Abstract
Common data mining metadata benefits sharing, exchanging and integration among data mining applications. The Predictive Model Markup Language PMML facilitates the exchange of models among data mining applications and becomes a standard of data mining metadata. However, the evolution of models and extension of products, PMML needs large number of language elements and leads to conflicts in PMML based data mining metadata inevitably. This paper presents an extended predictive model markup language EPMML for data mining, which is designed to reduce the complexity of PMML language elements. The description logic for predictive model markup language DL4PMML that belongs to the description logic family, is the formal logical foundation of EPMML and makes it possess strong semantic expression ability. We analyze how EPMML describe data mining contents in detail. Some experiments expatiate how EPMML based data mining metadata support automatically reasoning and detect inherent semantic conflicts.
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References
OMG, Common Warehouse Metamodel Specification, Version 1.1 (2001), http://www.omg.org
DMG, Data Mining Group-PMML Products (2008), http://www.dmg.org/products.html
Zhu, X.D., Huang, Z.Q., Shen, G.H.: Description Logic based Consistency Checking upon Data Mining Metadata. In: Wang, G., Li, T., Grzymala-Busse, J.W., Miao, D., Skowron, A., Yao, Y. (eds.) RSKT 2008. LNCS (LNAI), vol. 5009, pp. 475–482. Springer, Heidelberg (2008)
Zhu, X.D., Huang, Z.Q.: Conceptual Modeling Rules Extracting for Data Streams. Knowledge-based Systems 21(8), 934–940
DM-SSP-06: Data Mining Standards, Services and Platforms. In: DM-SSP Workshop associated with the 2006 KDD Conference, Philadelphia, PA, August 20-23 (2006), http://www.ncdm.uic.edu/dm-ssp-06.htm
DM-SSP-07, Data Mining Standards, Services and Platforms. In: DM-SSP Workshop associated with the 2007 KDD Conference, San Jose, California, August 12-15 (2007), http://www.opendatagroup.com/dmssp07
Pechter, R.: Conformance Standard for the Predictive Model Markup Language. In: The Fourth Workshop on Data Mining Standards, Services and Platforms (DM-SSP 2006), associated with 12th ACM SIGMOD International Conference on Knowledge Discovery & Data Mining (KDD 2006), Philadelphia, Pennsylvania, USA (2006)
Baader, F., Horrocks, I., Sattler, U.: Description Logics as Ontology Languages for the Semantic Web. In: Hutter, D., Stephan, W. (eds.) Mechanizing Mathematical Reasoning. LNCS (LNAI), vol. 2605, pp. 228–248. Springer, Heidelberg (2005)
Horrocks, I., Patel-Schneider, P.F.: Reducing OWL entailment to description logic satisfiability. Journal of Web Semantics 1, 345–357 (2004)
Horrocks, I., Sattler, U.: A Tableaux decision procedure for SHOIQ. In: The 19th International Joint Conference on Artificial Intelligence (IJCAI 2005), pp. 448–453 (2005)
Wessel, M.: Decidable and undecidable extensions of ALC with composition-based role inclusion axioms. University of Hamburg, Germany (2000)
Lutz, C.: The complexity of reasoning with concrete domains, in Teaching and Research Area for Theoretical Computer Science, Ph.D. RWTH Aachen, Germany (2002)
Lutz, C.: An improved NExpTime-hardness result for description logic ALC extended with inverse roles, nominals, and counting. Dresden University of Technology, Germany (2004)
Haarslev, V., Moller, R., Wessel, M.: RacerPro Version 1.9 (2005), http://www.racer-systems.com
CRISP-DM, CRoss Industry Standard Process for Data Mining (2007), http://www.crisp-dm.org
Zubcoff, J., Trujillo, J.: Conceptual Modeling for classification mining in Data Warehouses. In: Tjoa, A.M., Trujillo, J. (eds.) DaWaK 2006. LNCS, vol. 4081, pp. 566–575. Springer, Heidelberg (2006)
Castellano, M., Pastore, N., Arcieri, F., Summo, V., de Grecis, G.: A Model-view-controller Architecture for Knowledge Discovery. In: The 5th International Conference on Data Mining, Malaga, Spain (2004)
Chaves, J., Curry, C., Grossman, R.L., Locke, D., Vejcik, S.: Augustus: The design and Architecture of a PMML-based scoring engine. In: The Fourth Workshop on Data Mining Standards, Services and Platforms (DM-SSP 2006), associated with 12th ACM SIGMOD International Conference on Knowledge Discovery & Data Mining (KDD 2006), Philadelphia, Pennsylvania, USA (2006)
Haarslev, V., Möller, R., Wessel, M.: Querying the semantic web with Racer+nRQL (2004), http://www.racer-systems.com/technology/contributions/2004/HaMW04.pdf
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Zhu, X., Yang, J. (2010). An Extended Predictive Model Markup Language for Data Mining. In: Chen, L., Tang, C., Yang, J., Gao, Y. (eds) Web-Age Information Management. WAIM 2010. Lecture Notes in Computer Science, vol 6184. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14246-8_23
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DOI: https://doi.org/10.1007/978-3-642-14246-8_23
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