{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,30]],"date-time":"2025-06-30T13:43:37Z","timestamp":1751291017347},"publisher-location":"Cham","reference-count":28,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319623917"},{"type":"electronic","value":"9783319623924"}],"license":[{"start":{"date-parts":[[2017,1,1]],"date-time":"2017-01-01T00:00:00Z","timestamp":1483228800000},"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":[[2017]]},"DOI":"10.1007\/978-3-319-62392-4_14","type":"book-chapter","created":{"date-parts":[[2017,7,5]],"date-time":"2017-07-05T02:34:09Z","timestamp":1499222049000},"page":"188-202","source":"Crossref","is-referenced-by-count":7,"title":["Intelligent Twitter Data Analysis Based on Nonnegative Matrix Factorizations"],"prefix":"10.1007","author":[{"given":"Gabriella","family":"Casalino","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ciro","family":"Castiello","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nicoletta","family":"Del Buono","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Corrado","family":"Mencar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2017,7,6]]},"reference":[{"key":"14_CR1","doi-asserted-by":"crossref","unstructured":"Gupta, A., Joshi, A., Kumaraguru, P.: Identifying and characterizing user communities on Twitter during crisis events. In: Proceedings of the 2012 Workshop on Data-Driven User Behavioral Modelling and Mining from Social Media, DUBMMSM 2012, pp. 23\u201326. ACM, New York (2012)","DOI":"10.1145\/2390131.2390142"},{"issue":"8","key":"14_CR2","doi-asserted-by":"crossref","first-page":"2158","DOI":"10.1109\/TKDE.2016.2553667","volume":"28","author":"FMF Wong","year":"2016","unstructured":"Wong, F.M.F., Tan, C.W., Sen, S., Chiang, M.: Quantifying political leaning from tweets, retweets, and retweeters. IEEE Trans. Knowl. Data Eng. 28(8), 2158\u20132172 (2016)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"issue":"9","key":"14_CR3","doi-asserted-by":"crossref","first-page":"144","DOI":"10.1109\/MCOM.2013.6588663","volume":"51","author":"L Jin","year":"2013","unstructured":"Jin, L., Chen, Y., Wang, T., Hui, P., Vasilakos, A.V.: Understanding user behavior in online social networks: a survey. IEEE Commun. Mag. 51(9), 144\u2013150 (2013)","journal-title":"IEEE Commun. Mag."},{"key":"14_CR4","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4614-3223-4","volume-title":"Mining Text Data","author":"CC Aggarwal","year":"2012","unstructured":"Aggarwal, C.C., Zhai, C.: Mining Text Data. Springer Science & Business Media, New York (2012)"},{"issue":"6755","key":"14_CR5","doi-asserted-by":"crossref","first-page":"788","DOI":"10.1038\/44565","volume":"401","author":"DD Lee","year":"1999","unstructured":"Lee, D.D., Seung, H.S.: Learning the parts of objects by non-negative matrix factorization. Nature 401(6755), 788\u2013791 (1999)","journal-title":"Nature"},{"key":"14_CR6","series-title":"Machine Learning and Pattern Recognition Series","volume-title":"Regularization, Optimization, Kernels, and Support Vector Machines","author":"N Gillis","year":"2014","unstructured":"Gillis, N.: The why and how of nonnegative matrix factorization. In: Signoretto, M., Suykens, J.A.K., Argyriou, A. (eds.) Regularization, Optimization, Kernels, and Support Vector Machines. Machine Learning and Pattern Recognition Series. Chapman and Hall\/CRC, Boca Raton (2014)"},{"key":"14_CR7","series-title":"Signals and Communication Technology","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1007\/978-3-662-48331-2_2","volume-title":"Non-negative Matrix Factorization Techniques","author":"G Casalino","year":"2016","unstructured":"Casalino, G., Del Buono, N., Mencar, C.: Nonnegative matrix factorizations for intelligent data analysis. In: Naik, G.R. (ed.) Non-negative Matrix Factorization Techniques. SCT, pp. 49\u201374. Springer, Heidelberg (2016). doi: 10.1007\/978-3-662-48331-2_2"},{"key":"14_CR8","first-page":"15:1","volume":"2012","author":"G Casalino","year":"2012","unstructured":"Casalino, G., Del Buono, N., Minervini, M.: Nonnegative matrix factorizations performing object detection and localization. Appl. Comp. Intell. Soft Comput. 