{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T09:11:07Z","timestamp":1743066667738,"version":"3.40.3"},"publisher-location":"Cham","reference-count":23,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319417059"},{"type":"electronic","value":"9783319417066"}],"license":[{"start":{"date-parts":[[2016,1,1]],"date-time":"2016-01-01T00:00:00Z","timestamp":1451606400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016]]},"DOI":"10.1007\/978-3-319-41706-6_19","type":"book-chapter","created":{"date-parts":[[2016,7,2]],"date-time":"2016-07-02T11:54:11Z","timestamp":1467460451000},"page":"346-361","source":"Crossref","is-referenced-by-count":0,"title":["Supervised Extraction of Usage Patterns in Different Document Representations"],"prefix":"10.1007","author":[{"given":"Christian","family":"P\u00f6litz","sequence":"first","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2016,7,3]]},"reference":[{"key":"19_CR1","unstructured":"Blei, D.M., McAuliffe, J.D.: Supervised topic models. In: Advances in Neural Information Processing Systems 20, Proceedings of the Twenty-First Annual Conference on Neural Information Processing Systems, Vancouver, 3\u20136 December 2007, pp. 121\u2013128 (2007). http:\/\/papers.nips.cc\/paper\/3328-supervised-topic-models"},{"key":"19_CR2","first-page":"993","volume":"3","author":"DM Blei","year":"2003","unstructured":"Blei, D.M., Ng, A.Y., Jordan, M.I.: Latent dirichlet allocation. J. Mach. Learn. Res. 3, 993\u20131022 (2003)","journal-title":"J. Mach. Learn. Res."},{"key":"19_CR3","unstructured":"Blitzer, J., Dredze, M., Pereira, F.: Biographies, bollywood, boom-boxes and blenders: domain adaptation for sentiment classification. In: Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics, pp. 440\u2013447. Association for Computational Linguistics, Prague (June 2007)"},{"issue":"6","key":"19_CR4","doi-asserted-by":"crossref","first-page":"391","DOI":"10.1002\/(SICI)1097-4571(199009)41:6<391::AID-ASI1>3.0.CO;2-9","volume":"41","author":"S Deerwester","year":"1990","unstructured":"Deerwester, S., Dumais, S.T., Furnas, G.W., Landauer, T.K., Harshman, R.: Indexing by latent semantic analysis. J. Am. Soc. Inform. Sci. Technol. 41(6), 391\u2013407 (1990)","journal-title":"J. Am. Soc. Inform. Sci. Technol."},{"issue":"Suppl. 1","key":"19_CR5","doi-asserted-by":"crossref","first-page":"5228","DOI":"10.1073\/pnas.0307752101","volume":"101","author":"TL Griffiths","year":"2004","unstructured":"Griffiths, T.L., Steyvers, M.: Finding scientific topics. Proc. Nat. Acad. Sci. 101(Suppl. 1), 5228\u20135235 (2004)","journal-title":"Proc. Nat. Acad. Sci."},{"key":"19_CR6","doi-asserted-by":"crossref","unstructured":"Hotelling, H.: Analysis of a complex of statistical variables into principal components (1933)","DOI":"10.1037\/h0071325"},{"issue":"3","key":"19_CR7","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1007\/BF02289233","volume":"23","author":"H Kaiser","year":"1958","unstructured":"Kaiser, H.: The varimax criterion for analytic rotation in factor analysis. Psychometrika 23(3), 187\u2013200 (1958). http:\/\/dx.doi.org\/10.1007\/BF02289233","journal-title":"Psychometrika"},{"key":"19_CR8","unstructured":"Lee, D.D., Seung, H.S.: Algorithms for non-negative matrix factorization. In: NIPS, pp. 556\u2013562 (2000). citeseer.ist.psu.edu\/lee01algorithms.html"},{"key":"19_CR9","unstructured":"Liu, H., Wu, Z.: Non-negative matrix factorization with constraints (2010). https:\/\/www.aaai.org\/ocs\/index.php\/AAAI\/AAAI10\/paper\/view\/1820\/2027"},{"key":"19_CR10","doi-asserted-by":"crossref","DOI":"10.1017\/CBO9780511809071","volume-title":"Introduction to Information Retrieval","author":"CD Manning","year":"2008","unstructured":"Manning, C.D., Raghavan, P., Sch\u00fctze, H.: Introduction to Information Retrieval. Cambridge University Press, New York (2008)"},{"key":"19_CR11","doi-asserted-by":"crossref","first-page":"415","DOI":"10.1098\/rsta.1909.0016","volume":"209","author":"J Mercer","year":"1909","unstructured":"Mercer, J.: Functions of positive and negative type, and their connection with the theory of integral equations. Philos. Trans. R. Soc. Lond. 209, 415\u2013446 (1909)","journal-title":"Philos. Trans. R. Soc. Lond."