Publications

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dataset search
S. Lalithsena, Hitzler, P., Sheth, A., and Jain, P., “Automatic Domain Identification for Linked Open Data”, in 2013 IEEE/WIC/ACM International Conferences on Web Intelligence, WI 2013, Atlanta, GA, USA, 2013, pp. 205–212.PDF icon DomainIdentLOD-WI13.pdf (1.16 MB)
datalog
S. Rudolph, Krötzsch, M., and Hitzler, P., “Type-Elimination-Based Reasoning for the Description Logic SHIQbs using Decision Diagrams and Disjunctive Datalog”, Logical Methods in Computer Science, vol. 8, 2012.PDF icon type-elimination-2012.pdf (368.62 KB)
M. Krötzsch, Maier, F., Krisnadhi, A., and Hitzler, P., “A Better Uncle for OWL: Nominal Schemas for Integrating Rules and Ontologies”, in Proceedings of the 20th International Conference on World Wide Web, WWW 2011, Hyderabad, India, March 28 - April 1, 2011, 2011, pp. 645-654.PDF icon KroetzschMaierKrisnadhiHitzler-WWW11.pdf (406.28 KB)
Data models
A. Mahbub Uddin, Miraj, A. Al, Sarma, M. Sen, Das, A., and Gani, M. Manjurul, “Traditional Bengali Food Classification Using Convolutional Neural Network”, in 2021 IEEE Region 10 Symposium (TENSYMP), 2021, pp. 1-8.
data integration
C. Shimizu, Hitzler, P., Hirt, Q., Rehberger, D., Estrecha, S. Gonzalez, Foley, C., Sheill, A. M., Hawthorne, W., Mixter, J., Watrall, E., Carty, R., and Tarr, D., “The Enslaved Ontology: Peoples of the Historic Slave Trade”, Journal of Web Semantics, vol. 63, 2020.PDF icon (pdf) author version: The Enslaved Ontology (1020.25 KB)
Data complexity
S. Huang, Li, Q., and Hitzler, P., “Reasoning with Inconsistencies in Hybrid MKNF Knowledge Bases”, Logic Journal of the IGPL, vol. 21, pp. 263–290, 2013.PDF icon ljigpl-parahkmf-2013.pdf (225.39 KB)
D-SPARQ
R. Mutharaju, Sakr, S., Sala, A., and Hitzler, P., “D-SPARQ: Distributed, Scalable and Efficient RDF Query Engine”, in Proceedings of the ISWC 2013 Posters & Demonstrations Track, Sydney, Australia, 2013, vol. 1035, pp. 261–264.PDF icon dsparq-ISWC2013.pdf (210.38 KB)
Convolutional neural networks
A. Mahbub Uddin, Miraj, A. Al, Sarma, M. Sen, Das, A., and Gani, M. Manjurul, “Traditional Bengali Food Classification Using Convolutional Neural Network”, in 2021 IEEE Region 10 Symposium (TENSYMP), 2021, pp. 1-8.
S. Salam Aonty, Deb, K., Sarma, M. Sen, Dhar, P. Kumar, and Shimamura, T., “Multi-Person Pose Estimation Using Group-Based Convolutional Neural Network Model”, IEEE Access, vol. 11, pp. 42343-42360, 2023.
Convolutional Neural Network
A. Dalal, “Understanding CNN Hidden Neuron Activations using Concept Induction over Background Knowledge”, THE 23RD INTERNATIONAL SEMANTIC WEB CONFERENCE, ISWC 2024. 2024.PDF icon 2024_ISWC_doctoral.pdf (179.17 KB)
A. Mahbub Uddin, Miraj, A. Al, Sarma, M. Sen, Das, A., and Gani, M. Manjurul, “Traditional Bengali Food Classification Using Convolutional Neural Network”, in 2021 IEEE Region 10 Symposium (TENSYMP), 2021, pp. 1-8.
S. Salam Aonty, Deb, K., Sarma, M. Sen, Dhar, P. Kumar, and Shimamura, T., “Multi-Person Pose Estimation Using Group-Based Convolutional Neural Network Model”, IEEE Access, vol. 11, pp. 42343-42360, 2023.
Context theory
S. S. Sahoo, Bodenreider, O., Hitzler, P., Sheth, A., and Thirunarayan, K., “Provenance Context Entity (PaCE): Scalable Provenance Tracking for Scientific RDF Data”, in Scientific and Statistical Database Management, 22nd International Conference, SSDBM 2010, Heidelberg, Germany, 2010, vol. 6187, pp. 461–470.PDF icon PaCE-SSDBM2010.pdf (810.08 KB)
Concept Induction
A. Dalal, Rayan, R., Barua, A., Vasserman, E. Y., Sarker, K., and Hitzler, P., “On the Value of Labeled Data and Symbolic Methods for Hidden Neuron Activation Analysis”, in 18th International Conference on Neural-Symbolic Learning and Reasoning, NeSy 2024, 2024.PDF icon 2024_NeSy_CI.pdf (358.13 KB)
A. Dalal, Rayan, R., and Hitzler, P., “Error-margin Analysis for Hidden Neuron Activation Labels”, 18th International Conference on Neural-Symbolic Learning and Reasoning, NeSy 2024. Springer , 2024.PDF icon 2024_NeSy_CI_shortPaper.pdf (245.56 KB)

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