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|Title:||Finding closed MEMOs||Authors:||Aung, H.H.
|Issue Date:||2011||Citation:||Aung, H.H.,Tan, K.-L. (2011). Finding closed MEMOs. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 6809 LNCS : 369-386. ScholarBank@NUS Repository. https://doi.org/10.1007/978-3-642-22351-8_23||Abstract:||Current literature lacks a thorough study on the discovery of meeting patterns in moving object datasets. We (a) introduced MEMO, a more precise definition of meeting patterns, (b) proposed three new algorithms based on a novel data-driven approach to extract closed MEMOs from moving object datasets and (c) implemented and evaluated them along with the algorithm previously reported in , whose performance has never been evaluated. Experiments using real-world datasets revealed that our filter-and-refinement algorithm outperforms the others in many realistic settings. © 2011 Springer-Verlag Berlin Heidelberg.||Source Title:||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)||URI:||http://scholarbank.nus.edu.sg/handle/10635/41238||ISBN:||9783642223501||ISSN:||03029743||DOI:||10.1007/978-3-642-22351-8_23|
|Appears in Collections:||Staff Publications|
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