{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,9]],"date-time":"2024-09-09T20:36:45Z","timestamp":1725914205057},"publisher-location":"Cham","reference-count":18,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319701356"},{"type":"electronic","value":"9783319701363"}],"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\/978-3-319-70136-3_46","type":"book-chapter","created":{"date-parts":[[2017,10,25]],"date-time":"2017-10-25T06:33:43Z","timestamp":1508913223000},"page":"434-442","source":"Crossref","is-referenced-by-count":0,"title":["The Abstraction for Trajectories with Different Numbers of Sampling Points"],"prefix":"10.1007","author":[{"given":"Peng","family":"Li","sequence":"first","affiliation":[]},{"given":"Qing","family":"Xu","sequence":"additional","affiliation":[]},{"given":"Hao","family":"Wei","sequence":"additional","affiliation":[]},{"given":"Yuejun","family":"Guo","sequence":"additional","affiliation":[]},{"given":"Xiaoxiao","family":"Luo","sequence":"additional","affiliation":[]},{"given":"Mateu","family":"Sbert","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2017,10,26]]},"reference":[{"issue":"48109\u20132122","key":"46_CR1","first-page":"12","volume":"1001","author":"VP Chakka","year":"2003","unstructured":"Chakka, V.P., Everspaugh, A.C., Patel, J.M.: Indexing large trajectory data sets with seti. Ann Arbor 1001(48109\u20132122), 12 (2003)","journal-title":"Ann Arbor"},{"key":"46_CR2","unstructured":"Zheng, Y.: Tutorial on location-based social networks. In: Proceedings of the 21st International Conference on World Wide Web, WWW, vol. 12 (2012)"},{"issue":"4","key":"46_CR3","doi-asserted-by":"crossref","first-page":"041113","DOI":"10.1117\/1.JEI.22.4.041113","volume":"22","author":"BT Morris","year":"2013","unstructured":"Morris, B.T., Trivedi, M.M.: Understanding vehicular traffic behavior from video: a survey of unsupervised approaches. J. Electron. Imaging 22(4), 041113 (2013)","journal-title":"J. Electron. Imaging"},{"key":"46_CR4","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"452","DOI":"10.1007\/978-3-319-26555-1_51","volume-title":"Neural Information Processing","author":"X Luo","year":"2015","unstructured":"Luo, X., Xu, Q., Guo, Y., Wei, H., Lv, Y.: Trajectory abstracting with group-based signal denoising. In: Arik, S., Huang, T., Lai, W.K., Liu, Q. (eds.) ICONIP 2015. LNCS, vol. 9491, pp. 452\u2013461. Springer, Cham (2015). doi:\n10.1007\/978-3-319-26555-1_51"},{"key":"46_CR5","unstructured":"Chakrabarti, S., Ester, M., Fayyad, U., Gehrke, J., Han, J., Morishita, S., Piatetsky-Shapiro, G., Wang, W.: Data mining curriculum: a proposal (version 1.0). Intensive Working Group of ACM SIGKDD Curriculum Committee (2006)"},{"key":"46_CR6","unstructured":"Christopher, C.: Encyclopaedia britannica: definition of data mining. Technical report (2010). Accessed 09 Dec 2010"},{"issue":"2","key":"46_CR7","first-page":"83","volume":"27","author":"T Hastie","year":"2005","unstructured":"Hastie, T., Tibshirani, R., Friedman, J., Franklin, J.: The elements of statistical learning: data mining, inference and prediction. Math. Intell. 27(2), 83\u201385 (2005)","journal-title":"Math. Intell."},{"key":"46_CR8","unstructured":"Ester, M., Kriegel, H.-P., Sander, J., Xu, X.: A density-based algorithm for discovering clusters in large spatial databases with noise. In: KDD 1996, pp. 226\u2013231 (1996)"},{"key":"46_CR9","doi-asserted-by":"crossref","unstructured":"Ankerst, M., Breunig, M.M., Kriegel, H.