Please use this identifier to cite or link to this item: https://doi.org/10.1007/978-3-642-22351-8_23
Title: Finding closed MEMOs
Authors: Aung, H.H.
Tan, K.-L. 
Issue Date: 2011
Source: 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 [6], 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
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