Search Results for author: Wen Hua

Found 11 papers, 7 papers with code

Guiding Neural Entity Alignment with Compatibility

1 code implementation29 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.

Entity Alignment Knowledge Graphs

Dependency-aware Self-training for Entity Alignment

1 code implementation29 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.

Entity Alignment Knowledge Graphs

Large-scale Entity Alignment via Knowledge Graph Merging, Partitioning and Embedding

1 code implementation23 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.

Entity Alignment

High-quality Task Division for Large-scale Entity Alignment

1 code implementation22 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.

Entity Alignment Informativeness +1

Ensemble Semi-supervised Entity Alignment via Cycle-teaching

1 code implementation12 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.

Entity Alignment Knowledge Graphs

Informed Multi-context Entity Alignment

1 code implementation2 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.

Entity Alignment Entity Embeddings +1

ActiveEA: Active Learning for Neural Entity Alignment

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.

Active Learning Entity Alignment +1

Transfer-based adaptive tree for multimodal sentiment analysis based on user latent aspects

no code implementations27 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.

Multimodal Sentiment Analysis Recommendation Systems

Cognitive-aware Short-text Understanding for Inferring Professions

no code implementations4 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.

EmoDNN: Understanding emotions from short texts through a deep neural network ensemble

no code implementations3 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.

Emotion Recognition Management

SoulMate: Short-text author linking through Multi-aspect temporal-textual embedding

no code implementations27 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.

Community Detection named-entity-recognition +2

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