Abstract
This paper deals with the integration of data extracted from the web into an existing data warehouse indexed by a domain ontology. We are specially interested in data tables extracted from scientific publications found on the web. We propose a way to annotate data tables from the web according to a given domain ontology. In this paper we present the different steps of our annotation process. The columns of a web data table are first segregated according to whether they represent numeric or symbolic data. Then, we annotate the numeric (resp.symbolic) columns with their corresponding numeric (resp. symbolic) type found in the ontology. Our approach combines different evidences from the column contents and from the column title to find the best corresponding type in the ontology. The relations represented by the web data table are recognized using both the table title and the types of the columns that were previously annotated. We give experimental results of our annotation process, our application domain being food microbiology.
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Buche, P., Dervin, C., Haemmerlé, O., Thomopoulos, R.: Fuzzy querying of incomplete, imprecise, and heterogeneously structured data in the relational model using ontologies and rules. IEEE T. Fuzzy Systems 13(3), 373–383 (2005)
Zanibbi, R., Blostein, D., Cordy, J.R.: A survey of table recognition: Models, observations, transformations, and inferences. International Journal on Document Analysis and Recognition 7, 1–16 (2004)
Pivk, A., Cimiano, P., Sure, Y.: From tables to frames. In: Third International Semantic Web Conference, pp. 116–181 (2004)
Tenier, S., Toussaint, Y., Napoli, A., Polanco, X.: Instantiation of relations for semantic annotation. In: International Conference on Web Intelligence, pp. 463–472 (2006)
Embley, D.W., Tao, C., Liddle, S.W.: Automatically extracting ontologically specified data from html tables of unknown structure. In: Spaccapietra, S., March, S.T., Kambayashi, Y. (eds.) ER 2002. LNCS, vol. 2503, pp. 322–337. Springer, Heidelberg (2002)
Freitag, D., Kushmerick, N.: Boosted wrapper induction. In: 17th National Conference on Artificial Intelligence, pp. 577–583 (2000)
Baumgartner, R., Flesca, S., Gottlob, G.: Visual web information extraction with Lixto. In: International Conference on Very Large Data Bases, pp. 119–128 (2001)
Gagliardi, H., Haemmerlé, O., Pernelle, N., Saïs, F.: An automatic ontology-based approach to enrich tables semantically. In: AAAI Context and Ontologies Workshop (2005)
Lin, D.: An information-theoretic definition of similarity. In: International Conference on Machine Learning, pp. 296–304 (1998)
Hignette, G., Buche, P., Dervin, C., Dibie-Barthélemy, J., Haemmerlé, O., Soler, L.: Fuzzy semantic approach for data integration applied to risk in food: an example about the cold chain. In: Proceedings of the 13th World Congress of Food Science and Technology, Food is Life (2006)
Van Rijsbergen, C.J.: Information Retrieval, 2nd edn., Dept. of Computer Science, University of Glasgow (1979)
Yangarber, R., Lin, W., Grishman, R.: Unsupervised learning of generalized names. In: International Conference on Computational Linguistics, pp. 1–7 (2002)
Platt, J.C.: Fast training of support vector machines using sequential minimal optimization, pp. 185–208. MIT Press, Cambridge (1999)
Zadeh, L.: Fuzzy sets. Information and control 8, 338–353 (1965)
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Hignette, G., Buche, P., Dibie-Barthélemy, J., Haemmerlé, O. (2007). An Ontology-Driven Annotation of Data Tables. In: Weske, M., Hacid, MS., Godart, C. (eds) Web Information Systems Engineering – WISE 2007 Workshops. WISE 2007. Lecture Notes in Computer Science, vol 4832. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77010-7_4
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DOI: https://doi.org/10.1007/978-3-540-77010-7_4
Publisher Name: Springer, Berlin, Heidelberg
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