{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T00:58:35Z","timestamp":1740099515412,"version":"3.37.3"},"publisher-location":"Cham","reference-count":14,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030304898"},{"type":"electronic","value":"9783030304904"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-3-030-30490-4_46","type":"book-chapter","created":{"date-parts":[[2019,9,8]],"date-time":"2019-09-08T23:02:47Z","timestamp":1567983767000},"page":"569-580","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Soft Subspace Growing Neural Gas for Data Stream Clustering"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3117-9018","authenticated-orcid":false,"given":"Mohammed Oualid","family":"Attaoui","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mustapha","family":"Lebbah","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nabil","family":"Keskes","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hanene","family":"Azzag","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohammed","family":"Ghesmoune","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,9,9]]},"reference":[{"key":"46_CR1","doi-asserted-by":"publisher","first-page":"158","DOI":"10.1016\/j.procs.2015.07.290","volume":"53","author":"M Ghesmoune","year":"2015","unstructured":"Ghesmoune, M., Lebbah, M., Azzag, H.: Micro-batching growing neural gas for clustering data streams using spark streaming. Procedia Comput. Sci. 53, 158\u2013166 (2015)","journal-title":"Procedia Comput. Sci."},{"key":"46_CR2","doi-asserted-by":"crossref","unstructured":"Ntoutsi, I., Zimek, A., Palpanas, T., Kr\u00f6ger, P., Kriegel, H.P.: Density-based projected clustering over high dimensional data streams. In: Proceedings of the 2012 SIAM International Conference on Data Mining, SIAM, pp. 987\u2013998 (2012)","DOI":"10.1137\/1.9781611972825.85"},{"key":"46_CR3","doi-asserted-by":"crossref","unstructured":"Ren, J., Ma, R.: Density-based data streams clustering over sliding windows. In: Sixth International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2009, vol. 5, pp. 248\u2013252. IEEE (2009)","DOI":"10.1109\/FSKD.2009.553"},{"issue":"2","key":"46_CR4","doi-asserted-by":"crossref","first-page":"1478","DOI":"10.48084\/etasr.963","volume":"7","author":"M Shukla","year":"2017","unstructured":"Shukla, M., Kosta, Y.P., Jayswal, M.: A modified approach of optics algorithm for data streams. Eng. Technol. Appl. Sci. Res. 7(2), 1478\u20131481 (2017)","journal-title":"Eng. Technol. Appl. Sci. Res."},{"key":"46_CR5","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"824","DOI":"10.1007\/11527503_97","volume-title":"Advanced Data Mining and Applications","author":"Y Lu","year":"2005","unstructured":"Lu, Y., Sun, Y., Xu, G., Liu, G.: A grid-based clustering algorithm for high-dimensional data streams. In: Li, X., Wang, S., Dong, Z.Y. (eds.) ADMA 2005. LNCS (LNAI), vol. 3584, pp. 824\u2013831. Springer, Heidelberg (2005). https:\/\/doi.org\/10.1007\/11527503_97"},{"key":"46_CR6","doi-asserted-by":"publisher","first-page":"34","DOI":"10.1016\/j.neucom.2016.01.009","volume":"191","author":"I Khan","year":"2016","unstructured":"Khan, I., Huang, J.Z., Ivanov, K.: Incremental density-based ensemble clustering over evolving data streams. Neurocomputing 191, 34\u201343 (2016)","journal-title":"Neurocomputing"},{"key":"46_CR7","doi-asserted-by":"publisher","first-page":"84","DOI":"10.1016\/j.ins.2016.01.101","volume":"348","author":"Z Deng","year":"2016","unstructured":"Deng, Z., Choi, K.-S., Jiang, Y., Wang, J., Wang, S.: A survey on soft subspace clustering. Inf. Sci. 348, 84\u2013106 (2016)","journal-title":"Inf. Sci."},{"issue":"4","key":"46_CR8","doi-asserted-by":"publisher","first-page":"815","DOI":"10.1111\/j.1467-9868.2004.02059.x","volume":"66","author":"JH Friedman","year":"2004","unstructured":"Friedman, J.H., Meulman, J.J.: Clustering objects on subsets of attributes (with discussion). J. R. Stat. Soc.: Ser. B (Stat. Methodol.) 66(4), 815\u2013849 (2004)","journal-title":"J. R. Stat. Soc.: Ser. B (Stat. Methodol.)"},{"issue":"1\u20133","key":"46_CR9","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/S0925-2312(98)00030-7","volume":"21","author":"T Kohonen","year":"1998","unstructured":"Kohonen, T.: The self-organizing map. Neurocomputing 21(1\u20133), 1\u20136 (1998)","journal-title":"Neurocomputing"},{"key":"46_CR10","unstructured":"Ouattara, M., Keita, N.N., Badran, F., Mandin, C.: Soft subpace clustering pour donn\u00e9es multiblocs bas\u00e9e sur les cartes topologiques auto-organis\u00e9es som: 2s-som. In: SFDS 2013 (2013)"},{"issue":"1","key":"46_CR11","doi-asserted-by":"publisher","first-page":"434","DOI":"10.1016\/j.patcog.2011.06.004","volume":"45","author":"X Chen","year":"2012","unstructured":"Chen, X., Ye, Y., Xu, X., Huang, J.Z.: A feature group weighting method for subspace clustering of high-dimensional data. Pattern Recogn. 45(1), 434\u2013446 (2012)","journal-title":"Pattern Recogn."},{"key":"46_CR12","doi-asserted-by":"publisher","first-page":"36","DOI":"10.1016\/j.neunet.2016.02.003","volume":"78","author":"M Ghesmoune","year":"2016","unstructured":"Ghesmoune, M., Lebbah, M., Azzag, H.: A new growing neural gas for clustering data streams. Neural Netw. 78, 36\u201350 (2016)","journal-title":"Neural Netw."},{"key":"46_CR13","doi-asserted-by":"crossref","unstructured":"Zhu, Y., Shasha, D.: Statstream: statistical monitoring of thousands of data streams in real time. In VLDB 2002: Proceedings of the 28th International Conference on Very Large Databases, pp. 358\u2013369. Elsevier (2002). Work supported in part by US NSF grants IIS-9988345 and N2010: 0115586","DOI":"10.1016\/B978-155860869-6\/50039-1"},{"key":"46_CR14","unstructured":"Frank, A., Asuncion, A.: UCI machine learning repository. School of Information and Computer Science, University of California, Irvine, CA, p. 213 (2010). http:\/\/archive.ics.uci.edu\/ml"}],"container-title":["Lecture Notes in Computer Science","Artificial Neural Networks and Machine Learning \u2013 ICANN 2019: Text and Time Series"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-30490-4_46","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,1,19]],"date-time":"2021-01-19T02:44:42Z","timestamp":1611024282000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-30490-4_46"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030304898","9783030304904"],"references-count":14,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-30490-4_46","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"9 September 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICANN","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Artificial Neural Networks","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Munich","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Germany","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 September 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19 September 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icann2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/e-nns.org\/icann2019\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}