Balanced large scale knowledge matching using LSH forest

Michael Cochez; Vagan Terziyan; Vadim Ermolayev

doi:10.1007/978-3-319-27932-9_4

Balanced large scale knowledge matching using LSH forest

Michael Cochez^*, Vagan Terziyan, Vadim Ermolayev

^*Corresponding author for this work

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

Abstract

Evolving Knowledge Ecosystems were proposed recently to approach the Big Data challenge, following the hypothesis that knowledge evolves in a way similar to biological systems. Therefore, the inner working of the knowledge ecosystem can be spotted from natural evolution. An evolving knowledge ecosystem consists of Knowledge Organisms, which form a representation of the knowledge, and the environment in which they reside. The environment consists of contexts, which are composed of so-called knowledge tokens. These tokens are ontological fragments extracted from information tokens, in turn, which originate from the streams of information flowing into the ecosystem. In this article we investigate the use of LSH Forest (a self-tuning indexing schema based on locality-sensitive hashing) for solving the problem of placing new knowledge tokens in the right contexts of the environment. We argue and show experimentally that LSH Forest possesses required properties and could be used for large distributed set-ups.

Original language	English
Title of host publication	Semantic Keyword-Based Search on Structured Data Sources First COST Action IC1302 – International KEYSTONE Conference, IKC 2015, Revised Selected Papers
Editors	Yannis Velegrakis, Jorge Cardoso, Jorge Cardoso, Alexandre Miguel Pinto, Francesco Guerra, Geert-Jan Houben
Publisher	Springer Verlag
Pages	36-50
Number of pages	15
ISBN (Print)	9783319279312
DOIs	https://doi.org/10.1007/978-3-319-27932-9_4
Publication status	Published - 1 Jan 2015
Externally published	Yes
Event	1st COST Action IC1302 International KEYSTONE Conference on Semantic Keyword-Based Search on Structured Data Sources, IKC 2015 - Coimbra, Portugal Duration: 8 Sept 2015 → 9 Sept 2015

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9398
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	1st COST Action IC1302 International KEYSTONE Conference on Semantic Keyword-Based Search on Structured Data Sources, IKC 2015
Country/Territory	Portugal
City	Coimbra
Period	8/09/15 → 9/09/15

Keywords

Big data
Evolving knowledge ecosystems
Locality-sensitive hashing
LSH forest

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10.1007/978-3-319-27932-9_4

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Cochez, M., Terziyan, V., & Ermolayev, V. (2015). Balanced large scale knowledge matching using LSH forest. In Y. Velegrakis, J. Cardoso, J. Cardoso, A. M. Pinto, F. Guerra, & G.-J. Houben (Eds.), Semantic Keyword-Based Search on Structured Data Sources First COST Action IC1302 – International KEYSTONE Conference, IKC 2015, Revised Selected Papers (pp. 36-50). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9398). Springer Verlag. https://doi.org/10.1007/978-3-319-27932-9_4

Cochez, Michael ; Terziyan, Vagan ; Ermolayev, Vadim. / Balanced large scale knowledge matching using LSH forest. Semantic Keyword-Based Search on Structured Data Sources First COST Action IC1302 – International KEYSTONE Conference, IKC 2015, Revised Selected Papers. editor / Yannis Velegrakis ; Jorge Cardoso ; Jorge Cardoso ; Alexandre Miguel Pinto ; Francesco Guerra ; Geert-Jan Houben. Springer Verlag, 2015. pp. 36-50 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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Cochez, M, Terziyan, V & Ermolayev, V 2015, Balanced large scale knowledge matching using LSH forest. in Y Velegrakis, J Cardoso, J Cardoso, AM Pinto, F Guerra & G-J Houben (eds), Semantic Keyword-Based Search on Structured Data Sources First COST Action IC1302 – International KEYSTONE Conference, IKC 2015, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9398, Springer Verlag, pp. 36-50, 1st COST Action IC1302 International KEYSTONE Conference on Semantic Keyword-Based Search on Structured Data Sources, IKC 2015, Coimbra, Portugal, 8/09/15. https://doi.org/10.1007/978-3-319-27932-9_4

Balanced large scale knowledge matching using LSH forest. / Cochez, Michael; Terziyan, Vagan; Ermolayev, Vadim.
Semantic Keyword-Based Search on Structured Data Sources First COST Action IC1302 – International KEYSTONE Conference, IKC 2015, Revised Selected Papers. ed. / Yannis Velegrakis; Jorge Cardoso; Jorge Cardoso; Alexandre Miguel Pinto; Francesco Guerra; Geert-Jan Houben. Springer Verlag, 2015. p. 36-50 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9398).

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

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AU - Terziyan, Vagan

AU - Ermolayev, Vadim

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N2 - Evolving Knowledge Ecosystems were proposed recently to approach the Big Data challenge, following the hypothesis that knowledge evolves in a way similar to biological systems. Therefore, the inner working of the knowledge ecosystem can be spotted from natural evolution. An evolving knowledge ecosystem consists of Knowledge Organisms, which form a representation of the knowledge, and the environment in which they reside. The environment consists of contexts, which are composed of so-called knowledge tokens. These tokens are ontological fragments extracted from information tokens, in turn, which originate from the streams of information flowing into the ecosystem. In this article we investigate the use of LSH Forest (a self-tuning indexing schema based on locality-sensitive hashing) for solving the problem of placing new knowledge tokens in the right contexts of the environment. We argue and show experimentally that LSH Forest possesses required properties and could be used for large distributed set-ups.

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Cochez M, Terziyan V, Ermolayev V. Balanced large scale knowledge matching using LSH forest. In Velegrakis Y, Cardoso J, Cardoso J, Pinto AM, Guerra F, Houben GJ, editors, Semantic Keyword-Based Search on Structured Data Sources First COST Action IC1302 – International KEYSTONE Conference, IKC 2015, Revised Selected Papers. Springer Verlag. 2015. p. 36-50. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-27932-9_4

Balanced large scale knowledge matching using LSH forest

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Keywords

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