Abstract
Wikipedia Infoboxes are semi-structured data structures organized in an attribute-value fashion. Policies establish for each type of entity represented in Wikipedia the attribute names that the Infobox should contain in the form of a template. However, these requirements change over time and often users choose not to strictly obey them. As a result, it is hard to treat in an integrated way the history of the Wikipedia pages, making it difficult to analyze the temporal evolution of Wikipedia entities through their Infobox and impossible to perform direct comparison of entities of the same type. To address this challenge, we propose an approach to deal with the misalignment of the attribute names and identify clusters of synonymous Infobox attributes. Elements in the same cluster are considered as a temporal evolution of the same attribute. To identify the clusters we use two different distance metrics. The first is the co-occurrence degree that is treated as a negative distance, and the second is the co-occurrence of similar values in the attributes that are treated as a positive evidence of synonymy. We formalize the problem as a correlation clustering problem over a weighted graph constructed with attributes as nodes and positive and negative evidence as edges. We solve it with a linear programming model that shows a good approximation. Our experiments over a collection of Infoboxes of the last 13 years shows the potential of our approach.
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Notes
- 1.
https://en.wikipedia.org/wiki/Wikipedia:Statistics updated on 24 March 2019.
- 2.
Note a cleaning procedure has been applied to the input infoboxes to remove the “noise” generated by human mistakes.
References
Adar, E., Skinner, M., Weld, D.S.: Information arbitrage across multi-lingual Wikipedia. In: Proceedings of WSDM, pp. 94–103 (2009)
Agarwal, P., Strötgen, J.: Tiwiki: searching Wikipedia with temporal constraints. In: Proceedings of WWW, pp. 1595–1600 (2017)
Auer, S., Bizer, C., Kobilarov, G., Lehmann, J., Cyganiak, R., Ives, Z.G.: DBpedia: a nucleus for a web of open data. In: ISWC, pp. 722–735 (2007)
Bansal, N., Blum, A., Chawla, S.: Correlation clustering. Mach. Learn. 56(1–3), 89–113 (2004)
Bellahsene, Z., Bonifati, A., Rahm, E. (eds.): Schema Matching and Mapping. Data-Centric Systems and Applications. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-16518-4
Bernstein, P.A., Madhavan, J., Rahm, E.: Generic schema matching, ten years later. PVLDB 4(11), 695–701 (2011)
Bleifuß, T., Bornemann, L., Johnson, T., Kalashnikov, D.V., Naumann, F., Srivastava, D.: Exploring change - a new dimension of data analytics. PVLDB 12(2), 85–98 (2018)
Bleifuß, T., Bornemann, L., Kalashnikov, D.V., Naumann, F., Srivastava, D.: DBChEx: interactive exploration of data and schema change. In: Proceedings of CIDR (2019)
Bouma, G., Duarte, S., Islam, Z.: Cross-lingual alignment and completion of Wikipedia templates. In: Proceedings of the Workshop on Cross Lingual Information Access, pp. 21–29. Association for Computational Linguistics (2009)
Demaine, E.D., Emanuel, D., Fiat, A., Immorlica, N.: Correlation clustering in general weighted graphs. Theor. Comput. Sci. 361(2–3), 172–187 (2006)
Euzenat, J., Shvaiko, P.: Ontology Matching. Springer, Heidelberg (2007). https://doi.org/10.1007/978-3-540-49612-0
He, Y., Chakrabarti, K., Cheng, T., Tylenda, T.: Automatic discovery of attribute synonyms using query logs and table corpora. In: Proceedings of WWW, pp. 1429–1439 (2016)
Hoffart, J., Suchanek, F.M., Berberich, K., Weikum, G.: YAGO2: a spatially and temporally enhanced knowledge base from Wikipedia. Artif. Intell. 194, 28–61 (2013)
Rand, W.M.: Objective criteria for the evaluation of clustering methods. J. Am. Stat. Assoc. 66, 846–850 (1971)
Nguyen, T., Moreira, V., Nguyen, H., Nguyen, H., Freire, J.: Multilingual schema matching for wikipedia infoboxes. PVLDB 5(2), 133–144 (2011)
Rahm, E., Bernstein, P.A.: A survey of approaches to automatic schema matching. VLDB J. 10(4), 334–350 (2001)
Rinser, D., Lange, D., Naumann, F.: Cross-lingual entity matching and infobox alignment in Wikipedia. Inf. Syst. 38(6), 887–907 (2013)
Suchanek, F.M., Kasneci, G., Weikum, G.: YAGO: a large ontology from wikipedia and wordnet. J. Web Semant. 6(3), 203–217 (2008)
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Sottovia, P., Paganelli, M., Guerra, F., Velegrakis, Y. (2019). Finding Synonymous Attributes in Evolving Wikipedia Infoboxes. In: Welzer, T., Eder, J., Podgorelec, V., Kamišalić Latifić, A. (eds) Advances in Databases and Information Systems. ADBIS 2019. Lecture Notes in Computer Science(), vol 11695. Springer, Cham. https://doi.org/10.1007/978-3-030-28730-6_11
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DOI: https://doi.org/10.1007/978-3-030-28730-6_11
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