In the era of network live broadcasting for everyone,the development of live broadcasting platforms is also more intelligent and diversified.However,in the face of a large group of elderly users,the interface interact...In the era of network live broadcasting for everyone,the development of live broadcasting platforms is also more intelligent and diversified.However,in the face of a large group of elderly users,the interface interaction design mode used is still mainly based on the interaction mode for young groups,and is not designed for elderly users.Therefore,a design method for optimizing the interaction interface of live broadcasting platform for elderly users was proposed in this study.Firstly,the case study method and Delphi expert survey method were used to determine the design needs of elderly users and the design mode was analysed.Secondly,the orthogonal design principle was used to design a test sample of the interactive interface of live broadcasting platform applicable for the elderly users,and then a user evaluation system was established to calculate the weights of the design elements using hierarchical analysis,and then the predictive relationship between the design mode of the interactive interface of live broadcasting platform and the elderly users was established by Quantitative Theory I.Finally,Genetic Algorithm was applied to generate the optimized design scheme.The results showed that the design method based on the Genetic Algorithm and the combination of Quantitative Theory can scientifically and effectively optimize the design of the interactive interface of the live broadcasting platform for the elderly users,and improve the experience of the elderly users.展开更多
Using the existing positioning technology can easily obtain high-precision positioning information,which can save resources and reduce complexity when used in the communication field.In this paper,we propose a locatio...Using the existing positioning technology can easily obtain high-precision positioning information,which can save resources and reduce complexity when used in the communication field.In this paper,we propose a location-based user scheduling and beamforming scheme for the downlink of a massive multi-user input-output system.Specifically,we combine an analog outer beamformer with a digital inner beamformer.An outer beamformer can be selected from a codebook formed by antenna steering vectors,and then a reduced-complexity inner beamformer based on iterative orthogonal matrices and right triangular matrices(QR)decomposition is applied to cancel interuser interference.Then,we propose a low-complexity user selection algorithm using location information in this paper.We first derive the geometric angle between channel matrices,which represent the correlation between users.Furthermore,we derive the asymptotic signal to interference-plus-noise ratio(SINR)of the system in the context of two-stage beamforming using random matrix theory(RMT),taking into account inter-channel correlations and energies.Simulation results show that the algorithm can achieve higher system and speed while reducing computational complexity.展开更多
With the arrival of the big data era,the phenomenon of information overload is becoming increasingly severe.In response to the common issue of sparse user rating matrices in recommendation systems,a collaborative filt...With the arrival of the big data era,the phenomenon of information overload is becoming increasingly severe.In response to the common issue of sparse user rating matrices in recommendation systems,a collaborative filtering recommendation algorithm was proposed based on improved user profiles in this study.Firstly,a profile labeling system was constructed based on user characteristics.This study proposed that user profile labels should be created using basic user information and basic item information,in order to construct multidimensional user profiles.TF-IDF algorithm was used to determine the weights of user-item feature labels.Secondly,user similarity was calculated by weighting both profile-based collaborative filtering and user-based collaborative filtering algorithms,and the final user similarity was obtained by harmonizing these weights.Finally,personalized recommendations were generated using Top-N method.Validation with the MovieLens-1M dataset revealed that this algorithm enhances both recommendation Precision and Recall compared to single-method approaches(recommendation algorithm based on user portrait and user-based collaborative filtering algorithm).展开更多
The article combines institutional change and social participation of the subjects. By investigating the expanding of community subject and gradually cultivating their ability to participate,we can test the achievemen...The article combines institutional change and social participation of the subjects. By investigating the expanding of community subject and gradually cultivating their ability to participate,we can test the achievements of community development in our country,and lay a foundation for reaching the social development goals.展开更多
Many scholars have gradually realized that volunteer service can not only manifest the social value,but also become an effective way to enlarge citizen participation.Mainly from the aspects of the rationality of the i...Many scholars have gradually realized that volunteer service can not only manifest the social value,but also become an effective way to enlarge citizen participation.Mainly from the aspects of the rationality of the increasing of citizen participation in volunteer service,this paper analyses the significance of volunteer service in the modernization transformation of China and puts forward some suggestions for the development of China' s volunteer service in the future.展开更多
