Current situations of water conservancy development in China include:there is serious water shortage and pollution;total water reservoir capacity is large but most are dangerous reservoirs;water is widely distributed ...Current situations of water conservancy development in China include:there is serious water shortage and pollution;total water reservoir capacity is large but most are dangerous reservoirs;water is widely distributed and directly serves the masses;business is comprehensive and many fields are involved;projects include public welfare and operating types;great regional difference and problems are varied;utilization methods are extensive and water environment is vulnerable.Based on these situations,this paper analyzes the public goods feature of water resource facilities and management mechanism,and points out that water conservancy development should not merely depend on the market force.Then,it discusses that the influence and trust of transformation period on the whole social members are requirements of new harmonious rural communities,and expounds the necessity of trust for building long-term mechanism for water conservancy development.Finally,it presents policy suggestions:trust is closely connected with benefits of every person,thus developing community trust should begin with every individual;building long-term mechanism for water conservancy development should rely on cultivating highly trust-based rural community shared values.展开更多
With the rapid development of social network in recent years, a huge number of social information has been produced. As traditional recommender systems often face data sparsity and cold-start problem, the use of socia...With the rapid development of social network in recent years, a huge number of social information has been produced. As traditional recommender systems often face data sparsity and cold-start problem, the use of social information has attracted many researchers' attention to improve the prediction accuracy of recommender systems. Social trust and social relation have been proven useful to improve the performance of recommendation. Based on the classic collaborative filtering technique, we propose a PCCTTF recommender method that takes the rating time of users, social trust among users, and item tags into consideration, then do the item recommending. Experimental results show that the PCCTTF method has better prediction accuracy than classical collaborative filtering technique and the state-of-the-art recommender methods, and can also effectively alleviate data sparsity and cold-start problem. Furthermore, the PCCTTF method has better performance than all the compared methods while counting against shilling attacks.展开更多
文摘Current situations of water conservancy development in China include:there is serious water shortage and pollution;total water reservoir capacity is large but most are dangerous reservoirs;water is widely distributed and directly serves the masses;business is comprehensive and many fields are involved;projects include public welfare and operating types;great regional difference and problems are varied;utilization methods are extensive and water environment is vulnerable.Based on these situations,this paper analyzes the public goods feature of water resource facilities and management mechanism,and points out that water conservancy development should not merely depend on the market force.Then,it discusses that the influence and trust of transformation period on the whole social members are requirements of new harmonious rural communities,and expounds the necessity of trust for building long-term mechanism for water conservancy development.Finally,it presents policy suggestions:trust is closely connected with benefits of every person,thus developing community trust should begin with every individual;building long-term mechanism for water conservancy development should rely on cultivating highly trust-based rural community shared values.
基金Supported by the National Natural Science Foundation of China(71662014,61602219,71861013)。
文摘With the rapid development of social network in recent years, a huge number of social information has been produced. As traditional recommender systems often face data sparsity and cold-start problem, the use of social information has attracted many researchers' attention to improve the prediction accuracy of recommender systems. Social trust and social relation have been proven useful to improve the performance of recommendation. Based on the classic collaborative filtering technique, we propose a PCCTTF recommender method that takes the rating time of users, social trust among users, and item tags into consideration, then do the item recommending. Experimental results show that the PCCTTF method has better prediction accuracy than classical collaborative filtering technique and the state-of-the-art recommender methods, and can also effectively alleviate data sparsity and cold-start problem. Furthermore, the PCCTTF method has better performance than all the compared methods while counting against shilling attacks.
