Continuous Similarity Search for Dynamic Text Streams-Reference-Cited by-同舟云学术

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Continuous Similarity Search for Dynamic Text Streams

Published:2023-12-01 Issue:12 Volume:E106.D Page:2026-2035
ISSN:0916-8532
Container-title:IEICE Transactions on Information and Systems
language:en
Short-container-title:IEICE Trans. Inf. & Syst.

Author:

TSUCHIDA Yuma¹,KUBO Kohei¹,KOGA Hisashi¹

Affiliation:

1. University of Electro-Communications

Publisher

Institute of Electronics, Information and Communications Engineers (IEICE)

Subject

Artificial Intelligence,Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Hardware and Architecture,Software

Link

https://www.jstage.jst.go.jp/article/transinf/E106.D/12/E106.D_2022EDP7229/_pdf

Reference22 articles.

1. [1] L.H. U, J. Zhang, K. Moruatidis, and Y. Li, “Continuous top-k monitoring on document streams,” IEEE Trans. Knowl. Data Eng., vol.29, no.5, pp.991-1003, 2017. 10.1109/tkde.2017.2657622

2. [2] X. Wang, Y. Zhang, W. Zhang, X. Lin, and Z. Huang, “Skype: Top-k spatial-keyword publish/subscribe over sliding window,” Proc. VLDB Endow., vol.9, no.7, pp.588-599, 2016. 10.14778/2904483.2904490

3. [3] D. Yang, A. Shastri, E.A. Rundensteiner, and M.O. Ward, “An optimal strategy for monitoring top-k queries in streaming windows,” Proc. 14th International Conference on Extending Database Technology, pp.57-68, 2011. 10.1145/1951365.1951375

4. [4] G.D.F. Morales and A. Gionis, “Streaming similarity self-join,” Proc. VLDB Endow., vol.9, no.10, pp.792-803, 2016. 10.14778/2977797.2977805

5. [5] L. Pacífico and L. Ribeiro, “Sstr: Set similarity join over stream data,” Proc. 22nd International Conference on Enterprise Information Systems-Volume 1: ICEIS, pp.52-60, INSTICC, SciTePress, 2020. 10.5220/0009420400520060

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