@inproceedings{f08f5cb48b53488bb112bf11ec352f73,
title = "Link Prediction with Attention-Based Semantic Influence of Multiple Neighbors",
abstract = "The establishment of social links is not only determined by personal interests but also by neighbors{\textquoteright} influences, which may vary across different neighbors. However, the independent influence of each neighbor has not been separately considered on semantic level in current approaches. In this work, we predict missing social links by modeling semantic influence of each neighbor separately with an embedding approach. The semantic of influence is fine grained on each neighbor{\textquoteright}s specific interest with attention-based method. The proposed model named AIMN (Attention-based semantic Influence of Multiple Neighbors) is integrated with structure information with a uniform framework. Extensive experiments on different real-world networks demonstrate that AIMN outperforms state-of-the-art methods.",
keywords = "Attention, Link prediction, Network embedding, Semantic influence, Social networks",
author = "Meixian Song and Bo Wang and Xindian Ma and Qinghua Hu and Xin Wang and Yuexian Hou and Dawei Song",
note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2019.; 26th International Conference on Neural Information Processing, ICONIP 2019 ; Conference date: 12-12-2019 Through 15-12-2019",
year = "2019",
doi = "10.1007/978-3-030-36802-9\_54",
language = "English",
isbn = "9783030368012",
series = "Communications in Computer and Information Science",
publisher = "Springer",
pages = "506--514",
editor = "Tom Gedeon and Wong, \{Kok Wai\} and Minho Lee",
booktitle = "Neural Information Processing - 26th International Conference, ICONIP 2019, Proceedings",
address = "Germany",
}