In the context of big data, many large-scale knowledge graphs have emerged to effectively organize the explosive growth of web data on the Internet. To select suitable knowledge graphs for use from many knowledge grap...In the context of big data, many large-scale knowledge graphs have emerged to effectively organize the explosive growth of web data on the Internet. To select suitable knowledge graphs for use from many knowledge graphs, quality assessment is particularly important. As an important thing of quality assessment, completeness assessment generally refers to the ratio of the current data volume to the total data volume.When evaluating the completeness of a knowledge graph, it is often necessary to refine the completeness dimension by setting different completeness metrics to produce more complete and understandable evaluation results for the knowledge graph.However, lack of awareness of requirements is the most problematic quality issue. In the actual evaluation process, the existing completeness metrics need to consider the actual application. Therefore, to accurately recommend suitable knowledge graphs to many users, it is particularly important to develop relevant measurement metrics and formulate measurement schemes for completeness. In this paper, we will first clarify the concept of completeness, establish each metric of completeness, and finally design a measurement proposal for the completeness of knowledge graphs.展开更多
In the data-driven era of the internet and business environments,constructing accurate user profiles is paramount for personalized user understanding and classification.The traditional TF-IDF algorithm has some limita...In the data-driven era of the internet and business environments,constructing accurate user profiles is paramount for personalized user understanding and classification.The traditional TF-IDF algorithm has some limitations when evaluating the impact of words on classification results.Consequently,an improved TF-IDF-K algorithm was introduced in this study,which included an equalization factor,aimed at constructing user profiles by processing and analyzing user search records.Through the training and prediction capabilities of a Support Vector Machine(SVM),it enabled the prediction of user demographic attributes.The experimental results demonstrated that the TF-IDF-K algorithm has achieved a significant improvement in classification accuracy and reliability.展开更多
With the rapid development of big data,online education can use big data technology to achieve personalized and intelligent education as well as improve learning effect and user satisfaction.In this study,the users of...With the rapid development of big data,online education can use big data technology to achieve personalized and intelligent education as well as improve learning effect and user satisfaction.In this study,the users of The Open University of China online education platform were taken as the research object,their user behavior data was collected,cleaned,and analyzed with text mining.The RFM model and the improved K-Means algorithm were used to construct the user portrait of the platform group and the needs and preferences of different types of the users were analyzded.Chinese word segmentation was used to show the key words of different types of users and the word cloud of their using frequency.The focus of different user groups was determined to facilitate for the follow-up course recommendation and precision marketing.Experimental results showed that the improved K-Means algorithm can well depict the behavior of group users.The index of silhouette score was improved to 0.811 by the improved K-Means algorithm,from random uncertainty to a fixed value,which can effectively solve the problem of inconsistent results caused by outlier sample points.展开更多
Many digital platforms have employed free-content promotion strategies to deal with the high uncertainty levels regarding digital content products.However,the diversity of digital content products and user heterogenei...Many digital platforms have employed free-content promotion strategies to deal with the high uncertainty levels regarding digital content products.However,the diversity of digital content products and user heterogeneity in content preference may blur the impact of platform promotions across users and products.Therefore,free-content promotion strategies should be adapted to allocate marketing resources optimally and increase revenue.This study develops personal-ized free-content promotion strategies based on individual-level heterogeneous treatment effects and explores the causes of their heterogeneity,focusing on the moderating effect of user engagement-related variables.To this end,we utilize ran-dom field experimental data provided by a top Chinese e-book platform.We employ a framework that combines machine learning with econometric causal inference methods to estimate individual treatment effects and analyze their potential mechanisms.The analysis shows that,on average,free-content promotions lead to a significant increase in consumer pay-ments.However,the higher the level of user engagement,the lower the payment lift caused by promotions,as more-engaged users are more strongly affected by the cannibalization effect of free-content promotion.This study introduces a novel causal research design to help platforms improve their marketing strategies.展开更多
