Proceedings of the 2018 International Symposium on Communication Engineering & Computer Science (CECS 2018)

Similarity Retrieval Algorithm based on Multilevel Fingerprint Comparison Matrix

Authors
Qiang Lv, Feihu Duan, Yanchao Wu, Jiaxing He
Corresponding Author
Qiang Lv
Available Online July 2018.
DOI
10.2991/cecs-18.2018.61How to use a DOI?
Keywords
Simhash algorithm,multilevel fingerprint, comparison matrix.
Abstract

In order to carry out similarity retrieval in mass information accurately and efficiently, this paper proposes a similarity retrieval algorithm based on multilevel fingerprint comparison matrix. For mass text information, firstly, using the Simhash algorithm to generate multilevel fingerprints; secondly, selecting the similar texts, and constructing a comparison matrix; then, the similarity between texts is accurately marked by using the comparison matrix; Finally, the real data of a company is applied to verify the accuracy and efficiency of the proposed algorithm.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2018 International Symposium on Communication Engineering & Computer Science (CECS 2018)
Series
Advances in Computer Science Research
Publication Date
July 2018
ISBN
978-94-6252-571-9
ISSN
2352-538X
DOI
10.2991/cecs-18.2018.61How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Qiang Lv
AU  - Feihu Duan
AU  - Yanchao Wu
AU  - Jiaxing He
PY  - 2018/07
DA  - 2018/07
TI  - Similarity Retrieval Algorithm based on Multilevel Fingerprint Comparison Matrix
BT  - Proceedings of the 2018 International Symposium on Communication Engineering & Computer Science (CECS 2018)
PB  - Atlantis Press
SP  - 353
EP  - 361
SN  - 2352-538X
UR  - https://doi.org/10.2991/cecs-18.2018.61
DO  - 10.2991/cecs-18.2018.61
ID  - Lv2018/07
ER  -