Abstract
Knowledge graphs are playing an increasingly important role for many search tasks such as entity search, question answering, etc. Although there are millions of entities and thousands of relations in many existing knowledge graphs such as Freebase and DBpedia, they are still far from complete. Previous approaches to complete knowledge graphs are either factor decomposition based methods or machine learning based ones. We propose a complementary approach that estimates the likelihood of a triple existing based on similarity measure of entities and some common semantic patterns of the entities. Such a way of triple estimation is very effective which exploits the semantic contexts of entities. Experimental results demonstrate that our model achieves significant improvements on knowledge graph completion compared with the state-of-art techniques.
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
References
Auer, S., Bizer, C., Kobilarov, G., Lehmann, J., Cyganiak, R., Ives, Z.G.: DBpedia: a nucleus for a web of open data. In: Aberer, K., et al. (eds.) ASWC 2007 and ISWC 2007. LNCS, vol. 4825, pp. 722–735. Springer, Heidelberg (2007)
Bollacker, K.D., Evans, C., Paritosh, P., Sturge, T., Taylor, J.: Freebase: a collaboratively created graph database for structuring human knowledge. In: Proceedings of the ACM SIGMOD International Conference on Management of Data, SIGMOD 2008, Vancouver, BC, Canada, 10–12 June 2008, pp. 1247–1250 (2008)
Bordes, A., Usunier, N., GarcÃa-Durán, A., Weston, J., Yakhnenko, O.: Translating embeddings for modeling multi-relational data. In: Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held 5–8 December 2013, Lake Tahoe, Nevada, United States, pp. 2787–2795 (2013)
Dong, X., Gabrilovich, E., Heitz, G., Horn, W., Lao, N., Murphy, K., Strohmann, T., Sun, S., Zhang, W.: Knowledge vault: a web-scale approach to probabilistic knowledge fusion. In: The 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2014, New York, NY, USA, 24–27 August 2014, pp. 601–610 (2014)
Drumond, L., Rendle, S., Schmidt-Thieme, L.: Predicting RDF triples in incomplete knowledge bases with tensor factorization. In: Proceedings of the ACM Symposium on Applied Computing, SAC 2012, Riva, Trento, Italy, 26–30 March 2012, pp. 326–331 (2012)
Franz, T., Schultz, A., Sizov, S., Staab, S.: TripleRank: ranking semantic web data by tensor decomposition. In: Bernstein, A., Karger, D.R., Heath, T., Feigenbaum, L., Maynard, D., Motta, E., Thirunarayan, K. (eds.) ISWC 2009. LNCS, vol. 5823, pp. 213–228. Springer, Heidelberg (2009)
Gangemi, A., Presutti, V.: Towards a pattern science for the semantic web. Semantic Web 1(1–2), 61–68 (2010)
Jeh, G., Widom, J.: Simrank: a measure of structural-context similarity. In: Proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 23–26 July 2002, Edmonton, Alberta, Canada, pp. 538–543 (2002)
Krompass, D., Nickel, M., Tresp, V.: Large-scale factorization of type-constrained multi-relational data. In: International Conference on Data Science and Advanced Analytics, DSAA 2014, Shanghai, China, 30 October–1 November 2014, pp. 18–24 (2014)
Lao, N., Mitchell, T.M., Cohen, W.W.: Random walk inference and learning in a large scale knowledge base. In: Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing, EMNLP 2011, 27–31 July 2011, John McIntyre Conference Centre, Edinburgh, UK, A meeting of SIGDAT, a Special Interest Group of the ACL, pp. 529–539 (2011)
Lin, Y., Liu, Z., Luan, H., Sun, M., Rao, S., Liu, S.: Modeling relation paths for representation learning of knowledge bases. In: Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, EMNLP 2015, Lisbon, Portugal, 17–21 September 2015, pp. 705–714(2015)
