{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T07:22:56Z","timestamp":1774941776274,"version":"3.50.1"},"reference-count":27,"publisher":"Maximum Academic Press","issue":"2","license":[{"start":{"date-parts":[[2013,2,7]],"date-time":"2013-02-07T00:00:00Z","timestamp":1360195200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/www.cambridge.org\/core\/terms"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["The Knowledge Engineering Review"],"published-print":{"date-parts":[[2013,6]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>This paper presents a distributed architecture for automating data mining (DM) processes using standard languages. DM is a difficult task that relies on an exploratory and analytic process of processing large quantities of data in order to discover meaningful patterns. The increasing heterogeneity and complexity of available data requires some expert knowledge on how to combine the multiple and alternative DM tasks to process the data. Here, we describe DM tasks in terms of Automated Planning, which allows us to automate the DM knowledge flow construction. The work is based on the use of standards that have been defined in both DM and automated-planning communities. Thus, we use PMML (Predictive Model Markup Language) to describe DM tasks. From the PMML, a problem description in PDDL (Planning Domain Definition Language) can be generated, so any current planning system can be used to generate a plan. This plan is, again, translated to a DM workflow description, Knowledge Flow for Machine Learning format (Knowledge Flow file for the WEKA (Waikato Environment for Knowledge Analysis) tool), so the plan or DM workflow can be executed in WEKA.<\/jats:p>","DOI":"10.1017\/s0269888912000409","type":"journal-article","created":{"date-parts":[[2013,2,6]],"date-time":"2013-02-06T10:39:19Z","timestamp":1360147159000},"page":"157-173","source":"Crossref","is-referenced-by-count":4,"title":["Using automated planning for improving data mining processes"],"prefix":"10.48130","volume":"28","author":[{"given":"Susana","family":"Fern\u00e1ndez","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tom\u00e1s","family":"de la Rosa","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fernando","family":"Fern\u00e1ndez","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rub\u00e9n","family":"Su\u00e1rez","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Javier","family":"Ortiz","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daniel","family":"Borrajo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"David","family":"Manzano","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"27968","published-online":{"date-parts":[[2013,2,7]]},"reference":[{"key":"S0269888912000409_ref20","volume-title":"Machine Learning, Neural and Statistical Classification","author":"Michie","year":"1994"},{"key":"S0269888912000409_ref21","first-page":"47","volume-title":"Intelligent Technologies for Information Analysis","author":"Morik","year":"2003"},{"key":"S0269888912000409_ref19","unstructured":"Michalski R. S. , Kaufman K. A. 1998. Discovery planning: multistrategy learning in data mining. In Proceedings of the 4th International Workshop on Multistrategy Learning, Desenzano de Garda, Italy, 14\u201320."},{"key":"S0269888912000409_ref5","unstructured":"De la Rosa T. , Garc\u00eda-Olaya A. , Borrajo D. 2007. Using cases utility for heuristic planning improvement. In Case-Based Reasoning Research and Development: Proceedings of the 7th International Conference on Case-Based Reasoning, Weber, R. O. & Richter, M. M. Belfast, Northern Ireland, UK, 137\u2013148. Springer Verlag. ISBN 978-3-540-74138-1."},{"key":"S0269888912000409_ref22","unstructured":"Penberthy J. S. , Weld D. 1992. UCPOP: a sound, complete, partial order planner for ADL. In Proceedings of the 3rd International Conference on Principles of Knowledge Representation and Reasoning, San Mateo, CA."},{"key":"S0269888912000409_ref16","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1613\/jair.2716","article-title":"Message-based web service composition, integrity constraints, and planning under uncertainty: a new connection","volume":"35","author":"Hoffmann","year":"2009","journal-title":"Journal of Artificial Intelligence Research"},{"key":"S0269888912000409_ref17","unstructured":"Kietz J.-U. , Serban F. , Bernstein A. , Fischer S. 2009. Towards cooperative planning of data mining workflows. In ECML\/PKDD09 Workshop on Third Generation Data Mining: Towards Service-oriented Knowledge Discovery (SoKD-09), Bled, Slovenia, 1\u201312."