UMBC ebiquity UMBC ebiquity

Graph of Relations

January 1, 2010 - January 1, 2014

 

Users need better ways to explore linked open data collections and obtain information from it. Using SPARQL requires not only mastering its syntax and semantics but also understanding the RDF data model, the ontology used by the DBpedia, and URIs for entities of interest. Natural language question answering systems solve the problem, but these are still subjects of research. We are developing a compromise approach in which non-experts specify a graphical ``skeleton'' for a query and annotate it with freely chosen words, phrases and entity names. The combination reduces ambiguity and allows us to reliably produce an interpretation that can be translated into SPARQL. We have demonstrated the approach's feasibility for DBpedia with an implementation that performs well in an evaluation using queries from the 2011 QALD workshop. Key contributions are the robust methods that combine statistical association and semantic similarity to map user terms to the most appropriate classes and properties used in the DBpedia ontology.

Online demonstration

natural language processing, natural language, rdf, semantic web

OWL Tweet

Principal Faculty

  1. Tim Finin

Students

  1. Lushan Han

Faculty

  1. Anupam Joshi

Publications

2016

  1. A. L. Kashyap, L. Han, R. Yus, J. Sleeman, T. W. Satyapanich, S. R. Gandhi, and T. Finin, "Robust Semantic Text Similarity Using LSA, Machine Learning and Linguistic Resources", Article, Language Resources and Evaluation, March 2016, 2410 downloads.

2015

  1. Z. Syed, L. Han, M. M. Rahman, T. Finin, J. Kukla, and J. Yun, "Querying Large Linked Data Resources", InProceedings, 14th International Semantic Web Conference, October 2015, 1226 downloads.
  2. L. Han, T. Finin, A. Joshi, and D. Cheng, "Querying RDF Data with Text Annotated Graphs", InProceedings, Proceedings of the 27th International Conference on Scientific and Statistical Database Management, June 2015, 2603 downloads.
  3. Z. Syed, L. Han, M. M. Rahman, T. Finin, J. Kukla, and J. Yun, "UMBC_Ebiquity-SFQ: Schema Free Querying System", InProceedings, Proceedings of the Semantic Web Evaluation Challenge, ESWC, June 2015, 1266 downloads.

2014

  1. A. L. Kashyap, L. Han, R. Yus, J. Sleeman, T. W. Satyapanich, S. R. Gandhi, and T. Finin, "Meerkat Mafia: Multilingual and Cross-Level Semantic Textual Similarity systems", InProceedings, Proceedings of the 8th International Workshop on Semantic Evaluation, August 2014, 4218 downloads.
  2. L. Han, "Schema Free Querying of Semantic Data", PhdThesis, University of Maryland, Baltimore County, August 2014, 1673 downloads.

2013

  1. L. Han, A. L. Kashyap, T. Finin, J. Mayfield, and J. Weese, "UMBC_EBIQUITY-CORE: Semantic Textual Similarity Systems", InProceedings, Proceedings of the Second Joint Conference on Lexical and Computational Semantics, June 2013, 3959 downloads.
  2. L. Han, T. Finin, P. McNamee, A. Joshi, and Y. Yesha, "Improving Word Similarity by Augmenting PMI with Estimates of Word Polysemy", Article, IEEE Transactions on Knowledge and Data Engineering (TKDE), June 2013, 2907 downloads.

2012

  1. L. Han, T. Finin, and A. Joshi, "Schema-Free Structured Querying of DBpedia Data", InProceedings, Proceedings of the 21st ACM Conference on Information and Knowledge Management (CIKM), August 2012, 1788 downloads.
  2. L. Han, T. Finin, and A. Joshi, "GoRelations: Towards an Intuitive Query System for RDF Data", TechReport, University of Maryland, Baltimore County, February 2012, 1489 downloads.

2011

  1. L. Han, T. Finin, and A. Joshi, "GoRelations: An Intuitive Query System for DBpedia", InProceedings, Proceedings of the Joint International Semantic Technology Conference, December 2011, 2602 downloads.
  2. L. Han, T. Finin, P. McNamee, A. Joshi, and Y. Yesha, "Improving Word Similarity by Augmenting PMI with Estimates of Word Polysemy", TechReport, University of Maryland, Baltimore County, June 2011.

2009

  1. L. Han, T. Finin, and Y. Yesha, "Finding Semantic Web Ontology Terms from Words", InProceedings, Proceedings of the Eigth International Semantic Web Conference, October 2009, 2390 downloads, 3 citations.

2008

  1. L. Han and T. Finin, "Predicting Appropriate Semantic Web Terms from Words", InProceedings, Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence, July 2008, 2525 downloads.

Presentation

  1. GoRelations: an Intuitive Query System for DBPedia (and LOD)
  2. Making the Semantic Web Easier to Use
  3. Making the Semantic Web Easier to Use for Sharing Science Data

Dataset

  1. UMBC webbase corpus

Demonstration

  1. Word and phrase similarity

Research Areas

  1. Language technology
  2. Machine learning
  3. Semantic Web
  4. Web based information systems

Assertions

  1. (Resource) UMBC webbase corpus is a dataset of (Project) Graph of Relations