Abstract
This paper aims at comparing transformation-based approaches built to deal with relational data, and in particular two approaches which have emerged in two different communities: Relational Concept Analysis (RCA), based on an iterative use of the classical Formal Concept Analysis (FCA) approach, and Propositionalisation coming from the Inductive Logic Programming community. Both approaches work by transforming a complex problem into a simpler one, namely transforming a database consisting of several tables into a single table. For this purpose, a main table is chosen and new attributes capturing the information from the other tables are built and added to this table. We show the similarities between those transformations for what concerns the principles underlying them, the semantics of the built attributes and the result of a classification performed by FCA on the enriched table. This is illustrated on a simple dataset and we also present a synthetic comparison based on a larger dataset from the hydrological domain.
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References
Lachiche, N.: Propositionalization. In: Sammut, C., Webb, G.L. (eds.) Encyclopedia of Machine Learning, pp. 812–817. Springer (2010)
Kuželka, O., Železný, F.: HiFi: Tractable Propositionalization through Hierarchical Feature Construction. In: Late Breaking Papers, the 18th Int. Conf. on Inductive Logic Programming, pp. 1–6 (2008)
Ganter, B., Wille, R.: Formal Concept Analysis: Mathematical Foundations. Springer (1999)
Rouane-Hacene, M., Huchard, M., Napoli, A., Valtchev, P.: Relational concept analysis: mining concept lattices from multi-relational data. Ann. Math. Artif. Intell. 67(1), 81–108 (2013)
Rouane-Hacene, M., Huchard, M., Napoli, A., Valtchev, P.: Soundness and completeness of relational concept analysis. In: Cellier, P., Distel, F., Ganter, B. (eds.) ICFCA 2013. LNCS, vol. 7880, pp. 228–243. Springer, Heidelberg (2013)
Muggleton, S., Raedt, L.D.: Inductive logic programming: Theory and methods. Journal of Logic Programming 19(20), 629–679 (1994)
Agrawal, R., Imielinski, T., Swami, A.N.: Mining association rules between sets of items in large databases. In: Proceedings of the 1993 ACM SIGMOD Int. Conference on Management of Data, pp. 207–216 (1993)
Grac, C., Le Ber, F., Braud, A., Trémolières, M., Bertaux, A., Herrmann, A., Manné, S., Lafont, M.: Programme de recherche-développement Indices – rapport scienfique final. Contrat pluriannuel 1463 de l’Agence de l’Eau Rhin-Meuse, LHYGES – LSIIT – ONEMA – CEMAGREF (2011)
Bertaux, A., Le Ber, F., Braud, A., Trémolières, M.: Identifying ecological traits: A concrete FCA-based approach. In: Ferré, S., Rudolph, S. (eds.) ICFCA 2009. LNCS (LNAI), vol. 5548, pp. 224–236. Springer, Heidelberg (2009)
Hereth, J., Stumme, G., Wille, R., Wille, U.: Conceptual knowledge discovery and data analysis. In: Ganter, B., Mineau, G.W. (eds.) ICCS 2000. LNCS (LNAI), vol. 1867, pp. 421–437. Springer, Heidelberg (2000)
Guillas, S., Bertet, K., Ogier, J.M., Girard, N.: Some links between decision tree and dichotomic lattice. In: 8th Int. Conf. on Concept Lattices and Applications, CLA 2008, Olomouc, Czech Republic, pp. 193–205 (2008)
Prediger, S., Wille, R.: The Lattice of Concept Graphs of a Relationally Scaled Context. In: Tepfenhart, W.M. (ed.) ICCS 1999. LNCS, vol. 1640, pp. 401–414. Springer, Heidelberg (1999)
Wille, R.: Conceptual Graphs and Formal Concept Analysis. In: Delugach, H.S., Keeler, M.A., Searle, L., Lukose, D., Sowa, J.F. (eds.) ICCS 1997. LNCS, vol. 1257, pp. 290–303. Springer, Heidelberg (1997)
Wolff, K.E.: Relational Scaling in Relational Semantic Systems. In: Rudolph, S., Dau, F., Kuznetsov, S.O. (eds.) ICCS 2009. LNCS, vol. 5662, pp. 307–320. Springer, Heidelberg (2009)
Ferré, S., Ridoux, O., Sigonneau, B.: Arbitrary Relations in Formal Concept Analysis and Logical Information Systems. In: Dau, F., Mugnier, M.-L., Stumme, G. (eds.) ICCS 2005. LNCS (LNAI), vol. 3596, pp. 166–180. Springer, Heidelberg (2005)
Baader, F., Distel, F.: A finite basis for the set of \(\mathcal{EL}\)-implications holding in a finite model. In: Medina, R., Obiedkov, S. (eds.) ICFCA 2008. LNCS (LNAI), vol. 4933, pp. 46–61. Springer, Heidelberg (2008)
Stanley, R., Astudillo, H., Codocedo, V., Napoli, A.: A Conceptual-KDD Approach and its Application to Cultural Heritage. In: 10th Int. Conf. on Concept Lattices and Their Applications, CLA. CEUR Workshop Proceedings, vol. 1062, pp. 163–174 (2013)
Krmelova, M., Trnecka, M.: Boolean Factor Analysis of Multi-Relational Data. In: 10th Int. Conf. on Concept Lattices and Their Applications, CLA 2013, La Rochelle, France. CEUR Workshop Proceedings, vol. 1062, pp. 187–198 (2013)
Chekol, M.W., Napoli, A.: An FCA Framework for Knowledge Discovery in SPARQL Query Answers. In: Int. Semantic Web Conference (Posters & Demos), ISWC 2013, Sydney, Australia. CEUR Workshop Proceedings, vol. 1035, pp. 197–200 (2013)
Kötters, J.: Concept Lattices of a Relational Structure. In: Pfeiffer, H.D., Ignatov, D.I., Poelmans, J., Gadiraju, N. (eds.) ICCS 2013. LNCS, vol. 7735, pp. 301–310. Springer, Heidelberg (2013)
Azmeh, Z., Huchard, M., Napoli, A., Hacene, M.R., Valtchev, P.: Querying relational concept lattices. In: 8th Int. Conf. on Concept Lattices and Their Applications, Nancy, France. CEUR Workshop Proceedings, vol. 959, pp. 377–392 (2011)
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Dolques, X., Mondal, K.C., Braud, A., Huchard, M., Le Ber, F. (2014). RCA as a Data Transforming Method: A Comparison with Propositionalisation. In: Glodeanu, C.V., Kaytoue, M., Sacarea, C. (eds) Formal Concept Analysis. ICFCA 2014. Lecture Notes in Computer Science(), vol 8478. Springer, Cham. https://doi.org/10.1007/978-3-319-07248-7_9
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DOI: https://doi.org/10.1007/978-3-319-07248-7_9
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