The Science and Information (SAI) Organization
  • Home
  • About Us
  • Journals
  • Conferences
  • Contact Us

Publication Links

  • IJACSA
  • Author Guidelines
  • Publication Policies
  • Metadata Harvesting (OAI2)
  • Digital Archiving Policy

IJACSA

  • About the Journal
  • Call for Papers
  • Author Guidelines
  • Fees/ APC
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Editors
  • Reviewers
  • Apply as a Reviewer

IJARAI

  • About the Journal
  • Archives
  • Indexing & Archiving

Special Issues

  • Home
  • Archives
  • Call for Papers
  • Proposals
  • Guest Editors

Computing Conference

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Intelligent Systems Conference (IntelliSys)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Future Technologies Conference (FTC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Future of Information and Communication Conference (FICC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact
  • Home
  • Call for Papers
  • Guidelines
  • Fees
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Editors
  • Reviewers
  • Subscribe

Article Details

Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

DMTree: A Novel Indexing Method for Finding Similarities in Large Vector Sets

Author 1: Phuc Do
Author 2: Trung Phan Hong
Author 3: Huong Duong To

Download PDF

Digital Object Identifier (DOI) : 10.14569/IJACSA.2020.0110483

Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 11 Issue 4, 2020.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: In a vector set, to find similarities we will compute distances from the querying vector to all other vectors. On a large vector set, computing too many distances as above takes a lot of time. So we need to find a way to compute less distance and the MTree structure is the technique we need. The MTree structure is a technique of indexing vector sets based on a defined distance. We can solve effectively the problems of finding similarities by using the MTree structure. However, the MTree structure is built on one computer so the indexing power is limited. Today, large vector sets, not fit in one computer, are more and more. The MTree structure failed to index these large vector sets. Therefore, in this work, we present a novel indexing method, extended from the MTree structure, that can index large vector sets. Besides, we also perform experiments to prove the performance of this novel method.

Keywords: MTree; DMTree; spark; distributed k-NN query; distributed range query

Phuc Do, Trung Phan Hong and Huong Duong To, “DMTree: A Novel Indexing Method for Finding Similarities in Large Vector Sets” International Journal of Advanced Computer Science and Applications(IJACSA), 11(4), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0110483

@article{Do2020,
title = {DMTree: A Novel Indexing Method for Finding Similarities in Large Vector Sets},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2020.0110483},
url = {http://dx.doi.org/10.14569/IJACSA.2020.0110483},
year = {2020},
publisher = {The Science and Information Organization},
volume = {11},
number = {4},
author = {Phuc Do and Trung Phan Hong and Huong Duong To}
}


IJACSA

Upcoming Conferences

Future of Information and Communication Conference (FICC) 2023

2-3 March 2023

  • Hybrid | San Francisco

Computing Conference 2023

13-14 July 2023

  • Hybrid | London, UK

IntelliSys 2022

1-2 September 2022

  • Hybrid / Amsterdam

Future Technologies Conference (FTC) 2022

20-21 October 2022

  • Hybrid / Vancouver
The Science and Information (SAI) Organization
BACK TO TOP

Computer Science Journal

  • About the Journal
  • Call for Papers
  • Submit Paper
  • Indexing

Our Conferences

  • Computing Conference
  • Intelligent Systems Conference
  • Future Technologies Conference
  • Communication Conference

Help & Support

  • Contact Us
  • About Us
  • Terms and Conditions
  • Privacy Policy

© The Science and Information (SAI) Organization Limited. Registered in England and Wales. Company Number 8933205. All rights reserved. thesai.org