{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,30]],"date-time":"2025-10-30T07:09:57Z","timestamp":1761808197596},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,7]]},"abstract":"<jats:p>The problem of integrating heterogeneous data sources into an ontology is highly relevant in the database field.\n\nSeveral techniques exist to approach the problem, but side constraints on the data cannot be easily implemented and thus the results may be inconsistent.\n\nIn this paper we improve previous work by Taheriyan et al. [2016a] using Machine Learning (ML) to take into account inconsistencies in the data (unmatchable attributes) and encode the problem as a variation of the Steiner Tree, for which we use work by De U\u00f1a et al. [2016] in Constraint Programming (CP).\n\nCombining ML and CP achieves state-of-the-art precision, recall and speed, and provides a more flexible framework for variations of the problem.<\/jats:p>","DOI":"10.24963\/ijcai.2018\/178","type":"proceedings-article","created":{"date-parts":[[2018,7,5]],"date-time":"2018-07-05T01:49:10Z","timestamp":1530755350000},"page":"1277-1283","source":"Crossref","is-referenced-by-count":11,"title":["Machine Learning and Constraint Programming for Relational-To-Ontology Schema Mapping"],"prefix":"10.24963","author":[{"given":"Diego","family":"De U\u00f1a","sequence":"first","affiliation":[{"name":"Department of Computing and Information System, University of Melbourne"}]},{"given":"Nataliia","family":"R\u00fcmmele","sequence":"additional","affiliation":[{"name":"Siemens, Germany"}]},{"given":"Graeme","family":"Gange","sequence":"additional","affiliation":[{"name":"Department of Computing and Information System, University of Melbourne"}]},{"given":"Peter","family":"Schachte","sequence":"additional","affiliation":[{"name":"Department of Computing and Information System, University of Melbourne"}]},{"given":"Peter J.","family":"Stuckey","sequence":"additional","affiliation":[{"name":"Department of Computing and Information System, University of Melbourne"},{"name":"Data61, CSIRO, Melbourne, Australia"}]}],"member":"10584","event":{"number":"27","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"acronym":"IJCAI-2018","name":"Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}","start":{"date-parts":[[2018,7,13]]},"theme":"Artificial Intelligence","location":"Stockholm, Sweden","end":{"date-parts":[[2018,7,19]]}},"container-title":["Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2018,7,5]],"date-time":"2018-07-05T01:50:33Z","timestamp":1530755433000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2018\/178"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2018,7]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2018\/178","relation":{},"subject":[],"published":{"date-parts":[[2018,7]]}}}