Emir Muņoz
Emir Muņoz
Genesys Telecommunications Laboratories, Inc.
Geverifieerd e-mailadres voor genesys.com - Homepage
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Using linked data to mine RDF from wikipedia's tables
E Muņoz, A Hogan, A Mileo
Proceedings of the 7th ACM international conference on Web search and data …, 2014
552014
Triplifying Wikipedia’s Tables
E Muņoz, A Hogan, A Mileo
In Proceedings of the Linked Data for Information Extraction Workshop (LD4IE …, 2013
362013
Regularizing Knowledge Graph Embeddings via Equivalence and Inversion Axioms
P Minervini, L Costabello, E Muņoz, V Nováček, PY Vandenbussche
ECML/PKDD, 2017
182017
Facilitating prediction of adverse drug reactions by using knowledge graphs and multi-label learning models
E Muņoz, V Nováček, PY Vandenbussche
Briefings in bioinformatics 20 (1), 190-202, 2019
152019
Using drug similarities for discovery of possible adverse reactions
E Muņoz, V Nováček, PY Vandenbussche
AMIA Annual Symposium Proceedings 2016, 924, 2016
142016
Performance Analysis of Algorithms to Reason about XML Keys
F Ferrarotti, S Hartmann, S Link, M Marin, E Muņoz
Database and Expert Systems Applications, 101-115, 2012
92012
Mining cardinalities from knowledge bases
E Muņoz, M Nickles
International Conference on Database and Expert Systems Applications, 447-462, 2017
82017
On learnability of constraints from RDF data
E Muņoz
European Semantic Web Conference, 834-844, 2016
62016
A linked data-based decision tree classifier to review movies
S Aldarra, E Munoz
Know@ LOD, 2015
62015
DRETa: Extracting RDF from Wikitables
E Muņoz, A Hogan, A Mileo
In Demo Proceedings of the 12th International Semantic Web Conference (ISWC …, 2013
5*2013
Identifying Equivalent Relation Paths in Knowledge Graphs
SK Mohamed, E Muņoz, V Nováček, PY Vandenbussche
International Conference on Language, Data and Knowledge, 299-314, 2017
42017
Learning Content Patterns from Linked Data
E Muņoz
Linked Data for Information Extraction, 2014
42014
Soft Cardinality Constraints on XML Data
F Ferrarotti, S Hartmann, S Link, M Marin, E Muņoz
Web Information Systems Engineering - WISE 2013, 2013
42013
Loss Functions in Knowledge Graph Embedding Models
SK Mohamed, V Nováček, PY Vandenbussche, E Muņoz
DL4KG@ ESWC 2377, 1-10, 2019
32019
The Finite Implication Problem for Expressive XML Keys: Foundations, Applications, and Performance Evaluation
F Ferrarotti, S Hartmann, S Link, M Marin, E Muņoz
Transactions on Large-Scale Data and Knowledge-Centered Systems, 2013
32013
LODPeas: Like peas in a LOD (cloud)
A Hogan, E Muņoz, J Umbrich
In Proceedings of the Billion Triple Challenge 2012 (co-located with …, 2012
32012
ĩRaptor: A DOM-based system with appetite for hCard elements
E Muņoz, L Costabello, PY Vandenbussche
Linked Data for Information Extraction Challenge, 2014
22014
Embedding cardinality constraints in neural link predictors
E Muņoz, P Minervini, M Nickles
Proceedings of the 34th ACM/SIGAPP Symposium on Applied Computing, 2243-2250, 2019
12019
Statistical relation cardinality bounds in knowledge bases
E Muņoz, M Nickles
Transactions on Large-Scale Data-and Knowledge-Centered Systems XXXIX, 67-97, 2018
12018
A Hybrid Method for Rating Prediction Using Linked Data Features and Text Reviews.
S Yumusak, E Muņoz, P Minervini, E Dogdu, H Kodaz
(KNOW@ LOD/CoDeS)@ ESWC, 2016
12016
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Artikelen 1–20