{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,8]],"date-time":"2024-09-08T00:55:27Z","timestamp":1725756927345},"publisher-location":"Berlin, Heidelberg","reference-count":12,"publisher":"Springer Berlin Heidelberg","isbn-type":[{"type":"print","value":"9783642415494"},{"type":"electronic","value":"9783642415500"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2013]]},"DOI":"10.1007\/978-3-642-41550-0_25","type":"book-chapter","created":{"date-parts":[[2013,11,14]],"date-time":"2013-11-14T05:56:33Z","timestamp":1384408593000},"page":"284-295","source":"Crossref","is-referenced-by-count":0,"title":["Improving Automatic Edge Selection for Relational Classification"],"prefix":"10.1007","author":[{"given":"Cristina","family":"P\u00e9rez-Sol\u00e0","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jordi","family":"Herrera-Joancomart\u00ed","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","reference":[{"key":"25_CR1","doi-asserted-by":"crossref","unstructured":"John, G.H., Kohavi, R., Pfleger, K.: Irrelevant features and the subset selection problem. In: Proceedings of the 11th Int. Machine Learning, pp. 121\u2013129 (1994)","DOI":"10.1016\/B978-1-55860-335-6.50023-4"},{"issue":"1-2","key":"25_CR2","doi-asserted-by":"publisher","first-page":"273","DOI":"10.1016\/S0004-3702(97)00043-X","volume":"97","author":"R. Kohavi","year":"1997","unstructured":"Kohavi, R., John, G.H.: Wrappers for feature subset selection. Artificial Intelligence\u00a097(1-2), 273\u2013324 (1997)","journal-title":"Artificial Intelligence"},{"key":"25_CR3","unstructured":"Almuallim, H., Dietterich, T.G.: Learning with many irrelevant features. In: Proceedings of the 9th National Conf. on Artificial Intelligence, pp. 547\u2013552 (1991)"},{"key":"25_CR4","unstructured":"Kira, K., Rendell, L.A.: The feature selection problem: traditional methods and a new algorithm. In: Proc. of the 10th Conf. on Artificial intelligence, pp. 129\u2013134 (1992)"},{"key":"25_CR5","doi-asserted-by":"crossref","unstructured":"Cardie, C.: Using decision trees to improve case-based learning. In: Proceedings of the 10th Int. Conf. on Machine Learning, pp. 25\u201332. Morgan Kaufmann (1993)","DOI":"10.1016\/B978-1-55860-307-3.50010-1"},{"key":"25_CR6","first-page":"935","volume":"8","author":"S.A. Macskassy","year":"2007","unstructured":"Macskassy, S.A., Provost, F.: Classification in networked data: A toolkit and a univariate case study. J. Mach. Learn. Res.\u00a08, 935\u2013983 (2007)","journal-title":"J. Mach. Learn. Res."},{"key":"25_CR7","doi-asserted-by":"crossref","first-page":"026126","DOI":"10.1103\/PhysRevE.67.026126","volume":"67","author":"M.E.J. Newman","year":"2003","unstructured":"Newman, M.E.J.: Mixing patterns in networks. Phys. Rev. E\u00a067, 026126 (2003)","journal-title":"Phys. Rev. E"},{"issue":"1-2","key":"25_CR8","doi-asserted-by":"publisher","first-page":"65","DOI":"10.1007\/s10994-006-6064-1","volume":"62","author":"C. Perlich","year":"2006","unstructured":"Perlich, C., Provost, F.: Distribution-based aggregation for relational learning with identifier attributes. Machine Learning\u00a062(1-2), 65\u2013105 (2006)","journal-title":"Machine Learning"},{"key":"25_CR9","doi-asserted-by":"crossref","unstructured":"Perlich, C., Provost, F.: Aggregation-based feature invention and relational concept classes. In: Proc. of the 9th Int. Conf. on Knowledge Discovery and Data Mining, pp. 167\u2013176 (2003)","DOI":"10.1145\/956750.956772"},{"key":"25_CR10","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1016\/0377-0427(87)90125-7","volume":"20","author":"P. Rousseeuw","year":"1987","unstructured":"Rousseeuw, P.: Silhouettes: A graphical aid to the interpretation and validation of cluster analysis. J. of Computational & Applied Mathematics\u00a020, 53\u201365 (1987)","journal-title":"J. of Computational & Applied Mathematics"},{"key":"25_CR11","unstructured":"Macskassy, S., Provost, F.: NetKit-SRL - network learning toolkit for statistical relational learning"},{"key":"25_CR12","unstructured":"Kendall, M., Gibbons, J.D.: Rank Correlation Methods, 5th edn. A Charles Griffin Title (September 1990)"}],"container-title":["Lecture Notes in Computer Science","Modeling Decisions for Artificial Intelligence"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-642-41550-0_25","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,5,24]],"date-time":"2019-05-24T02:57:28Z","timestamp":1558666648000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-642-41550-0_25"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013]]},"ISBN":["9783642415494","9783642415500"],"references-count":12,"URL":"https:\/\/doi.org\/10.1007\/978-3-642-41550-0_25","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2013]]}}}