Title: Learning Long-text Semantic Similarity with Multi-Granularity Semantic Embedding Based on Knowledge Enhancement
Abstract:research-article Learning Long-text Semantic Similarity with Multi-Granularity Semantic Embedding Based on Knowledge Enhancement Share on Authors: Deguang Peng Chongqing Megalight Technology co. LTD, ...research-article Learning Long-text Semantic Similarity with Multi-Granularity Semantic Embedding Based on Knowledge Enhancement Share on Authors: Deguang Peng Chongqing Megalight Technology co. LTD, China Chongqing Megalight Technology co. LTD, ChinaView Profile , Bohui Hao Chongqing University of Posts and Telecommunications, China Chongqing University of Posts and Telecommunications, ChinaView Profile , Xianlun Tang Chongqing University of Posts and Telecommunications, China Chongqing University of Posts and Telecommunications, ChinaView Profile , Yingjie Chen Chongqing University of Posts and Telecommunications, China Chongqing University of Posts and Telecommunications, ChinaView Profile , Jian Sun Chongqing University of Posts and Telecommunications, China Chongqing University of Posts and Telecommunications, ChinaView Profile , Runzhu Wang University of Chongqing, China University of Chongqing, ChinaView Profile Authors Info & Claims CCRIS 2020: 2020 International Conference on Control, Robotics and Intelligent SystemOctober 2020 Pages 19–25https://doi.org/10.1145/3437802.3437806Published:27 October 2020 0citation35DownloadsMetricsTotal Citations0Total Downloads35Last 12 Months35Last 6 weeks6 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet AccessRead More
Publication Year: 2020
Publication Date: 2020-10-27
Language: en
Type: article
Indexed In: ['crossref']
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Cited By Count: 5
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