Representation of Semantic Word Embeddings Based on SLDA and Word2vec Model  

作　　者：TANG Huanling ZHU Hui WEI Hongmin ZHENG Han MAO Xueli LU Mingyu GUO Jin 

机构地区：[1]School of Computer Science and Technology,Shandong Technology and Business University,Yantai 264005,China [2]Co-innovation Center of Shandong Colleges and Universities:Future Intelligent Computing,Yantai 264005,China [3]Key Laboratory of Intelligent Information Processing in Universities of Shandong,Shandong Technology and Business University,Yantai 264005,China [4]School of Information and Electronic Engineering,Shandong Technology and Business University,Yantai 264005,China [5]Information Science and Technology College,Dalian Maritime University,Dalian 116026,China [6]School of Computer and Information Technology,Liaoning Normal University,Dalian 116029,China

出　　处：《Chinese Journal of Electronics》2023年第3期647-654,共8页电子学报（英文版）

基　　金：supported by the National Natural Science Foundation of China(61976124,61976125,61773244,61772319,61772250).

摘　　要：To solve the problem of semantic loss in text representation,this paper proposes a new embedding method of word representation in semantic space called wt2svec based on supervised latent Dirichlet allocation(SLDA)and Word2vec.It generates the global topic embedding word vector utilizing SLDA which can discover the global semantic information through the latent topics on the whole document set.It gets the local semantic embedding word vector based on the Word2vec.The new semantic word vector is obtained by combining the global semantic information with the local semantic information.Additionally,the document semantic vector named doc2svec is generated.The experimental results on different datasets show that wt2svec model can obviously promote the accuracy of the semantic similarity of words,and improve the performance of text categorization compared with Word2vec.

关 键 词：Supervised latent Dirichlet allocation Semantic word vector Word2vec Word embedding Semantic similarity Text categorization 

分 类 号：TP391.1[自动化与计算机技术—计算机应用技术]