Improving query efficiency in high dimensional point indexes

dc.contributor.author	Ούτσιος, Ευάγγελος	el
dc.contributor.author	Ευαγγελίδης, Γεώργιος	el
dc.contributor.author	Outsios, Evangelos	en
dc.contributor.author	Evangelidis, Georgios	en
dc.date.accessioned	2015-04-25T08:53:15Z
dc.date.available	2015-04-25T08:53:15Z
dc.date.issued	2015-04-25
dc.identifier.uri	http://hdl.handle.net/11400/8907
dc.rights	Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/us/	*
dc.source	http://history.icininfo.net/2011/	el
dc.source	http://history.icininfo.net/2011/	el
dc.subject	K-dimensional point indexing
dc.subject	Optimizing data node storage utilization
dc.subject	Βελτιστοποίηση της χρήσης των δεδομένων αποθήκευσης κόμβου
dc.subject	Range query performance
dc.subject	Σειρά απόδοση του ερωτήματος
dc.title	Improving query efficiency in high dimensional point indexes	en
heal.type	conferenceItem
heal.classification	Computer science
heal.classification	Computer programming
heal.classification	Πληροφορική
heal.classification	Προγραμματισμός
heal.classificationURI	http://skos.um.es/unescothes/C00750
heal.classificationURI	http://skos.um.es/unescothes/C00749
heal.classificationURI	N/A-Πληροφορική
heal.classificationURI	N/A-Προγραμματισμός
heal.contributorName	Γιαννακόπουλος, Γεώργιος Α. (συντ.)	el
heal.contributorName	Σακκάς, Δαμιανός Π. (συντ.)	el
heal.language	en
heal.access	free
heal.recordProvider	Τεχνολογικό Εκπαιδευτικό Ίδρυμα Αθήνας. Σχολή Διοίκησης και Οικονομίας. Τμήμα Βιβλιοθηκονομίας και Συστημάτων Πληροφόρησης	el
heal.publicationDate	2011-09
heal.bibliographicCitation	Outsios, E. and Evangelidis, G. (2011). Improving query efficiency in high dimensional point indexes. International Conference on Integrated Information (IC-ININFO 2011), Kos Island, Greece, 29 September - 3 Octomber 2011. pp. 30-33. Available from: http://history.icininfo.net/2011/FileStore/procs_INFO_2011.pdf	en
heal.abstract	In this paper, we focus on the leaf level nodes of tree-like k-dimensional indexes that store the data entries, since those nodes represent the majority of the nodes in the index. We propose a generic node splitting approach that defers splitting when possible and instead favors merging of a full node with an appropriate sibling and then re-splitting of the resulting node. Our experiments with the hB-tree, show that the proposed splitting approach achieves high average node storage utilization regardless of data distribution, data insertion patterns and dimensionality.	en
heal.fullTextAvailability	true
heal.conferenceName	International Conference on Integrated Information (IC-ININFO 2011)	el
heal.conferenceItemType	full paper