The construction and development of social public management's new normal depend on the scientific transformation of government functionalization orientation and highlighting the role of grassroots public's ex...The construction and development of social public management's new normal depend on the scientific transformation of government functionalization orientation and highlighting the role of grassroots public's extensive illustrations on social issues and social conditions.Based on this situation,in the process of public participation mechanism construction,it is necessary to emphasize that the construction of joint elements should be carried out systematically and comprehensively,and to dig deep into the relations and functions of all elements.When the stability of public participation mechanism construction is fully guaranteed,it will extensively supervise and evaluate the development of government's social public management cause,help achieve the final goal of coordinating social development environment and social development elements,ensure that the intrinsic value of public participation mechanism can be thoroughly displayed.展开更多
文摘In the era of network live broadcasting for everyone,the development of live broadcasting platforms is also more intelligent and diversified.However,in the face of a large group of elderly users,the interface interaction design mode used is still mainly based on the interaction mode for young groups,and is not designed for elderly users.Therefore,a design method for optimizing the interaction interface of live broadcasting platform for elderly users was proposed in this study.Firstly,the case study method and Delphi expert survey method were used to determine the design needs of elderly users and the design mode was analysed.Secondly,the orthogonal design principle was used to design a test sample of the interactive interface of live broadcasting platform applicable for the elderly users,and then a user evaluation system was established to calculate the weights of the design elements using hierarchical analysis,and then the predictive relationship between the design mode of the interactive interface of live broadcasting platform and the elderly users was established by Quantitative Theory I.Finally,Genetic Algorithm was applied to generate the optimized design scheme.The results showed that the design method based on the Genetic Algorithm and the combination of Quantitative Theory can scientifically and effectively optimize the design of the interactive interface of the live broadcasting platform for the elderly users,and improve the experience of the elderly users.
基金supported by the National Natural Science Foundation of China(61901341).
文摘Using the existing positioning technology can easily obtain high-precision positioning information,which can save resources and reduce complexity when used in the communication field.In this paper,we propose a location-based user scheduling and beamforming scheme for the downlink of a massive multi-user input-output system.Specifically,we combine an analog outer beamformer with a digital inner beamformer.An outer beamformer can be selected from a codebook formed by antenna steering vectors,and then a reduced-complexity inner beamformer based on iterative orthogonal matrices and right triangular matrices(QR)decomposition is applied to cancel interuser interference.Then,we propose a low-complexity user selection algorithm using location information in this paper.We first derive the geometric angle between channel matrices,which represent the correlation between users.Furthermore,we derive the asymptotic signal to interference-plus-noise ratio(SINR)of the system in the context of two-stage beamforming using random matrix theory(RMT),taking into account inter-channel correlations and energies.Simulation results show that the algorithm can achieve higher system and speed while reducing computational complexity.
文摘With the arrival of the big data era,the phenomenon of information overload is becoming increasingly severe.In response to the common issue of sparse user rating matrices in recommendation systems,a collaborative filtering recommendation algorithm was proposed based on improved user profiles in this study.Firstly,a profile labeling system was constructed based on user characteristics.This study proposed that user profile labels should be created using basic user information and basic item information,in order to construct multidimensional user profiles.TF-IDF algorithm was used to determine the weights of user-item feature labels.Secondly,user similarity was calculated by weighting both profile-based collaborative filtering and user-based collaborative filtering algorithms,and the final user similarity was obtained by harmonizing these weights.Finally,personalized recommendations were generated using Top-N method.Validation with the MovieLens-1M dataset revealed that this algorithm enhances both recommendation Precision and Recall compared to single-method approaches(recommendation algorithm based on user portrait and user-based collaborative filtering algorithm).
基金the staged achievement of the MOE(Ministry of Education in China)Project of Humanities and Social Sciences(Project No.11YJC 840052)
文摘The article combines institutional change and social participation of the subjects. By investigating the expanding of community subject and gradually cultivating their ability to participate,we can test the achievements of community development in our country,and lay a foundation for reaching the social development goals.
文摘Many scholars have gradually realized that volunteer service can not only manifest the social value,but also become an effective way to enlarge citizen participation.Mainly from the aspects of the rationality of the increasing of citizen participation in volunteer service,this paper analyses the significance of volunteer service in the modernization transformation of China and puts forward some suggestions for the development of China' s volunteer service in the future.
