1 code implementation • 29 Nov 2022 • Bing Liu, Harrisen Scells, Wen Hua, Guido Zuccon, Genghong Zhao, Xia Zhang
Making compatible predictions thus should be one of the goals of training an EA model along with fitting the labelled data: this aspect however is neglected in current methods.
1 code implementation • 29 Nov 2022 • Bing Liu, Tiancheng Lan, Wen Hua, Guido Zuccon
Entity Alignment (EA), which aims to detect entity mappings (i. e. equivalent entity pairs) in different Knowledge Graphs (KGs), is critical for KG fusion.
1 code implementation • 23 Aug 2022 • Kexuan Xin, Zequn Sun, Wen Hua, Wei Hu, Jianfeng Qu, Xiaofang Zhou
Therefore, in this work, we propose a scalable GNN-based entity alignment approach to reduce the structure and alignment loss from three perspectives.
1 code implementation • 22 Aug 2022 • Bing Liu, Wen Hua, Guido Zuccon, Genghong Zhao, Xia Zhang
To include in the EA subtasks a high proportion of the potential mappings originally present in the large EA task, we devise a counterpart discovery method that exploits the locality principle of the EA task and the power of trained EA models.
1 code implementation • 12 Mar 2022 • Kexuan Xin, Zequn Sun, Wen Hua, Bing Liu, Wei Hu, Jianfeng Qu, Xiaofang Zhou
We also design a conflict resolution mechanism to resolve the alignment conflict when combining the new alignment of an aligner and that from its teacher.
1 code implementation • 2 Jan 2022 • Kexuan Xin, Zequn Sun, Wen Hua, Wei Hu, Xiaofang Zhou
Entity alignment is a crucial step in integrating knowledge graphs (KGs) from multiple sources.
1 code implementation • EMNLP 2021 • Bing Liu, Harrisen Scells, Guido Zuccon, Wen Hua, Genghong Zhao
Entity Alignment (EA) aims to match equivalent entities across different Knowledge Graphs (KGs) and is an essential step of KG fusion.
no code implementations • 27 Jun 2021 • Sana Rahmani, Saeid Hosseini, Raziyeh Zall, Mohammad Reza Kangavari, Sara Kamran, Wen Hua
Based on the given extrinsic and intrinsic analysis results, we note that compared to other theoretical-based techniques, the proposed hierarchical clustering approach can better group the users within the adaptive tree.
no code implementations • 4 Jun 2021 • Sayna Esmailzadeh, Saeid Hosseini, Mohammad Reza Kangavari, Wen Hua
Leveraging short-text contents to estimate the occupation of microblog authors has significant gains in many applications.
no code implementations • 3 Jun 2021 • Sara Kamran, Raziyeh Zall, Mohammad Reza Kangavari, Saeid Hosseini, Sana Rahmani, Wen Hua
The latent knowledge in the emotions and the opinions of the individuals that are manifested via social networks are crucial to numerous applications including social management, dynamical processes, and public security.
no code implementations • 27 Oct 2019 • Saeed Najafipour, Saeid Hosseini, Wen Hua, Mohammad Reza Kangavari, Xiaofang Zhou
Our approach, on the one hand, computes the relevance score (edge weight) between the authors through considering a portmanteau of contents and concepts, and on the other hand, employs a stack-wise graph cutting algorithm to extract the communities of the related authors.