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Guoliang Ji
Researcher at Chinese Academy of Sciences
Publications - 5
Citations - 2537
Guoliang Ji is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Matrix (mathematics) & Relationship extraction. The author has an hindex of 5, co-authored 5 publications receiving 1722 citations.
Papers
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Proceedings ArticleDOI
Knowledge Graph Embedding via Dynamic Mapping Matrix
TL;DR: A more fine-grained model named TransD, which is an improvement of TransR/CTransR, which not only considers the diversity of relations, but also entities, which makes it can be applied on large scale graphs.
Proceedings Article
Knowledge graph completion with adaptive sparse transfer matrix
TL;DR: Experimental results show that TranSparse outperforms Trans(E, H, R, and D) significantly, and achieves state-of-the-art performance on triplet classification and link prediction tasks.
Proceedings Article
Distant Supervision for Relation Extraction with Sentence-level Attention and Entity Descriptions
TL;DR: This paper proposes a sentence-level attention model to select the valid instances, which makes full use of the supervision information from knowledge bases, and extracts entity descriptions from Freebase and Wikipedia pages to supplement background knowledge for the authors' task.
Proceedings ArticleDOI
Learning to Represent Knowledge Graphs with Gaussian Embedding
TL;DR: The experimental results demonstrate that the KG2E method can effectively model the (un)certainties of entities and relations in a KG, and it significantly outperforms state-of-the-art methods (including TransH and TransR).
Posted Content
Question Answering over Knowledge Base with Neural Attention Combining Global Knowledge Information
TL;DR: A neural attention-based model to represent the questions dynamically according to the different focuses of various candidate answer aspects is presented, and the global knowledge inside the underlying KB is leveraged, aiming at integrating the rich KB information into the representation of the answers.