2012, 15:1\u201315:19 (2012)","journal-title":"Appl. Comp. Intell. Soft Comput."},{"key":"14_CR9","doi-asserted-by":"crossref","DOI":"10.1002\/9780470747278","volume-title":"Nonnegative Matrix and Tensor Factorizations: Applications to Exploratory Multi-way Data Analysis and Blind Source Separation","author":"A Cichocki","year":"2009","unstructured":"Cichocki, A., Zdunek, R., Phan, A.H., Amari, S.: Nonnegative Matrix and Tensor Factorizations: Applications to Exploratory Multi-way Data Analysis and Blind Source Separation. Wiley, Hoboken (2009)"},{"key":"14_CR10","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"281","DOI":"10.1007\/978-3-319-51469-7_24","volume-title":"Machine Learning, Optimization, and Big Data","author":"N Del Buono","year":"2016","unstructured":"Del Buono, N., Esposito, F., Fumarola, F., Boccarelli, A., Coluccia, M.: Breast cancer\u2019s microarray data: pattern discovery using nonnegative matrix factorizations. In: Pardalos, P.M., Conca, P., Giuffrida, G., Nicosia, G. (eds.) MOD 2016. LNCS, vol. 10122, pp. 281\u2013292. Springer, Cham (2016). doi: 10.1007\/978-3-319-51469-7_24"},{"key":"14_CR11","first-page":"8","volume":"2013","author":"Y-H Kim","year":"2013","unstructured":"Kim, Y.-H., Seo, S., Ha, Y.-H., Lim, S., Yoon, Y.: Two applications of clustering techniques to Twitter: community detection and issue extraction. Discret. Dyn. Nat. Soc. 2013, 8 (2013)","journal-title":"Discret. Dyn. Nat. Soc."},{"key":"14_CR12","doi-asserted-by":"crossref","unstructured":"Yan, X., Guo, J., Liu, S., Cheng, X., Wang, Y.: Learning topics in short texts by non-negative matrix factorization on term correlation matrix. In: Proceedings of the SIAM International Conference on Data Mining SIAM 2013, pp. 749\u2013757 (2013)","DOI":"10.1137\/1.9781611972832.83"},{"issue":"9","key":"14_CR13","first-page":"8","volume":"6","author":"AZ Arifin","year":"2014","unstructured":"Arifin, A.Z., Sari, Y.A., Ratnasari, E.K., Mutrofinn, S.: Emotion detection of tweets in Indonesian language using non-negative matrix factorization. Int. J. Intell. Syst. Appl. 6(9), 8 (2014)","journal-title":"Int. J. Intell. Syst. Appl."},{"key":"14_CR14","doi-asserted-by":"crossref","unstructured":"Saha, A., Sindhwani, V.: Learning evolving and emerging topics in social media: a dynamic NMF approach with temporal regularization. In: Proceedings of the Fifth ACM International Conference on Web Search and Data Mining, WSDM 2012, pp. 693\u2013702. ACM, New York (2012)","DOI":"10.1145\/2124295.2124376"},{"key":"14_CR15","unstructured":"Godfrey, D., Johns, C., Sadek, C., Meyer, C., Race, S.: A case study in text mining: interpreting Twitter data from world cup tweets (2014)"},{"key":"14_CR16","doi-asserted-by":"publisher","first-page":"219","DOI":"10.1007\/978-3-662-43505-2_14","volume-title":"Springer Handbook of Computational Intelligence","author":"JM Alonso","year":"2015","unstructured":"Alonso, J.M., Castiello, C., Mencar, C.: Interpretability of fuzzy systems: current research trends and prospects. In: Kacprzyk, J., Pedrycz, W. (eds.) Springer Handbook of Computational Intelligence, pp. 219\u2013237. Springer, Heidelberg (2015). doi: 10.1007\/978-3-662-43505-2_14"},{"key":"14_CR17","doi-asserted-by":"crossref","first-page":"369","DOI":"10.1016\/j.ins.2013.05.038","volume":"257","author":"G Casalino","year":"2014","unstructured":"Casalino, G., Del Buono, N., Mencar, C.: Subtractive clustering for seeding non-negative matrix factorizations. Inf. Sci. 257, 369\u2013387 (2014)","journal-title":"Inf. Sci."},{"issue":"1","key":"14_CR18","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1016\/j.csda.2006.11.006","volume":"52","author":"M Berry","year":"2007","unstructured":"Berry, M., Browne, M., Langville, A., Pauca, P., Plemmons, R.: Algorithms and applications for approximate nonnegative matrix factorization. Comput. Stat. Data Anal. 52(1), 155\u2013173 (2007)","journal-title":"Comput. Stat. Data Anal."