Exploiting semantics from ontologies and shared annotations to find patterns in annotated linked open data

CEUR Workshop Proceedings

Volumn 1116, Issue , 2013, Pages 15-26

  Palma, Guillermo ^a   Vidal, Maria Esther ^a   Raschid, Louiqa ^b   Thor, Andreas ^c  

^a UNIVERSIDAD SIMÓN BOLÍVAR   (Venezuela)

^b UNIVERSITY OF MARYLAND   (United States)

^c UNIVERSITY OF LEIPZIG   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

CLUSTERING ALGORITHMS;

ANNOTATED DATASETS; CONTROLLED VOCABULARY TERMS; DOMAIN EXPERTS; DOMAIN SEMANTICS; EVALUATION RESULTS; LINKED OPEN DATUM;

SEMANTIC WEB;

EID: 84921916916     PISSN: 16130073     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (13)

1. S. Belongie, J. Malik, and J. Puzicha. Shape matching and object recognition using shape contexts. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 24(4):509-522, 2002.
2. J. Benik, C. Chang, L. Raschid, M. E. Vidal, G. Palma, and A. Thor. Finding cross genome patterns in annotation graphs. In Proceedings of Data Integration in the Life Sciences (DILS), 2012.
3. S. Bhagwani, S. Satapathy, and H. Karnick. Semantic textual similarity using maximal weighted bipartite graph matching. In Proceedings of the First Joint Conference on Lexical and Computational Semantics-Volume 1: Proceedings of the main conference and the shared task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation, pages 579-585. Association for Computational Linguistics, 2012.
4. W. W. Cohen, P. D. Ravikumar, and S. E. Fienberg. A comparison of string distance metrics for name-matching tasks. In IIWeb, pages 73-78, 2003.
5. D. J. Cook and L. B. Holder. Mining graph data. Wiley-Blackwell, 2007.
6. M. A. Jaro. Probabilistic linkage of large public health data files. Statistics in Medicine, pages 491-498, 1995.
7. B. McInnes, T. Pedersen, and S. Pakhomov. Umls-interface and umls-similarity : Open source software for measuring paths and semantic similarity. Proceedings of the AMIA Symposium, pages 431-435, 2009.
8. G. Palma, M.-E. Vidal, E. Haag, L. Raschid, and A. Thor. Measuring relatedness between scientific entities in annotation datasets. Technical report, University of Maryland. UMIACS Technical Report, 2013.
9. V. Pekar and S. Staab. Taxonomy learning-factoring the structure of a taxonomy into a semantic classification decision. In COLING, 2002.
10. L. Raschid, G. Palma, M.-E. Vidal, and A. Thor. Exploration using signatures in annotation graph datasets. Technical report, University of Maryland. UMIACS Technical Report, 2013.
11. Y. Shavitt, E. Weinsberg, and U. Weinsberg. Estimating peer similarity using distance of shared files. In International workshop on peer-to-peer systems (IPTPS), volume 104, 2010.
12. C. Shi, X. Kong, P. S. Yu, S. Xie, and B. Wu. Relevance search in heterogeneous networks. In EDBT, pages 180-191, 2012.
13. Y. Sun, J. Han, X. Yan, P. S. Yu, and T.Wu. Pathsim: Meta path-based top-k similarity search in heterogeneous information networks. PVLDB, 4(11):992-1003, 2011.