eprintid: 4688
rev_number: 4
eprint_status: archive
userid: 472
dir: disk0/00/00/46/88
datestamp: 2021-12-10 10:57:04
lastmod: 2021-12-10 10:57:04
status_changed: 2021-12-10 10:57:04
type: conference_item
succeeds: 4670
metadata_visibility: show
creators_name: Hoang, Thi Linh
creators_name: Pham, Tuan Dung
creators_name: Ta, Viet Cuong
creators_id: hoanglinh@vnu.edu.vn
creators_id: phamtuandung12@gmail.com
creators_id: cuongtv@vnu.edu.vn
title: Improving Graph Convolutional Networks with Transformer Layer in social-based items recommendation
ispublished: inpress
subjects: IT
divisions: fac_fit
abstract: With the emergence of online social networks, social-based items recommendation has become a popular research direction. Recently, Graph Convolutional Networks have shown promising results by modeling the information diffusion process in graphs. It provides a unified framework for graph embedding that can leverage both the social graph structure and node features information. In this paper, we improve the embedding output of the graph-based convolution layer by adding a number of transformer layers. The transformer layers with attention architecture help discover frequent patterns in the embedding space which increase the predictive power of the model in the downstream tasks. Our approach is tested on two social-based items recommendation dataset, Ciao and Epinions and our model outperforms other graph-based recommendation baselines.
date: 2021-11-11
date_type: submitted
full_text_status: public
pres_type: paper
event_title: The 13th International Conference on KNOWLEDGE AND SYSTEMS ENGINEERING (KSE 2021)
event_location: Bangkok, Thailand
event_dates: 10-12 Nov 2021
event_type: conference
refereed: TRUE
citation:   Hoang, Thi Linh and Pham, Tuan Dung and Ta, Viet Cuong  (2021) Improving Graph Convolutional Networks with Transformer Layer in social-based items recommendation.  In: The 13th International Conference on KNOWLEDGE AND SYSTEMS ENGINEERING (KSE 2021), 10-12 Nov 2021, Bangkok, Thailand.    (In Press)  
document_url: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/4688/2/Improving_Graph_Convolutional_Networks_with_Transformer_Layer_in_social-based_items_recommendation_IEEE_Express.pdf