In recent years,deep learning methods have developed rapidly and found application in many fields,including natural language processing.In the field of aspect-level sentiment analysis,deep learning methods can also gr...In recent years,deep learning methods have developed rapidly and found application in many fields,including natural language processing.In the field of aspect-level sentiment analysis,deep learning methods can also greatly improve the performance of models.However,previous studies did not take into account the relationship between user feature extraction and contextual terms.To address this issue,we use data feature extraction and deep learning combined to develop an aspect-level sentiment analysis method.To be specific,we design user comment feature extraction(UCFE)to distill salient features from users’historical comments and transform them into representative user feature vectors.Then,the aspect-sentence graph convolutional neural network(ASGCN)is used to incorporate innovative techniques for calculating adjacency matrices;meanwhile,ASGCN emphasizes capturing nuanced semantics within relationships among aspect words and syntactic dependency types.Afterward,three embedding methods are devised to embed the user feature vector into the ASGCN model.The empirical validations verify the effectiveness of these models,consistently surpassing conventional benchmarks and reaffirming the indispensable role of deep learning in advancing sentiment analysis methodologies.展开更多
Generalized Petersen graphs are an important class of commonly used interconnection networks and have been studied . The total domination number of generalized Petersen graphs P(m,2) is obtained in this paper.
Virtual Home Library (VHL) is an integrated IT system that utilizes virtual reality technology and an IPTV set-top box (STB) to virtually construct a ‘library’ and the relevant reading environment on televisions in ...Virtual Home Library (VHL) is an integrated IT system that utilizes virtual reality technology and an IPTV set-top box (STB) to virtually construct a ‘library’ and the relevant reading environment on televisions in people’s home. Unlike the online e-book reading applications, Virtual Home Library can be applied on televisions – the world’s most convenient and most efficient communication tool. Providing extended digital library services, it will be a perfect group reading utility for family readers. The system has been investigated by a joint research team formed by the National Library of China and the Communication University of China, collaborating with a Chinese IPTV equipment manufacturer. This paper presents some preliminary investigations of the VHL system performed by the research team.展开更多
基金This work is partly supported by the Fundamental Research Funds for the Central Universities(CUC230A013)It is partly supported by Natural Science Foundation of Beijing Municipality(No.4222038)It is also supported by National Natural Science Foundation of China(Grant No.62176240).
文摘In recent years,deep learning methods have developed rapidly and found application in many fields,including natural language processing.In the field of aspect-level sentiment analysis,deep learning methods can also greatly improve the performance of models.However,previous studies did not take into account the relationship between user feature extraction and contextual terms.To address this issue,we use data feature extraction and deep learning combined to develop an aspect-level sentiment analysis method.To be specific,we design user comment feature extraction(UCFE)to distill salient features from users’historical comments and transform them into representative user feature vectors.Then,the aspect-sentence graph convolutional neural network(ASGCN)is used to incorporate innovative techniques for calculating adjacency matrices;meanwhile,ASGCN emphasizes capturing nuanced semantics within relationships among aspect words and syntactic dependency types.Afterward,three embedding methods are devised to embed the user feature vector into the ASGCN model.The empirical validations verify the effectiveness of these models,consistently surpassing conventional benchmarks and reaffirming the indispensable role of deep learning in advancing sentiment analysis methodologies.
文摘Generalized Petersen graphs are an important class of commonly used interconnection networks and have been studied . The total domination number of generalized Petersen graphs P(m,2) is obtained in this paper.
文摘Virtual Home Library (VHL) is an integrated IT system that utilizes virtual reality technology and an IPTV set-top box (STB) to virtually construct a ‘library’ and the relevant reading environment on televisions in people’s home. Unlike the online e-book reading applications, Virtual Home Library can be applied on televisions – the world’s most convenient and most efficient communication tool. Providing extended digital library services, it will be a perfect group reading utility for family readers. The system has been investigated by a joint research team formed by the National Library of China and the Communication University of China, collaborating with a Chinese IPTV equipment manufacturer. This paper presents some preliminary investigations of the VHL system performed by the research team.
