Abstract
Linked Open Data (LOD) has a graph structure in which nodes are represented by Uniform Resource Identifiers (URIs), and thus LOD sets are connected and searched through different domains. In fact, however, 5% of the values are literal (string without URI) even in DBpedia, which is a de facto hub of LOD. Since the literal becomes a terminal node, and we need to rely on regular expression matching, we cannot trace the links in the LOD graphs during searches. Therefore, this paper proposes a method of identifying and aggregating literal nodes that have the same meaning in order to facilitate cross-domain search through links in LOD. The novelty of our method is that part of the LOD graph structure is regarded as a block image, and then image features of LOD are extracted. In experiments, we created about 30,000 literal pairs from a Japanese music category of DBpedia Japanese and Freebase, and confirmed that the proposed method correctly determines literal identity with F-measure of 99%.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Bizer, C., Heath, T., Berners-Lee, T.: Linked Data - The Story So Far. International Journal on Semantic Web and Information Systems (IJSWIS) 5(3), 1–22 (2009)
Obata, T., Sugiyama, T., Hoki, K., Ito, T.: Consultation Algorithm for Computer Shogi: Move Decisions by Majority. In: van den Herik, H.J., Iida, H., Plaat, A. (eds.) CG 2010. LNCS, vol. 6515, pp. 156–165. Springer, Heidelberg (2011)
Hoki, K., Kaneko, T.: The Global Landscape of Objective Functions for the Optimization of Shogi Piece Values with a Game-Tree Search. In: van den Herik, H.J., Plaat, A. (eds.) ACG 2011. LNCS, vol. 7168, pp. 184–195. Springer, Heidelberg (2012)
Volz, J., Bizer, C., Gaedke, M., Kobilarov, G.: Silk - A link discovery framework for the web of data. In: Proc. of 2nd Linked Data on the Web Workshop (LDOW). CEUR Workshop Proceedings, vol. 538 (2009)
Volz, J., Bizer, C., Gaedke, M., Kobilarov, G.: Discovering and maintaining links on the web of data. In: Bernstein, A., Karger, D.R., Heath, T., Feigenbaum, L., Maynard, D., Motta, E., Thirunarayan, K. (eds.) ISWC 2009. LNCS, vol. 5823, pp. 650–665. Springer, Heidelberg (2009)
Isele, R., Bizer, C.: Learning linkage rules using genetic programming. In: Proc. of 6th International Workshop on Ontology Matching (OM). CEUR Workshop Proceedings, vol. 814 (2011)
Sindice - The Semantic Web Index (2014), http://sindice.com/
Google Refine (in transition over to Open Refine) (2014), https://github.com/OpenRefine
Maali, F., Cyganiak, R., Peristeras, V.: Re-using Cool URIs: Entity Reconciliation Against LOD Hubs. In: Proc of 4th Linked Data on the Web Workshop (LDOW 2011). CEUR Workshop Proceedings, vol. 813 (2011)
Niu, X., Rong, S., Wang, H., Yu, Y.: An Effective Rule Miner for Instance Matching in a Web of Data. In: Proc. of 21st ACM International Conference on Information and Knowledge Management (CIKM), pp. 1085–1094 (2012)
Rong, S., Niu, X., Xiang, E.W., Wang, H., Yang, Q., Yu, Y.: A Machine Learning Approach for Instance Matching Based on Similarity Metrics. In: Cudré-Mauroux, P., Heflin, J., Sirin, E., Tudorache, T., Euzenat, J., Hauswirth, M., Parreira, J.X., Hendler, J., Schreiber, G., Bernstein, A., Blomqvist, E. (eds.) ISWC 2012, Part I. LNCS, vol. 7649, pp. 460–475. Springer, Heidelberg (2012)
Dai, W., Yang, Q., Xue, G., Yu, Y.: Boosting for transfer learning. In: Proc. of 24th International Conference on Machine Learning (ICML), pp. 193–200 (2007)
Hu, W., Chen, J., Cheng, G., Qu, Y.: Objectcoref & falcon-ao: results for oaei2010. In: Proc. of 5th International Workshop on Ontology Matching (OM). CEUR Workshop Proceedings, vol. 689 (2010)
Li, J., Tang, J., Li, Y., Luo, Q.: Rimom: A dynamic multistrategy ontology alignment framework. IEEE Transactions on Knowledge and Data Engineering 21(8), 1218–1232 (2009)
Castano, S., Ferrara, A., Montanelli, S., Varese, G.: Ontology and Instance Matching. In: Knowledge-Driven Multimedia Information Extraction and Ontology Evolution, pp. 167–195 (2011)
Apache Solr (2014), http://lucene.apache.org/solr/
Gunaratna, K., Thirunarayan, K., Jain, P., Sheth, A., Wijeratne, S.: A Statistical and Schema Independent Approach to Identify Equivalent Properties on Linked Data. In: Proc. of 9th International Conference on Semantic Systems (I-SEMANTICS), pp. 33–40 (2013)
Fujitsu Laboratories of Europe Limited: “Fujitsu Laboratories Develops Technology for Automatically Linking with Open Data throughout the World” (2014), http://www.fujitsu.com/global/news/pr/archives/month/2014/20140116-01.html
TAC KBP 2013 Entity Linking Track (2014), http://www.nist.gov/tac/2013/KBP/EntityLinking/index.html
Miao, Q., Lu, H., Zhang, S., Meng, Y.: Simple Yet Effective Method for Entity Linking in Microblog-Genre Text. In: Zhou, G., Li, J., Zhao, D., Feng, Y. (eds.) NLPCC 2013. CCIS, vol. 400, pp. 440–447. Springer, Heidelberg (2013)
Lowe, D.G.: Object recognition from local scale-invariant features. In: Proc. of 7th International Conference on Computer Vision (ICCV), vol. 2, pp. 1150–1157 (1999)
Li, Y., Bandar, Z.A., McLean, D.: An Approach for Measuring Semantic Similarity between Words Using Multiple Information Sources. IEEE Transactions on Knowledge and Data Engineering 15(4), 871–882 (2003)
Princeton University: WordNet: A lexical database for English (2014), http://wordnetweb.princeton.edu/perl/webwn
National Institute of Information and Communications Technology: Japanese WordNet (2014), http://nlpwww.nict.go.jp/wn-ja
National Institute of Informatics: DBpedia Japanese (2014), http://ja.dbpedia.org/sparql
OpenLink Software: OpenSearch (2014), http://lod.openlinksw.com/sparql/
Breiman, L.: Random Forests. Machine Learning 45(1), 5–32 (2001)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Kawamura, T., Nagano, S., Ohsuga, A. (2014). Literal Node Matching Based on Image Features toward Linked Data Integration. In: Ślȩzak, D., Schaefer, G., Vuong, S.T., Kim, YS. (eds) Active Media Technology. AMT 2014. Lecture Notes in Computer Science, vol 8610. Springer, Cham. https://doi.org/10.1007/978-3-319-09912-5_15
Download citation
DOI: https://doi.org/10.1007/978-3-319-09912-5_15
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-09911-8
Online ISBN: 978-3-319-09912-5
eBook Packages: Computer ScienceComputer Science (R0)