Link Prediction Model for Anchor Chain Connection Method

DOI

10.2991/978-94-6463-040-4_100How to use a DOI?

Keywords

Anchor link; Link prediction; LBSN; Prediction algorithm

Abstract

In order to improve the accuracy of the location-based social network (LBSN) multi-source heterogeneous data link prediction, a model named anchor link-predict (AL-P), based on the anchor link method is proposed. Firstly, the network representation learning method is used to obtain the user relationship topology in LBSN. The matrix decomposition method is used to obtain the user sign-in record representation space in LBSN. Then, the anchor link method is joined the user relationship topology and user check-in record, and the potential relationship between them is mined. Finally, the experimental analysis shows that the Al-P model can significantly improve the link prediction effect under different evaluation indexes compared with the existing predicting models of same type.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Shou-meng Huang
PY  - 2022
DA  - 2022/12/27
TI  - Link Prediction Model for Anchor Chain Connection Method
BT  - Proceedings of the 2022 3rd International Conference on Artificial Intelligence and Education (IC-ICAIE 2022)
PB  - Atlantis Press
SP  - 657
EP  - 663
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-040-4_100
DO  - 10.2991/978-94-6463-040-4_100
ID  - Huang2022
ER  -