@inproceedings{bf5f6c4e7ce8450fb8701867f274e660,
title = "A sequential neural information diffusion model with structure attention",
abstract = "In this paper, we propose a novel sequential neural network with structure attention to model information diffusion. The proposed model explores both sequential nature of an information diffusion process and structural characteristics of user connection graph. The recurrent neural network framework is employed to model the sequential information. The attention mechanism is incorporated to capture the structural dependency among users, which is defined as the diffusion context of a user. A gating mechanism is further developed to effectively integrate the sequential and structural information. The proposed model is evaluated on the diffusion prediction task. The performances on both synthetic and real datasets demonstrate its superiority over popular baselines and state-of-the-art sequence-based models.",
keywords = "Information Diffusion, Neural Network, Structure Attention",
author = "Zhitao Wang and Chengyao Chen and Wenjie Li",
year = "2018",
month = oct,
day = "17",
doi = "10.1145/3269206.3269275",
language = "English",
series = "International Conference on Information and Knowledge Management, Proceedings",
publisher = "Association for Computing Machinery",
pages = "1795--1798",
editor = "Norman Paton and Selcuk Candan and Haixun Wang and James Allan and Rakesh Agrawal and Alexandros Labrinidis and Alfredo Cuzzocrea and Mohammed Zaki and Divesh Srivastava and Andrei Broder and Assaf Schuster",
booktitle = "CIKM 2018 - Proceedings of the 27th ACM International Conference on Information and Knowledge Management",
note = "27th ACM International Conference on Information and Knowledge Management, CIKM 2018 ; Conference date: 22-10-2018 Through 26-10-2018",
}