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Xianpei Han
Researcher at Chinese Academy of Sciences
Publications - 131
Citations - 2603
Xianpei Han is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Computer science & Parsing. The author has an hindex of 19, co-authored 109 publications receiving 1877 citations.
Papers
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Proceedings ArticleDOI
Collective entity linking in web text: a graph-based method
Xianpei Han,Le Sun,Jun Zhao +2 more
TL;DR: Experimental results show that the proposed graph-based collective EL method can achieve significant performance improvement over the traditional EL methods, and the purely collective nature of the inference algorithm, in which evidence for related EL decisions can be reinforced into high-probability decisions.
Proceedings ArticleDOI
Named entity disambiguation by leveraging wikipedia semantic knowledge
Xianpei Han,Jun Zhao +1 more
TL;DR: A novel similarity measure is proposed to leverage Wikipedia semantic knowledge for disambiguation, which surpasses other knowledge bases by the coverage of concepts, rich semantic information and up-to-date content and has been tested on the standard WePS data sets.
Proceedings Article
A Generative Entity-Mention Model for Linking Entities with Knowledge Base
Xianpei Han,Le Sun +1 more
TL;DR: This paper proposes a generative probabilistic model, called entity-mention model, which can leverage heterogenous entity knowledge (including popularity knowledge, name knowledge and context knowledge) for the entity linking task.
Posted Content
CAIL2018: A Large-Scale Legal Dataset for Judgment Prediction
Chaojun Xiao,Haoxi Zhong,Zhipeng Guo,Cunchao Tu,Zhiyuan Liu,Maosong Sun,Yansong Feng,Xianpei Han,Zhen Hu,Heng Wang,Jianfeng Xu +10 more
TL;DR: The CAIL2018 dataset is introduced, the first large-scale Chinese legal dataset for judgment prediction, which contains more than $2.6 million criminal cases published by the Supreme People's Court of China, which are several times larger than other datasets in existing works on judgment prediction.
Proceedings Article
An Entity-Topic Model for Entity Linking
Xianpei Han,Le Sun +1 more
TL;DR: This paper proposes a generative model -- called entity-topic model, to effectively join the above two complementary directions of EL research together and can accurately link all mentions in a document.