Attraction and avoidance detection from movements

Cite This

Files in this item

Files Size Format View

There are no files associated with this item.

LI, Zhenhui, Bolin DING, Fei WU, Tobias Kin Hou LEI, Roland KAYS, Margaret C. CROFOOT, 2013. Attraction and avoidance detection from movements. 39th International Conference on Very Large Data Bases : VLDB Endowment. Trento, Italy, Aug 26, 2013 - Aug 30, 2013. In: JAGADISH, H. V., ed., Aoying ZHOU, ed.. Proceedings of the VLDB Endowment. New York, NY, USA:ACM, pp. 157-168. ISSN 2150-8097. Available under: doi: 10.14778/2732232.2732235

@inproceedings{Li2013Attra-47697, title={Attraction and avoidance detection from movements}, year={2013}, doi={10.14778/2732232.2732235}, number={7 (3)}, issn={2150-8097}, address={New York, NY, USA}, publisher={ACM}, series={Proceedings of the VLDB Endowment}, booktitle={Proceedings of the VLDB Endowment}, pages={157--168}, editor={Jagadish, H. V. and Zhou, Aoying}, author={Li, Zhenhui and Ding, Bolin and Wu, Fei and Lei, Tobias Kin Hou and Kays, Roland and Crofoot, Margaret C.} }

<rdf:RDF xmlns:dcterms="" xmlns:dc="" xmlns:rdf="" xmlns:bibo="" xmlns:dspace="" xmlns:foaf="" xmlns:void="" xmlns:xsd="" > <rdf:Description rdf:about=""> <dc:contributor>Crofoot, Margaret C.</dc:contributor> <dcterms:available rdf:datatype="">2019-11-28T10:28:04Z</dcterms:available> <dcterms:issued>2013</dcterms:issued> <dcterms:title>Attraction and avoidance detection from movements</dcterms:title> <dc:language>eng</dc:language> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> <dc:creator>Wu, Fei</dc:creator> <bibo:uri rdf:resource=""/> <dc:contributor>Wu, Fei</dc:contributor> <dc:creator>Crofoot, Margaret C.</dc:creator> <dc:date rdf:datatype="">2019-11-28T10:28:04Z</dc:date> <dspace:isPartOfCollection rdf:resource=""/> <dc:contributor>Kays, Roland</dc:contributor> <foaf:homepage rdf:resource="http://localhost:8080/jspui"/> <dc:creator>Lei, Tobias Kin Hou</dc:creator> <dc:contributor>Ding, Bolin</dc:contributor> <dc:contributor>Lei, Tobias Kin Hou</dc:contributor> <dcterms:abstract xml:lang="eng">With the development of positioning technology, movement data has become widely available nowadays. An important task in movement data analysis is to mine the relationships among moving objects based on their spatiotemporal interactions. Among all relationship types, attraction and avoidance are arguably the most natural ones. However, rather surprisingly, there is no existing method that addresses the problem of mining significant attraction and avoidance relationships in a well-defined and unified framework. In this paper, we propose a novel method to measure the significance value of relationship between any two objects by examining the background model of their movements via permutation test. Since permutation test is computationally expensive, two effective pruning strategies are developed to reduce the computation time. Furthermore, we show how the proposed method can be extended to efficiently answer the classic threshold query: given an object, retrieve all the objects in the database that have relationships, whose significance values are above certain threshold, with the query object. Empirical studies on both synthetic data and real movement data demonstrate the effectiveness and efficiency of our method.</dcterms:abstract> <dc:creator>Li, Zhenhui</dc:creator> <dcterms:isPartOf rdf:resource=""/> <dc:creator>Ding, Bolin</dc:creator> <dc:creator>Kays, Roland</dc:creator> <dc:contributor>Li, Zhenhui</dc:contributor> </rdf:Description> </rdf:RDF>

This item appears in the following Collection(s)

Search KOPS


My Account