},{"key":"14_CR19","first-page":"556","volume-title":"Advances in Neural Information Processing Systems 13","author":"DD Lee","year":"2001","unstructured":"Lee, D.D., Seung, H.S.: Algorithms for non-negative matrix factorization. In: Leen, T.K., Dietterich, T.G., Tresp, V. (eds.) Advances in Neural Information Processing Systems 13, pp. 556\u2013562. MIT Press, Cambridge (2001)"},{"issue":"10","key":"14_CR20","doi-asserted-by":"crossref","first-page":"2756","DOI":"10.1162\/neco.2007.19.10.2756","volume":"19","author":"C-J Lin","year":"2007","unstructured":"Lin, C.-J.: Projected gradient methods for nonnegative matrix factorization. Neural Comput. 19(10), 2756\u20132779 (2007)","journal-title":"Neural Comput."},{"issue":"12","key":"14_CR21","doi-asserted-by":"crossref","first-page":"1495","DOI":"10.1093\/bioinformatics\/btm134","volume":"23","author":"H Kim","year":"2007","unstructured":"Kim, H., Park, H.: Sparse non-negative matrix factorizations via alternating non-negativity-constrained least squares for microarray data analysis. Bioinformatics 23(12), 1495\u20131502 (2007)","journal-title":"Bioinformatics"},{"issue":"3","key":"14_CR22","doi-asserted-by":"crossref","first-page":"403","DOI":"10.1109\/TPAMI.2006.60","volume":"28","author":"A Pascual-Montano","year":"2006","unstructured":"Pascual-Montano, A., Carazo, J.M., Kochi, K., Lehmann, D., Pascual-Marqui, R.D.: Nonsmooth nonnegative matrix factorization (nsNMF). IEEE Trans. Pattern Anal. Mach. Intell. 28(3), 403\u2013415 (2006)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"14_CR23","unstructured":"Albright, R., Cox, J., Duling, D., Langville, A., Meyer, C.: Algorithms, initializations, and convergence for the nonnegative matrix factorization. Technical report, NCSU Technical Report Math 81706 (2006)"},{"key":"14_CR24","doi-asserted-by":"crossref","first-page":"1350","DOI":"10.1016\/j.patcog.2007.09.010","volume":"41","author":"C Boutsidis","year":"2008","unstructured":"Boutsidis, C., Gallopoulos, E.: SVD based initialization: a head start for nonnegative matrix factorization. Pattern Recogn. 41, 1350\u20131362 (2008)","journal-title":"Pattern Recogn."},{"key":"14_CR25","doi-asserted-by":"crossref","unstructured":"Xu, W., Liu, X., Gong, Y.: Document clustering based on non-negative matrix factorization. In: Proceedings of the 26th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2003, pp. 267\u2013273. ACM, New York (2003)","DOI":"10.1145\/860435.860485"},{"issue":"2","key":"14_CR26","doi-asserted-by":"crossref","first-page":"373","DOI":"10.1016\/j.ipm.2004.11.005","volume":"42","author":"F Shahnaz","year":"2006","unstructured":"Shahnaz, F., Berry, M.W., Pauca, V.P., Plemmons, R.J.: Document clustering using nonnegative matrix factorization. Inf. Process. Manag. 42(2), 373\u2013386 (2006)","journal-title":"Inf. Process. Manag."},{"key":"14_CR27","doi-asserted-by":"crossref","unstructured":"Ding, C., He, X., Simon, H.D.: On the equivalence of nonnegative matrix factorization and k-means - spectral clustering. In: Proceedings of the SIAM Data Mining Conference, pp. 606\u2013610. SIAM (2005)","DOI":"10.1137\/1.9781611972757.70"},{"key":"14_CR28","unstructured":"Rosenberg, A., Hirschberg, J.: V-measure: a conditional entropy-based external cluster evaluation measure. In: Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL), pp. 410\u2013420 (2007)"}],"container-title":["Lecture Notes in Computer Science","Computational Science and Its Applications \u2013 ICCSA 2017"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-62392-4_14","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,9,28]],"date-time":"2019-09-28T13:25:24Z","timestamp":1569677124000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-62392-4_14"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017]]},"ISBN":["9783319623917","9783319623924"],"references-count":28,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-62392-4_14","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2017]]}}}