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Because of the extensive user coverage of news sites and apps, greater social and commercial value can be realized if users can access their favourite news as easily as…
Because of the extensive user coverage of news sites and apps, greater social and commercial value can be realized if users can access their favourite news as easily as possible. However, news has a timeliness factor; there are serious cold start and data sparsity in news recommendation, and news users are more susceptible to recent topical news. Therefore, this study aims to propose a personalized news recommendation approach based on topic model and restricted Boltzmann machine (RBM).
Firstly, the model extracts the news topic information based on the LDA2vec topic model. Then, the implicit behaviour data are analysed and converted into explicit rating data according to the rules. The highest weight is assigned to recent hot news stories. Finally, the topic information and the rating data are regarded as the conditional layer and visual layer of the conditional RBM (CRBM) model, respectively, to implement news recommendations.
The experimental results show that using LDA2vec-based news topic as a conditional layer in the CRBM model provides a higher prediction rating and improves the effectiveness of news recommendations.
This study proposes a personalized news recommendation approach based on an improved CRBM. Topic model is applied to news topic extraction and used as the conditional layer of the CRBM. It not only alleviates the sparseness of rating data to improve the efficient in CRBM but also considers that readers are more susceptible to popular or trending news.
Poverty alleviation is a global challenge. Human society has never ceased to fight against poverty. China was once the developing country with the largest rural poor…
Poverty alleviation is a global challenge. Human society has never ceased to fight against poverty. China was once the developing country with the largest rural poor population in the world. Remarkable achievements have been made in China’s antipoverty program over the past decades, shaping a unique poverty reduction strategy with Chinese characteristics. The purpose of this paper is to first review the history of China’s rural reform and antipoverty, and then analyze the related policy systems, mechanism innovations and future challenges in poverty alleviation and development. At last, some specific policy implications were provided.
Literature on China’s antipoverty history was reviewed and mechanism innovations on targeted poverty alleviation strategy were investigated.
Along with the deepening of the rural reform, the poverty alleviation and development in new China have undergone six stages, and experienced a transformation from relief-oriented to development-oriented poverty alleviation. The object of poverty alleviation has gradually targeted with a transformation from poor counties/areas to villages/households, and the effectiveness of poverty alleviation is also gradually improved. However, the increase in the difficulty of antipoverty, fragile ecological environment, rapid population aging and rural decline poses challenges to the construction of a well-off society in an all-round way in China. Specific antipoverty measures were put forward based on the investigation. Finally, the authors emphasize the importance of strengthening the study of poverty geography.
This study investigates the history of China’s antipoverty policy and analyzes the future challenges for implementing targeted poverty alleviation policy. These findings will lay a foundation for the formulation of China’s antipoverty policies after 2020, and provide experience for poverty alleviation in other developing countries around the world.