{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,7]],"date-time":"2025-04-07T00:40:02Z","timestamp":1743986402670,"version":"3.40.3"},"publisher-location":"Berlin, Heidelberg","reference-count":29,"publisher":"Springer Berlin Heidelberg","isbn-type":[{"type":"print","value":"9783642325991"},{"type":"electronic","value":"9783642326004"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2012]]},"DOI":"10.1007\/978-3-642-32600-4_28","type":"book-chapter","created":{"date-parts":[[2012,8,20]],"date-time":"2012-08-20T05:02:17Z","timestamp":1345438937000},"page":"384-396","source":"Crossref","is-referenced-by-count":0,"title":["Learning to Rank from Concept-Drifting Network Data Streams"],"prefix":"10.1007","author":[{"given":"Lucrezia","family":"Macchia","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michelangelo","family":"Ceci","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Donato","family":"Malerba","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","reference":[{"key":"28_CR1","doi-asserted-by":"crossref","unstructured":"Aiolli, F.: A preference model for structured supervised learning tasks. In: ICDM, pp. 557\u2013560. IEEE Computer Society (2005)","DOI":"10.1109\/ICDM.2005.11"},{"key":"28_CR2","series-title":"Statistics\/Probability Series","volume-title":"Classification and Regression Trees","author":"L. Breiman","year":"1984","unstructured":"Breiman, L., Friedman, J.H., Olshen, R.A., Stone, C.J.: Classification and Regression Trees. Statistics\/Probability Series. Wadsworth Publishing Company, Belmont (1984)"},{"key":"28_CR3","doi-asserted-by":"crossref","unstructured":"Crammer, K., Singer, Y.: Pranking with ranking. In: NIPS, pp. 641\u2013647. MIT Press (2001)","DOI":"10.7551\/mitpress\/1120.003.0087"},{"key":"28_CR4","doi-asserted-by":"crossref","unstructured":"Dembczyski, K., Kotlowski, W., Slowiski, R., Szelag, M.: Learning of rule ensembles for multiple attribute ranking problems. In: F\u00fcrnkranz, J., H\u00fcllermeier, E. (eds.) Preference Learning, pp. 217\u2013247. Springer (2010)","DOI":"10.1007\/978-3-642-14125-6_11"},{"issue":"2","key":"28_CR5","doi-asserted-by":"publisher","first-page":"111","DOI":"10.1111\/j.0824-7935.2004.00233.x","volume":"20","author":"J. Doyle","year":"2004","unstructured":"Doyle, J.: Prospects for preferences. Computational Intelligence\u00a020(2), 111\u2013136 (2004)","journal-title":"Computational Intelligence"},{"key":"28_CR6","series-title":"Wiley series in probability and mathematical statistics","volume-title":"Applied regression analysis","author":"N.R. Draper","year":"1996","unstructured":"Draper, N.R., Smith, H.: Applied regression analysis. Wiley series in probability and mathematical statistics. Wiley, New York (1996)"},{"key":"28_CR7","unstructured":"Draper, N.R., Smith, H.: Applied regression analysis. John Wiley & Sons (1982)"},{"key":"28_CR8","series-title":"Lecture Notes in Artificial Intelligence","doi-asserted-by":"publisher","first-page":"365","DOI":"10.1007\/3-540-36169-3_29","volume-title":"Algorithmic Learning Theory","author":"S. Har-Peled","year":"2002","unstructured":"Har-Peled, S., Roth, D., Zimak, D.: Constraint Classification: A New Approach to Multiclass Classification. In: Cesa-Bianchi, N., Numao, M., Reischuk, R. (eds.) ALT 2002. LNCS (LNAI), vol.\u00a02533, pp. 365\u2013379. Springer, Heidelberg (2002)"},{"key":"28_CR9","unstructured":"Har-Peled, S., Roth, D., Zimak, D.: Constraint classification for multiclass classification and ranking. In: Becker, S., Thrun, S., Obermayer, K. (eds.) Advances in Neural Information Processing Systems 15 (NIPS 2002), pp. 785\u2013792 (2003)"},{"key":"28_CR10","unstructured":"Herbrich, R., Graepel, T., Bollmann-sdorra, P., Obermayer, K.: Learning preference relations for information retrieval (1998)"},{"key":"28_CR11","doi-asserted-by":"crossref","unstructured":"Herbrich, R., Graepel, T., Obermayer, K.: Large margin rank boundaries for ordinal regression. MIT Press (2000)","DOI":"10.7551\/mitpress\/1113.003.0010"},{"key":"28_CR12","unstructured":"Jensen, D., Neville, J.: Linkage and autocorrelation cause feature selection bias in relational learning. In: Proc. 9th Intl. Conf. on Machine Learning, pp. 259\u2013266. Morgan Kaufmann (2002)"},{"key":"28_CR13","doi-asserted-by":"publisher","first-page":"133","DOI":"10.1145\/775047.775067","volume-title":"Proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2002","author":"T. Joachims","year":"2002","unstructured":"Joachims, T.: Optimizing search engines using clickthrough data. In: Proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2002, pp. 133\u2013142. ACM, New York (2002)"},{"key":"28_CR14","unstructured":"Karalic, A.: Linear regression in regression tree leaves. In: Proceedings of ECAI 1992, pp. 440\u2013441. John Wiley & Sons (1992)"},{"key":"28_CR15","unstructured":"Lubinsky, D.: Tree structured interpretable regression. In: Fisher, D., Lenz, H.J. (eds.) Learning from Data. Lecture Notes in Statistics. Springer (1994)"},{"key":"28_CR16","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"566","DOI":"10.1007\/978-3-642-31537-4_44","volume-title":"Machine Learning and Data Mining in Pattern Recognition","author":"L. Macchia","year":"2012","unstructured":"Macchia, L., Ceci, M., Malerba, D.: Mining Ranking Models from Dynamic Network Data. In: Perner, P. (ed.) MLDM 2012. LNCS, vol.