},{"key":"19_CR12","unstructured":"Mimno, D.M., McCallum, A.: Topic models conditioned on arbitrary features with dirichlet-multinomial regression. CoRR abs\/1206.3278 (2012). http:\/\/arxiv.org\/abs\/1206.3278"},{"key":"19_CR13","unstructured":"Nguyen, V.A., Boyd-Graber, J., Resnik, P.: Sometimes average is best: the importance of averaging for prediction using mcmc inference in topic modeling. In: Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 1752\u20131757. Association for Computational Linguistics (2014). http:\/\/aclweb.org\/anthology\/D14-1182"},{"key":"19_CR14","doi-asserted-by":"crossref","unstructured":"Ramage, D., Hall, D., Nallapati, R., Manning, C.D.: Labeled lda: a supervised topic model for credit attribution in multi-labeled corpora. In: Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing, EMNLP 2009, vol. 1, pp. 248\u2013256. Association for Computational Linguistics, Stroudsburg (2009). http:\/\/dl.acm.org\/citation.cfm?id=1699510.1699543","DOI":"10.3115\/1699510.1699543"},{"issue":"5","key":"19_CR15","doi-asserted-by":"crossref","first-page":"503","DOI":"10.1108\/00220410410560582","volume":"60","author":"S Robertson","year":"2004","unstructured":"Robertson, S.: Understanding inverse document frequency: on theoretical arguments for idf. J. Documentation 60(5), 503\u2013520 (2004). http:\/\/dx.doi.org\/10.1108\/00220410410560582","journal-title":"J. Documentation"},{"key":"19_CR16","first-page":"97","volume":"2","author":"R Rosipal","year":"2002","unstructured":"Rosipal, R., Trejo, L.J.: Kernel partial least squares regression in reproducing kernel hilbert space. J. Mach. Learn. Res. 2, 97\u2013123 (2002). http:\/\/dl.acm.org\/citation.cfm?id=944790.944806","journal-title":"J. Mach. Learn. Res."},{"key":"19_CR17","volume-title":"Real and Complex Analysis","author":"W Rudin","year":"1987","unstructured":"Rudin, W.: Real and Complex Analysis, 3rd edn. McGraw-Hill Inc., New York (1987)","edition":"3"},{"key":"19_CR18","unstructured":"Sch\u00f6lkopf, B., Smola, A.J., M\u00fcller, K.R.: Advances in kernel methods. In: Kernel Principal Component Analysis, pp. 327\u2013352. MIT Press, Cambridge (1999). http:\/\/dl.acm.org\/citation.cfm?id=299094.299113"},{"key":"19_CR19","doi-asserted-by":"crossref","DOI":"10.1017\/CBO9780511809682","volume-title":"Kernel Methods for Pattern Analysis","author":"J Shawe-Taylor","year":"2004","unstructured":"Shawe-Taylor, J., Cristianini, N.: Kernel Methods for Pattern Analysis. Cambridge University Press, New York (2004)"},{"key":"19_CR20","doi-asserted-by":"crossref","unstructured":"Yu, K., Yu, S., Tresp, V.: Multi-label informed latent semantic indexing. In: Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2005, pp. 258\u2013265. ACM, New York (2005). http:\/\/doi.acm.org\/10.1145\/1076034.1076080","DOI":"10.1145\/1076034.1076080"},{"key":"19_CR21","doi-asserted-by":"crossref","unstructured":"Zeng, X.Q., Wang, M.W., Nie, J.Y.: Text classification based on partial least square analysis. In: Proceedings of the 2007 ACM Symposium on Applied Computing, SAC 2007, pp. 834\u2013838. ACM, New York (2007). http:\/\/doi.acm.org\/10.1145\/1244002.1244187","DOI":"10.1145\/1244002.1244187"},{"key":"19_CR22","unstructured":"Zhu, J., Ahmed, A., Xing, E.P.: Medlda: maximum margin supervised topic models for regression and classification. In: Proceedings of the 26th Annual International Conference on Machine Learning, pp. 1257\u20131264, ICML 2009. ACM, New York (2009). http:\/\/doi.acm.org\/10.1145\/1553374.1553535"},{"key":"19_CR23","unstructured":"Zhu, J., Chen, N., Perkins, H., Zhang, B.: Gibbs max-margin topic models with fast sampling algorithms. In: ICML (1). JMLR Proceedings, vol. 28, pp. 124\u2013132. JMLR.org (2013). http:\/\/dblp.uni-trier.de\/db\/conf\/icml\/icml2013.htmlZhuCPZ13"}],"container-title":["Lecture Notes in Computer Science","Solving Large Scale Learning Tasks. Challenges and Algorithms"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-41706-6_19","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,9,10]],"date-time":"2019-09-10T12:13:41Z","timestamp":1568117621000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-41706-6_19"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016]]},"ISBN":["9783319417059","9783319417066"],"references-count":23,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-41706-6_19","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2016]]}}}