With the rapid development of Web 2.0, more and more people are sharing their opinions about online products, so there is much product review data. However, it is difficult to compare products directly using ratings b...With the rapid development of Web 2.0, more and more people are sharing their opinions about online products, so there is much product review data. However, it is difficult to compare products directly using ratings because many ratings are based on different scales or ratings are even missing. This paper addresses the following question： given textual reviews, how can we automatically determine the semantic orientations of reviewers and then rank different items？ Due to the absence of ratings in many reviews, it is difficult to collect sufficient rating data for certain specific categories of products （e.g., movies）, but it is easier to find rating data in another different but related category （e.g., books）. We refer to this problem as transfer rating, and try to train a better ranking model for items in the interested category with the help of rating data from another related category. Specifically, we developed a ranking-oriented method called TRate for determining the semantic orientations and for ranking different items and formulated it in a regularized algorithm for rating knowledge transfer by bridging the two related categories via a shared latent semantic space. Tests on the Epinion dataset verified its effectiveness.展开更多
Using economics and game theory, two kinds of models have been proposed in this paper under the assumption that foreign and domestic firms behave under the condition of dynamic game of perfect information. One model i...Using economics and game theory, two kinds of models have been proposed in this paper under the assumption that foreign and domestic firms behave under the condition of dynamic game of perfect information. One model is for calculating Anti-dumping rate which is obtained according to current regulations of Anti-dumping, but it is not optimal. The other is an optimal model of Anti-dumping which is obtained according to the maximum principle of domestic social welfare. Then, through the comparison of this two models in detail, several shortages have been revealed about Anti-dumping rate model based on current regulations of Anti-dumping. Finally, a suggestion is indicated that WTO and China should use the optimal model to calculate Anti-dumping rate.展开更多
基金supported by the National Natural Science Foundation of China (No. 60773061)the National Natural Science Foundation of Jiangsu Province of China (No. BK2008381)+1 种基金supported by the National High-Tech Research and Development (863) Program of China (No.2009AA01Z138)supported by the National Natural Science Foundation of China (No.70771043)
文摘With the rapid development of Web 2.0, more and more people are sharing their opinions about online products, so there is much product review data. However, it is difficult to compare products directly using ratings because many ratings are based on different scales or ratings are even missing. This paper addresses the following question： given textual reviews, how can we automatically determine the semantic orientations of reviewers and then rank different items？ Due to the absence of ratings in many reviews, it is difficult to collect sufficient rating data for certain specific categories of products （e.g., movies）, but it is easier to find rating data in another different but related category （e.g., books）. We refer to this problem as transfer rating, and try to train a better ranking model for items in the interested category with the help of rating data from another related category. Specifically, we developed a ranking-oriented method called TRate for determining the semantic orientations and for ranking different items and formulated it in a regularized algorithm for rating knowledge transfer by bridging the two related categories via a shared latent semantic space. Tests on the Epinion dataset verified its effectiveness.
文摘Using economics and game theory, two kinds of models have been proposed in this paper under the assumption that foreign and domestic firms behave under the condition of dynamic game of perfect information. One model is for calculating Anti-dumping rate which is obtained according to current regulations of Anti-dumping, but it is not optimal. The other is an optimal model of Anti-dumping which is obtained according to the maximum principle of domestic social welfare. Then, through the comparison of this two models in detail, several shortages have been revealed about Anti-dumping rate model based on current regulations of Anti-dumping. Finally, a suggestion is indicated that WTO and China should use the optimal model to calculate Anti-dumping rate.