\u00a07376, pp. 566\u2013577. Springer, Heidelberg (2012)"},{"issue":"5","key":"28_CR17","doi-asserted-by":"publisher","first-page":"612","DOI":"10.1109\/TPAMI.2004.1273937","volume":"26","author":"D. Malerba","year":"2004","unstructured":"Malerba, D., Esposito, F., Ceci, M., Appice, A.: Top-down induction of model trees with regression and splitting nodes. IEEE Trans. Pattern Anal. Mach. Intell.\u00a026(5), 612\u2013625 (2004)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"28_CR18","doi-asserted-by":"crossref","unstructured":"Neville, J., Simsek, O., Jensen, D.: Autocorrelation and relational learning: Challenges and opportunities. In: Wshp. Statistical Relational Learning (2004)","DOI":"10.21236\/ADA472226"},{"key":"28_CR19","unstructured":"Newman, M.E.J., Watts, D.J.: The structure and dynamics of networks. Princeton University Press (2006)"},{"key":"28_CR20","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1613\/jair.614","volume":"11","author":"D. Opitz","year":"1999","unstructured":"Opitz, D., Maclin, R.: Popular ensemble methods: An empirical study. Journal of Artificial Intelligence Research\u00a011, 169\u2013198 (1999)","journal-title":"Journal of Artificial Intelligence Research"},{"issue":"3","key":"28_CR21","doi-asserted-by":"publisher","first-page":"351","DOI":"10.2307\/2087176","volume":"15","author":"W.S. Robinson","year":"1950","unstructured":"Robinson, W.S.: Ecological Correlations and the Behavior of Individuals. American Sociological Review\u00a015(3), 351\u2013357 (1950)","journal-title":"American Sociological Review"},{"key":"28_CR22","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"333","DOI":"10.1007\/978-3-642-23808-6_22","volume-title":"Machine Learning and Knowledge Discovery in Databases","author":"D. Stojanova","year":"2011","unstructured":"Stojanova, D., Ceci, M., Appice, A., D\u017eeroski, S.: Network Regression with Predictive Clustering Trees. In: Gunopulos, D., Hofmann, T., Malerba, D., Vazirgiannis, M. (eds.) ECML PKDD 2011, Part III. LNCS, vol.\u00a06913, pp. 333\u2013348. Springer, Heidelberg (2011)"},{"key":"28_CR23","doi-asserted-by":"publisher","first-page":"377","DOI":"10.1145\/502512.502568","volume-title":"Proceedings of the Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2001","author":"W.N. Street","year":"2001","unstructured":"Street, W.N., Kim, Y.: A streaming ensemble algorithm (sea) for large-scale classification. In: Proceedings of the Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2001, pp. 377\u2013382. ACM, New York (2001)"},{"issue":"4","key":"28_CR24","doi-asserted-by":"publisher","first-page":"801","DOI":"10.1046\/j.1523-1739.1998.97140.x","volume":"12","author":"B.J. Swanson","year":"1998","unstructured":"Swanson, B.J.: Autocorrelated rates of change in animal populations and their relationship to precipitation. Conservation Biology\u00a012(4), 801\u2013808 (1998)","journal-title":"Conservation Biology"},{"key":"28_CR25","first-page":"99","volume-title":"Advances in Neural Information Processing Systems 1","author":"G. Tesauro","year":"1989","unstructured":"Tesauro, G.: Connectionist learning of expert preferences by comparison training. In: Advances in Neural Information Processing Systems 1, pp. 99\u2013106. Morgan Kaufmann Publishers Inc., San Francisco (1989)"},{"key":"28_CR26","unstructured":"Torgo, L.: Functional models for regression tree leaves. In: Fisher, D.H. (ed.) ICML, pp. 385\u2013393. Morgan Kaufmann (1997)"},{"key":"28_CR27","doi-asserted-by":"publisher","first-page":"226","DOI":"10.1145\/956750.956778","volume-title":"Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2003","author":"H. Wang","year":"2003","unstructured":"Wang, H., Fan, W., Yu, P.S., Han, J.: Mining concept-drifting data streams using ensemble classifiers. In: Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2003, pp. 226\u2013235. ACM, New York (2003)"},{"key":"28_CR28","doi-asserted-by":"publisher","first-page":"736","DOI":"10.1145\/1150402.1150496","volume-title":"Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2006","author":"H. Wang","year":"2006","unstructured":"Wang, H., Yin, J., Pei, J., Yu, P.S., Yu, J.X.: Suppressing model overfitting in mining concept-drifting data streams. In: Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2006, pp. 736\u2013741. ACM, New York (2006)"},{"key":"28_CR29","unstructured":"Wang, Y., Witten, I.H.: Induction of model trees for predicting continuous classes. In: Poster papers of the 9th European Conference on Machine Learning. Springer (1997)"}],"container-title":["Lecture Notes in Computer Science","Database and Expert Systems Applications"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-642-32600-4_28.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,6]],"date-time":"2025-04-06T23:58:56Z","timestamp":1743983936000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-642-32600-4_28"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2012]]},"ISBN":["9783642325991","9783642326004"],"references-count":29,"URL":"https:\/\/doi.org\/10.1007\/978-3-642-32600-4_28","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2012]]}}}