Standard
(A)kNN query processing on the cloud: A survey. / Nodarakis, Nikolaos; Rapti, Angeliki; Sioutas, Spyros; Tsakalidis, Athanasios K.; Tsolis, Dimitrios; Tzimas, Giannis; Panagis, Yannis.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag, 2017. p. 26-40 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 10230 LNCS).
Research output: Chapter in Book/Report/Conference proceeding › Book chapter › Research › peer-review
Harvard
Nodarakis, N, Rapti, A, Sioutas, S, Tsakalidis, AK, Tsolis, D, Tzimas, G
& Panagis, Y 2017,
(A)kNN query processing on the cloud: A survey. in
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10230 LNCS, pp. 26-40.
https://doi.org/10.1007/978-3-319-57045-7_3
APA
Nodarakis, N., Rapti, A., Sioutas, S., Tsakalidis, A. K., Tsolis, D., Tzimas, G.
, & Panagis, Y. (2017).
(A)kNN query processing on the cloud: A survey. In
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 26-40). Springer Verlag,. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 10230 LNCS
https://doi.org/10.1007/978-3-319-57045-7_3
Vancouver
Nodarakis N, Rapti A, Sioutas S, Tsakalidis AK, Tsolis D, Tzimas G et al.
(A)kNN query processing on the cloud: A survey. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag,. 2017. p. 26-40. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 10230 LNCS).
https://doi.org/10.1007/978-3-319-57045-7_3
Author
Nodarakis, Nikolaos ; Rapti, Angeliki ; Sioutas, Spyros ; Tsakalidis, Athanasios K. ; Tsolis, Dimitrios ; Tzimas, Giannis ; Panagis, Yannis. / (A)kNN query processing on the cloud: A survey. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag, 2017. pp. 26-40 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 10230 LNCS).
Bibtex
@inbook{441936340a9e40928f72f6d0e71da570,
title = "(A)kNN query processing on the cloud: A survey",
abstract = "{\textcopyright} Springer International Publishing AG 2017. A k-nearest neighbor (kNN) query determines the k nearest points, using distance metrics, from a given location. An all k-nearest neighbor (AkNN) query constitutes a variation of a kNN query and retrieves the k nearest points for each point inside a database. Their main usage resonates in spatial databases and they consist the backbone of many location-based applications and not only. Although (A)kNN is a fundamental query type, it is computationally very expensive. During the last years a multiplicity of research papers has focused around the distributed (A)kNN query processing on the cloud. This work constitutes a survey of research efforts towards this direction. The main contribution of this work is an up-to-date review of the latest (A)kNN query processing approaches. Finally, we discuss various research challenges and directions of further research around this domain.",
keywords = "Big data, MapReduce, Nearest neighbour, NoSQL, Query processing",
author = "Nikolaos Nodarakis and Angeliki Rapti and Spyros Sioutas and Tsakalidis, {Athanasios K.} and Dimitrios Tsolis and Giannis Tzimas and Yannis Panagis",
year = "2017",
doi = "10.1007/978-3-319-57045-7_3",
language = "English",
isbn = "9783319570440",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag,",
pages = "26--40",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
}
RIS
TY - CHAP
T1 - (A)kNN query processing on the cloud: A survey
AU - Nodarakis, Nikolaos
AU - Rapti, Angeliki
AU - Sioutas, Spyros
AU - Tsakalidis, Athanasios K.
AU - Tsolis, Dimitrios
AU - Tzimas, Giannis
AU - Panagis, Yannis
PY - 2017
Y1 - 2017
N2 - © Springer International Publishing AG 2017. A k-nearest neighbor (kNN) query determines the k nearest points, using distance metrics, from a given location. An all k-nearest neighbor (AkNN) query constitutes a variation of a kNN query and retrieves the k nearest points for each point inside a database. Their main usage resonates in spatial databases and they consist the backbone of many location-based applications and not only. Although (A)kNN is a fundamental query type, it is computationally very expensive. During the last years a multiplicity of research papers has focused around the distributed (A)kNN query processing on the cloud. This work constitutes a survey of research efforts towards this direction. The main contribution of this work is an up-to-date review of the latest (A)kNN query processing approaches. Finally, we discuss various research challenges and directions of further research around this domain.
AB - © Springer International Publishing AG 2017. A k-nearest neighbor (kNN) query determines the k nearest points, using distance metrics, from a given location. An all k-nearest neighbor (AkNN) query constitutes a variation of a kNN query and retrieves the k nearest points for each point inside a database. Their main usage resonates in spatial databases and they consist the backbone of many location-based applications and not only. Although (A)kNN is a fundamental query type, it is computationally very expensive. During the last years a multiplicity of research papers has focused around the distributed (A)kNN query processing on the cloud. This work constitutes a survey of research efforts towards this direction. The main contribution of this work is an up-to-date review of the latest (A)kNN query processing approaches. Finally, we discuss various research challenges and directions of further research around this domain.
KW - Big data
KW - MapReduce
KW - Nearest neighbour
KW - NoSQL
KW - Query processing
UR - http://www.mendeley.com/research/aknn-query-processing-cloud-survey
U2 - 10.1007/978-3-319-57045-7_3
DO - 10.1007/978-3-319-57045-7_3
M3 - Book chapter
SN - 9783319570440
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 26
EP - 40
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PB - Springer Verlag,
ER -