dc.contributor.author | Zeinalipour-Yazdi, Constantinos D. | en |
dc.contributor.author | Lin, S. | en |
dc.contributor.author | Gunopulos, Dimitrios | en |
dc.creator | Zeinalipour-Yazdi, Constantinos D. | en |
dc.creator | Lin, S. | en |
dc.creator | Gunopulos, Dimitrios | en |
dc.date.accessioned | 2019-11-13T10:43:04Z | |
dc.date.available | 2019-11-13T10:43:04Z | |
dc.date.issued | 2006 | |
dc.identifier.isbn | 1-59593-433-2 | |
dc.identifier.isbn | 978-1-59593-433-8 | |
dc.identifier.uri | http://gnosis.library.ucy.ac.cy/handle/7/55191 | |
dc.description.abstract | In this paper we introduce the distributed spatio-temporal similarity search problem: given a query trajectory Q, we want to find the trajectories that follow a motion similar to Q, when each of the target trajectories is segmented across a number of distributed nodes. We propose two novel algorithms, UB-K and UBLB-K, which combine local computations of lower and upper bounds on the matching between the distributed subsequences and Q. Such an operation generates the desired result without pulling together all the distributed subsequences over the fundamentally expensive communication medium. Our solutions find applications in a wide array of domains, such as cellular networks, wild life monitoring and video surveillance. Our experimental evaluation using realistic data demonstrates that our framework is both efficient and robust to a variety of conditions. Copyright 2006 ACM. | en |
dc.source | International Conference on Information and Knowledge Management, Proceedings | en |
dc.source | 15th ACM Conference on Information and Knowledge Management, CIKM 2006 | en |
dc.source.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-34547620671&doi=10.1145%2f1183614.1183621&partnerID=40&md5=fcf1c754248acf95bb5124167a90e0b5 | |
dc.subject | Problem solving | en |
dc.subject | Computational methods | en |
dc.subject | Algorithms | en |
dc.subject | Upper bounds | en |
dc.subject | Robust control | en |
dc.subject | Query processing | en |
dc.subject | Spatio-temporal similarity search | en |
dc.subject | Top-K query processing | en |
dc.subject | Wild life | en |
dc.title | Distributed spatio-temporal similarity search | en |
dc.type | info:eu-repo/semantics/conferenceObject | |
dc.identifier.doi | 10.1145/1183614.1183621 | |
dc.description.startingpage | 14 | |
dc.description.endingpage | 23 | |
dc.author.faculty | 002 Σχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied Sciences | |
dc.author.department | Τμήμα Πληροφορικής / Department of Computer Science | |
dc.type.uhtype | Conference Object | en |
dc.description.notes | <p>Sponsors: ACM Special Interest Group on Information Retrieval, SIGIR | en |
dc.description.notes | ACM Special Interest Group on Hypertext, Hypermedia, and Web | en |
dc.description.notes | Conference code: 70026 | en |
dc.description.notes | Cited By :23</p> | en |
dc.contributor.orcid | Zeinalipour-Yazdi, Constantinos D. [0000-0002-8388-1549] | |
dc.gnosis.orcid | 0000-0002-8388-1549 | |