Lin, Y., Liu, Z., Sun, M., Liu, Y., Zhu, X.: Learning entity and relation embeddings for knowledge graph completion. In: Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 25–30 January 2015, Austin, Texas, USA, pp. 2181–2187 (2015)
Maccatrozzo, V., Ceolin, D., Aroyo, L., Groth, P.: A semantic pattern-based recommender. In: Presutti, V., et al. (eds.) SemWebEval 2014. CCIS, vol. 475, pp. 182–187. Springer, Heidelberg (2014)
Mikolov, T., Sutskever, I., Chen, K., Corrado, G.S., Dean, J.: Distributed representations of words and phrases and their compositionality. In: Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5–8, 2013, Lake Tahoe, Nevada, United States, pp. 3111–3119 (2013)
Miller, G.A.: Wordnet: a lexical database for English. Commun. ACM 38(11), 39–41 (1995)
Muggleton, S.: Inverse entailment and progol. New Gener. Comput. 13(3&4), 245–286 (1995)
Nickel, M., Tresp, V., Kriegel, H.: A three-way model for collective learning on multi-relational data. In: Proceedings of the 28th International Conference on Machine Learning, ICML 2011, Bellevue, Washington, USA, 28 June–2 July 2011, pp. 809–816 (2011)
Nickel, M., Tresp, V., Kriegel, H.: Factorizing YAGO: scalable machine learning for linked data. In: Proceedings of the 21st World Wide Web Conference 2012, WWW 2012, Lyon, France, 16–20 April 2012, pp. 271–280 (2012)
Quinlan, J.R., Cameron-Jones, R.M.: FOIL: a midterm report. In: Machine Learning: ECML-93, European Conference on Machine Learning, Vienna, Austria, 5–7 April 1993, pp. 3–20 (1993)
Raedt, L.D., Dehaspe, L.: Clausal discovery. Mach. Learn. 26(2–3), 99–146 (1997)
Socher, R., Chen, D., Manning, C.D., Ng, A.Y.: Reasoning with neural tensor networks for knowledge base completion. In: Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held 5–8 December 2013, Lake Tahoe, Nevada, United States, pp. 926–934 (2013)
Suchanek, F.M., Kasneci, G., Weikum, G.: Yago: a core of semantic knowledge. In: Proceedings of the 16th International Conference on World Wide Web, WWW 2007, Banff, Alberta, Canada, 8–12 May 2007, pp. 697–706 (2007)
Sun, Y., Han, J., Yan, X., Yu, P.S., Wu, T.: Pathsim: meta path-based top-k similarity search in heterogeneous information networks. PVLDB 4(11), 992–1003 (2011)
Tong, H., Faloutsos, C., Pan, J.: Fast random walk with restart and its applications. In: Proceedings of the 6th IEEE International Conference on Data Mining (ICDM 2006), 18–22 December 2006, Hong Kong, China, pp. 613–622 (2006)
Wang, Z., Zhang, J., Feng, J., Chen, Z.: Knowledge graph embedding by translating on hyperplanes. In: Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 27–31 July 2014, Québec City, Québec, Canada, pp. 1112–1119 (2014)
Acknowledgements
This work is supported by National Basic Research Program of China (973 Program) No. 2012CB316205, the National Science Foundation of China under grant (No. 61472426, 61170010, 61432006), the Fundamental Research Funds for the Central Universities, the Research Funds of Renmin University of China No. 14XNLQ06, and a gift by Tencent.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Zhang, X., Du, C., Li, P., Li, Y. (2016). Knowledge Graph Completion via Local Semantic Contexts. In: Navathe, S., Wu, W., Shekhar, S., Du, X., Wang, X., Xiong, H. (eds) Database Systems for Advanced Applications. DASFAA 2016. Lecture Notes in Computer Science(), vol 9642. Springer, Cham. https://doi.org/10.1007/978-3-319-32025-0_27
Download citation
DOI: https://doi.org/10.1007/978-3-319-32025-0_27
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-32024-3
Online ISBN: 978-3-319-32025-0
eBook Packages: Computer ScienceComputer Science (R0)