{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,3]],"date-time":"2025-05-03T04:12:03Z","timestamp":1746245523464,"version":"3.40.4"},"publisher-location":"Cham","reference-count":22,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319066042"},{"type":"electronic","value":"9783319066059"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2014]]},"DOI":"10.1007\/978-3-319-06605-9_25","type":"book-chapter","created":{"date-parts":[[2014,5,8]],"date-time":"2014-05-08T01:56:51Z","timestamp":1399514211000},"page":"296-310","source":"Crossref","is-referenced-by-count":1,"title":["Finding Better Topics: Features, Priors and Constraints"],"prefix":"10.1007","author":[{"given":"Xiaona","family":"Wu","sequence":"first","affiliation":[]},{"given":"Jia","family":"Zeng","sequence":"additional","affiliation":[]},{"given":"Jianfeng","family":"Yan","sequence":"additional","affiliation":[]},{"given":"Xiaosheng","family":"Liu","sequence":"additional","affiliation":[]}],"member":"297","reference":[{"key":"25_CR1","first-page":"993","volume":"3","author":"D.M. Blei","year":"2003","unstructured":"Blei, D.M., Ng, A.Y., Jordan, M.I.: Latent Dirichlet allocation. J. Mach. Learn. Res.\u00a03, 993\u20131022 (2003)","journal-title":"J. Mach. Learn. Res."},{"key":"25_CR2","doi-asserted-by":"publisher","first-page":"5228","DOI":"10.1073\/pnas.0307752101","volume":"101","author":"T.L. Griffiths","year":"2004","unstructured":"Griffiths, T.L., Steyvers, M.: Finding scientific topics. Proc. Natl. Acad. Sci.\u00a0101, 5228\u20135235 (2004)","journal-title":"Proc. Natl. Acad. Sci."},{"issue":"5","key":"25_CR3","doi-asserted-by":"publisher","first-page":"1121","DOI":"10.1109\/TPAMI.2012.185","volume":"33","author":"J. Zeng","year":"2013","unstructured":"Zeng, J., Cheung, W.K., Liu, J.: Learning topic models by belief propagation. IEEE Trans. Pattern Anal. Mach. Intell.\u00a033(5), 1121\u20131134 (2013)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"25_CR4","unstructured":"Chang, J., Boyd-Graber, J., Gerris, S., Wang, C., Blei, D.: Reading tea leaves: How humans interpret topic models. In: NIPS, pp. 288\u2013296 (2009)"},{"key":"25_CR5","unstructured":"Salton, G., McGill, M.J.: Introduction to modern information retrieval. McGraw-Hill, New York (1983)"},{"key":"25_CR6","doi-asserted-by":"crossref","unstructured":"Buckley, C.: Automatic query expansion using SMART: Trec 3. In: Proceedings of The Third Text REtrieval Conference (TREC-3), pp. 69\u201380 (1994)","DOI":"10.6028\/NIST.SP.500-225.adhoc-cornell"},{"key":"25_CR7","unstructured":"Hoffman, M., Blei, D., Bach, F.: Online learning for latent Dirichlet allocation. In: NIPS, pp. 856\u2013864 (2010)"},{"key":"25_CR8","doi-asserted-by":"crossref","unstructured":"Ramage, D., Heymann, P., Manning, C.D., Garcia-Molina, H.: Clustering the tagged web. In: Web Search and Data Mining, pp. 54\u201363 (2009)","DOI":"10.1145\/1498759.1498809"},{"key":"25_CR9","unstructured":"Wilson, A.T., Chew, P.A.: Term weighting schemes for latent Dirichlet allocation. In: North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 465\u2013473 (2010)"},{"key":"25_CR10","unstructured":"Minka, T.P.: Estimating a Dirichlet distribution. Technical report, Microsoft Research (2000)"},{"key":"25_CR11","unstructured":"Asuncion, A., Welling, M., Smyth, P., Teh, Y.W.: On smoothing and inference for topic models. In: UAI, pp. 27\u201334 (2009)"},{"key":"25_CR12","unstructured":"Wallach, H., Mimno, D., McCallum, A.: Rethinking LDA: Why priors matter. In: NIPS, pp. 1973\u20131981 (2009)"},{"key":"25_CR13","unstructured":"Zhu, J., Xing, E.P.: Sparse topical coding. In: UAI (2011)"},{"issue":"1","key":"25_CR14","doi-asserted-by":"publisher","first-page":"28","DOI":"10.1016\/j.neucom.2010.11.038","volume":"76","author":"W. Zhu","year":"2012","unstructured":"Zhu, W., Zhang, L., Bian, Q.: A hierarchical latent topic model based on sparse coding. Neurocomputing\u00a076(1), 28\u201335 (2012)","journal-title":"Neurocomputing"},{"key":"25_CR15","first-page":"1457","volume":"5","author":"P.O. Hoyer","year":"2004","unstructured":"Hoyer, P.O.: Non-negative matrix factorization with sparseness constraints. Journal of Machine Learning Research\u00a05, 1457\u20131469 (2004)","journal-title":"Journal of Machine Learning Research"},{"key":"25_CR16","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"739","DOI":"10.1007\/978-3-642-35527-1_61","volume-title":"Advanced Data Mining and Applications","author":"J. Zeng","year":"2012","unstructured":"Zeng, J., Cao, X.-Q., Liu, Z.-Q.: Residual belief propagation for topic modeling. In: Zhou, S., Zhang, S., Karypis, G. (eds.) ADMA 2012. LNCS, vol.\u00a07713, pp. 739\u2013752. Springer, Heidelberg (2012)"},{"key":"25_CR17","unstructured":"Zeng, J., Liu, Z.Q., Cao, X.Q.: A new approach to speeding up topic modeling, arXiv:1204.0170 [cs.LG] (2012)"},{"key":"25_CR18","unstructured":"Heinrich, G.: Parameter estimation for text analysis. Technical report, University of Leipzig (2008)"},{"issue":"3","key":"25_CR19","doi-asserted-by":"publisher","first-page":"374","DOI":"10.1007\/s10115-004-0194-1","volume":"8","author":"S. Zhong","year":"2005","unstructured":"Zhong, S., Ghosh, J.: Generative model-based document clustering: A comparative study. Knowl. Inf. Syst.\u00a08(3), 374\u2013384 (2005)","journal-title":"Knowl. Inf. Syst."},{"key":"25_CR20","unstructured":"Mimno, D.M., Wallach, H.M., Talley, E.M., Leenders, M., McCallum, A.: Optimizing semantic coherence in topic models. In: EMNLP, pp. 262\u2013272 (2011)"},{"key":"25_CR21","unstructured":"Newman, D., Karimi, S., Cavedon, L.: External evaluation of topic models. In: Australasian Document Computing Symposium, pp. 11\u201318 (2009)"},{"key":"25_CR22","first-page":"2233","volume":"13","author":"J. Zeng","year":"2012","unstructured":"Zeng, J.: TMBP: A topic modeling toolbox using belief propagation. J. Mach. Learn.Res.\u00a013, 2233\u20132236 (2012)","journal-title":"J. Mach. Learn.Res."}],"container-title":["Lecture Notes in Computer Science","Advances in Knowledge Discovery and Data Mining"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-06605-9_25","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,2]],"date-time":"2025-05-02T20:50:38Z","timestamp":1746219038000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-06605-9_25"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014]]},"ISBN":["9783319066042","9783319066059"],"references-count":22,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-06605-9_25","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2014]]}}}