基金supported by the National Key Laboratory for Comp lex Systems Simulation Foundation (6142006190301)。
文摘In the context of big data, many large-scale knowledge graphs have emerged to effectively organize the explosive growth of web data on the Internet. To select suitable knowledge graphs for use from many knowledge graphs, quality assessment is particularly important. As an important thing of quality assessment, completeness assessment generally refers to the ratio of the current data volume to the total data volume.When evaluating the completeness of a knowledge graph, it is often necessary to refine the completeness dimension by setting different completeness metrics to produce more complete and understandable evaluation results for the knowledge graph.However, lack of awareness of requirements is the most problematic quality issue. In the actual evaluation process, the existing completeness metrics need to consider the actual application. Therefore, to accurately recommend suitable knowledge graphs to many users, it is particularly important to develop relevant measurement metrics and formulate measurement schemes for completeness. In this paper, we will first clarify the concept of completeness, establish each metric of completeness, and finally design a measurement proposal for the completeness of knowledge graphs.
文摘In the data-driven era of the internet and business environments,constructing accurate user profiles is paramount for personalized user understanding and classification.The traditional TF-IDF algorithm has some limitations when evaluating the impact of words on classification results.Consequently,an improved TF-IDF-K algorithm was introduced in this study,which included an equalization factor,aimed at constructing user profiles by processing and analyzing user search records.Through the training and prediction capabilities of a Support Vector Machine(SVM),it enabled the prediction of user demographic attributes.The experimental results demonstrated that the TF-IDF-K algorithm has achieved a significant improvement in classification accuracy and reliability.
文摘With the rapid development of big data,online education can use big data technology to achieve personalized and intelligent education as well as improve learning effect and user satisfaction.In this study,the users of The Open University of China online education platform were taken as the research object,their user behavior data was collected,cleaned,and analyzed with text mining.The RFM model and the improved K-Means algorithm were used to construct the user portrait of the platform group and the needs and preferences of different types of the users were analyzded.Chinese word segmentation was used to show the key words of different types of users and the word cloud of their using frequency.The focus of different user groups was determined to facilitate for the follow-up course recommendation and precision marketing.Experimental results showed that the improved K-Means algorithm can well depict the behavior of group users.The index of silhouette score was improved to 0.811 by the improved K-Means algorithm,from random uncertainty to a fixed value,which can effectively solve the problem of inconsistent results caused by outlier sample points.
基金supported by the Anhui Postdoctoral Scientific Research Program Foundation(2022B579).
文摘Many digital platforms have employed free-content promotion strategies to deal with the high uncertainty levels regarding digital content products.However,the diversity of digital content products and user heterogeneity in content preference may blur the impact of platform promotions across users and products.Therefore,free-content promotion strategies should be adapted to allocate marketing resources optimally and increase revenue.This study develops personal-ized free-content promotion strategies based on individual-level heterogeneous treatment effects and explores the causes of their heterogeneity,focusing on the moderating effect of user engagement-related variables.To this end,we utilize ran-dom field experimental data provided by a top Chinese e-book platform.We employ a framework that combines machine learning with econometric causal inference methods to estimate individual treatment effects and analyze their potential mechanisms.The analysis shows that,on average,free-content promotions lead to a significant increase in consumer pay-ments.However,the higher the level of user engagement,the lower the payment lift caused by promotions,as more-engaged users are more strongly affected by the cannibalization effect of free-content promotion.This study introduces a novel causal research design to help platforms improve their marketing strategies.
基金supported by the Research Program of Henan Federation of Humanities and Social Sciences entitled“The Research of Chinese Higher Education Model”(SKL-2011-2135)
文摘The construction and development of social public management's new normal depend on the scientific transformation of government functionalization orientation and highlighting the role of grassroots public's extensive illustrations on social issues and social conditions.Based on this situation,in the process of public participation mechanism construction,it is necessary to emphasize that the construction of joint elements should be carried out systematically and comprehensively,and to dig deep into the relations and functions of all elements.When the stability of public participation mechanism construction is fully guaranteed,it will extensively supervise and evaluate the development of government's social public management cause,help achieve the final goal of coordinating social development environment and social development elements,ensure that the intrinsic value of public participation mechanism can be thoroughly displayed.
