Exploring Term Networks for Semantic Search over RDF Knowledge Graphs

TitleExploring Term Networks for Semantic Search over RDF Knowledge Graphs
Publication TypeConference Proceedings
Year of Publication2016
AuthorsEdgard Marx, Konrad Hoffner, Saeedeh Shekarpour, Axel-Cyrille Ngonga Ngomo, Jens Lehmann, Sören Auer
EditorEmmanouel Garoufallou, Imma Subirats Coll, Armando Stellato, Jane Greenberg
Conference NameMetadata and Semantics Research: 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings
Pagination249–261
Date Published04/2016
PublisherSpringer International Publishing
Conference LocationCham
ISBN Number978-3-319-49157-8
KeywordsKnowledge graphs, rdf, Semantic Search
Abstract

Information retrieval approaches are considered as a key technology to empower lay users to access the Web of Data. A large number of related approaches such as Question Answering and Semantic Search have been developed to address this problem. While Question Answering promises more accurate results by returning a specific answer, Semantic Search engines are designed to retrieve the best top- KK ranked resources. In this work, we propose *path, a Semantic Search approach that explores term networks for querying RDF knowledge graphs. The adequacy of the approach is evaluated employing benchmark datasets against state-of-the-art Question Answering as well as Semantic Search systems. The results show that *path achieves better F 11 -score than the currently best performing Semantic Search system.

DOI10.1007/978-3-319-49157-8_22
Full Text

Citation Format:
E. Marx, K. Hoffner, S. Shekarpour, A. N. Ngomo, J. Lehmann, S. Auer. (2016). Exploring Term Networks for Semantic Search over RDF Knowledge Graphs. (Eds.) Garoufallou, E., Coll, I., Stellato, A. & Greenberg, J. Metadata and Semantics Research 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings. Cham: Springer International Publishing Imprint Springer.