-P., Sander, J.: Optics: ordering points to identify the clustering structure. In: ACM SIGMOD Record, vol. 28, pp. 49\u201360. ACM (1999)","DOI":"10.1145\/304182.304187"},{"issue":"2","key":"46_CR10","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1109\/TIT.1982.1056489","volume":"28","author":"S Lloyd","year":"1982","unstructured":"Lloyd, S.: Least squares quantization in PCM. IEEE Trans. Inf. Theory 28(2), 129\u2013137 (1982)","journal-title":"IEEE Trans. Inf. Theory"},{"key":"46_CR11","unstructured":"Wang, W., Yang, J., Muntz, R., et al.: Sting: a statistical information grid approach to spatial data mining. In: VLDB 1997, pp. 186\u2013195 (1997)"},{"issue":"3","key":"46_CR12","doi-asserted-by":"crossref","first-page":"645","DOI":"10.1109\/TNN.2005.845141","volume":"16","author":"X Rui","year":"2005","unstructured":"Rui, X., Wunsch, D., et al.: Survey of clustering algorithms. IEEE Trans. Neural Netw. 16(3), 645\u2013678 (2005)","journal-title":"IEEE Trans. Neural Netw."},{"key":"46_CR13","doi-asserted-by":"crossref","unstructured":"Zheng, Y., Li, Q., Chen, Y., Xie, X., Ma, W.-Y.: Understanding mobility based on GPS data. In: Proceedings of the 10th International Conference on Ubiquitous Computing, pp. 312\u2013321. ACM (2008)","DOI":"10.1145\/1409635.1409677"},{"issue":"2","key":"46_CR14","first-page":"32","volume":"33","author":"Y Zheng","year":"2010","unstructured":"Zheng, Y., Xie, X., Ma, W.-Y.: Geolife: a collaborative social networking service among user, location and trajectory. IEEE Data Eng. Bull. 33(2), 32\u201339 (2010)","journal-title":"IEEE Data Eng. Bull."},{"key":"46_CR15","doi-asserted-by":"crossref","unstructured":"Zheng, Y., Zhang, L., Xie, X., Ma, W.-Y.: Mining interesting locations and travel sequences from GPS trajectories. In: Proceedings of the 18th International Conference on World Wide Web, pp. 791\u2013800. ACM (2009)","DOI":"10.1145\/1526709.1526816"},{"issue":"11","key":"46_CR16","doi-asserted-by":"crossref","first-page":"1555","DOI":"10.1109\/TCSVT.2008.2005603","volume":"18","author":"N Anjum","year":"2008","unstructured":"Anjum, N., Cavallaro, A.: Multifeature object trajectory clustering for video analysis. IEEE Trans. Circ. Syst. Video Technol. 18(11), 1555\u20131564 (2008)","journal-title":"IEEE Trans. Circ. Syst. Video Technol."},{"issue":"11","key":"46_CR17","doi-asserted-by":"crossref","first-page":"1544","DOI":"10.1109\/TCSVT.2008.2005599","volume":"18","author":"C Piciarelli","year":"2008","unstructured":"Piciarelli, C., Micheloni, C., Foresti, G.L.: Trajectory-based anomalous event detection. IEEE Trans. Circ. Syst. Video Technol. 18(11), 1544\u20131554 (2008)","journal-title":"IEEE Trans. Circ. Syst. Video Technol."},{"issue":"11","key":"46_CR18","doi-asserted-by":"crossref","first-page":"2287","DOI":"10.1109\/TPAMI.2011.64","volume":"33","author":"BT Morris","year":"2011","unstructured":"Morris, B.T., Trivedi, M.M.: Trajectory learning for activity understanding: unsupervised, multilevel, and long-term adaptive approach. IEEE Trans. Pattern Anal. Mach. Intell. 33(11), 2287\u20132301 (2011)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."}],"container-title":["Lecture Notes in Computer Science","Neural Information Processing"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-70136-3_46","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2017,10,25]],"date-time":"2017-10-25T06:44:35Z","timestamp":1508913875000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-70136-3_46"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017]]},"ISBN":["9783319701356","9783319701363"],"references-count":18,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-70136-3_46","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2017]]}}}