Entity Discovery and Linking Approach Based on Random Walk with Restart

doi:10.13190/j.jbupt.2016-220

JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM ›› 2017, Vol. 40 ›› Issue (6): 115-119.doi: 10.13190/j.jbupt.2016-220

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Entity Discovery and Linking Approach Based on Random Walk with Restart

TAN Yong-mei¹, ZHENG Di¹, LIU Shu-wen¹, LÜ Xue-qiang²

1. Intelligence Science and Technology Center, Beijing University of Posts and Telecommunications, Beijing 100876, China;
2. Beijing Key Laboratory of Internet Culture and Digital Dissemination Research, Beijing Information Science and Technology University, Beijing 100101, China

Received:2016-12-12 Online:2017-12-28 Published:2017-12-28
Supported by:

Abstract

Abstract: An entity discovery and linking approach based on random walk with restart was presented. Unified semantic representation for entities and documents-the probability distribution obtained from a random walk on a subgraph of the knowledge based was adopted. According to this distributed representation, the entities that are similar with mentions as the linking results was obtained. This method achieved 0.665 F value on entity linking section of TAC 2015 TEDL task, it performs better than other participating systems. It is illustrated that the method can overcome the feature sparsity issue and is less amenable to feature sparsity bias.

Key words: entity linking, semantic relatedness, random walk

CLC Number:

TN911.22

TAN Yong-mei, ZHENG Di, LIU Shu-wen, LÜ Xue-qiang. Entity Discovery and Linking Approach Based on Random Walk with Restart[J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2017, 40(6): 115-119.

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Entity Discovery and Linking Approach Based on Random Walk with Restart

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