},{"key":"S0269888912000409_ref26","volume-title":"Data Mining: Practical Machine Learning Tools and Techniques","author":"Witten","year":"2005"},{"key":"S0269888912000409_ref9","first-page":"37","article-title":"From data mining to knowledge discovery in databases","volume":"17","author":"Fayyad","year":"1996","journal-title":"AI Magazine"},{"key":"S0269888912000409_ref1","doi-asserted-by":"crossref","unstructured":"Amant R. S. , Cohen P. R. 1997. Evaluation of a semi-autonomous assistant for exploratory data analysis. In Proceedings of the 1st International Conference on Autonomous Agents, Johnson, W. L. & Hayes-Roth, B. (eds). Marina del Rey, California, United States, 355\u2013362. ACM Press.","DOI":"10.1145\/267658.267740"},{"key":"S0269888912000409_ref2","doi-asserted-by":"crossref","unstructured":"Ambite J. L. , Kapoor D. 2007. Automatically composing data workflows with relational descriptions and shim services. In The Semantic Web, Lecture Notes in Computer Science 4825, 15\u201329. Springer.","DOI":"10.1007\/978-3-540-76298-0_2"},{"key":"S0269888912000409_ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2005.67"},{"key":"S0269888912000409_ref4","doi-asserted-by":"publisher","DOI":"10.1109\/34.531806"},{"key":"S0269888912000409_ref6","doi-asserted-by":"crossref","unstructured":"Diamantini C. , Potena D. , Storti E. 2009. Ontology-driven KDD process composition. In Advances in Intelligent Data Analysis VIII, Lecture Notes in Computer Science 5772, 285\u2013296. Springer.","DOI":"10.1007\/978-3-642-03915-7_25"},{"key":"S0269888912000409_ref7","unstructured":"Engels R. 1996. Planning tasks for knowledge discovery in databases; performing task-oriented user-guidance. In Proceedings of the 2nd International Conference on KDD, Menlo Park, California. AAAI Press."},{"key":"S0269888912000409_ref8","doi-asserted-by":"publisher","DOI":"10.1145\/176789.176797"},{"key":"S0269888912000409_ref23","unstructured":"Rodr\u00edguez-Moreno M. D. , Borrajo D. , Cesta A. , Oddi A. 2007. Integrating planning and scheduling in workflow domains. Expert System with Applications, 33(2). Retrieved from http:\/\/hdl.handle.net\/10016\/8289."},{"key":"S0269888912000409_ref25","volume-title":"Studies in Computational Intelligence (SCI)","author":"Sumathi","year":"2006"},{"key":"S0269888912000409_ref10","doi-asserted-by":"crossref","unstructured":"Fern\u00e1ndez F. , Borrajo D. , Fern\u00e1ndez S. , Manzano D. 2009. Assisting data mining through automated planning. In Machine Learning and Data Mining 2009 (MLDM 2009), Perner, P. (ed.), Lecture Notes in Artificial Intelligence 5632, 760\u2013774. Springer-Verlag.","DOI":"10.1007\/978-3-642-03070-3_57"},{"key":"S0269888912000409_ref12","volume-title":"Automated Planning\u2014Theory and Practice","author":"Ghallab","year":"2004"},{"key":"S0269888912000409_ref13","doi-asserted-by":"publisher","DOI":"10.1145\/846170.846172"},{"key":"S0269888912000409_ref14","unstructured":"Golden K. 1997. Planning and Knowledge Representations for Softbots. PhD thesis, University of Washington."},{"key":"S0269888912000409_ref15","unstructured":"Hilario M. , Kalousis A. , Nguyen P. , Woznica A. 2009. A data mining ontology for algorithm selection and meta-learning. In ECML\/PKDD09 Workshop on Third Generation Data Mining: Towards Service-oriented Knowledge Discovery (SoKD-09), Bled, Slovenia, 76\u201387."},{"key":"S0269888912000409_ref18","unstructured":"Livingston G. R. , Rosenberg J. M. , Buchanan B. G. 2001. Closing the loop: an agenda- and justification-based framework for selecting the next discovery task to perform. IEEE International Conference on Data Mining, Vancouver, BC, Canada, 385. doi: http:\/\/doi.ieeecomputersociety.org\/10.1109\/ICDM.2001.989543."},{"key":"S0269888912000409_ref24","doi-asserted-by":"publisher","DOI":"10.1007\/s10115-006-0037-3"},{"key":"S0269888912000409_ref27","unstructured":"Zakova M. , Kremen P. , Zelezny F. , Lavrac N. 2008. Planning for data mining workflow composition. In SoKD: ECML\/PKDD 2008 Workshop on 3rd Generation Data Mining: Towards Service-oriented Knowledge Discovery, Antwerp, Belgium."},{"key":"S0269888912000409_ref11","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1613\/jair.1129","article-title":"PDDL2.1: an extension to PDDL for expressing temporal planning domains","volume":"20","author":"Fox","year":"2003","journal-title":"Journal of Artificial Intelligence Research"}],"container-title":["The Knowledge Engineering Review"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.cambridge.org\/core\/services\/aop-cambridge-core\/content\/view\/S0269888912000409","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,5]],"date-time":"2026-01-05T14:41:54Z","timestamp":1767624114000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.cambridge.org\/core\/product\/identifier\/S0269888912000409\/type\/journal_article"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013,2,7]]},"references-count":27,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2013,6]]}},"alternative-id":["S0269888912000409"],"URL":"https:\/\/doi.org\/10.1017\/s0269888912000409","relation":{},"ISSN":["0269-8889","1469-8005"],"issn-type":[{"value":"0269-8889","type":"print"},{"value":"1469-8005","type":"electronic"}],"subject":[],"published":{"date-parts":[[2013,2,7]]}}}