engineering in Practice, vol. 2600. CEUR-WS.org, Stanford University, Palo Alto, California, USA, 2020.PDF icon paper5.pdf (1.89 MB)

Pages