Web service recommendation is one of the most important fi elds of research in the area of service computing. The two core problems of Web service recommendation are the prediction of unknown Qo S property values and ...Web service recommendation is one of the most important fi elds of research in the area of service computing. The two core problems of Web service recommendation are the prediction of unknown Qo S property values and the evaluation of overall Qo S according to user preferences. Aiming to address these two problems and their current challenges, we propose two efficient approaches to solve these problems. First, unknown Qo S property values were predicted by modeling the high-dimensional Qo S data as tensors, by utilizing an important tensor operation, i.e., tensor composition, to predict these Qo S values. Our method, which considers all Qo S dimensions integrally and uniformly, allows us to predict multi-dimensional Qo S values accurately and easily. Second, the overall Qo S was evaluated by proposing an efficient user preference learning method, which learns user preferences based on users' ratings history data, allowing us to obtain user preferences quantifiably and accurately. By solving these two core problems, it became possible to compute a realistic value for the overall Qo S. The experimental results showed our proposed methods to be more efficient than existing methods.展开更多
This study is designed to explore the impact of LLS （Language Learning Styles） on learning strategy preferences through questionnaire and data analysis. The aim of the study is to make an through investigation of Ch...This study is designed to explore the impact of LLS （Language Learning Styles） on learning strategy preferences through questionnaire and data analysis. The aim of the study is to make an through investigation of Chinese non-English majors＇ learning styles and their learning strategies in English study, and to analyze the impact of learning styles on learning strategy preferences statistically so as to provide empirical evidence in this field, and then present some implications for college English teaching and learning in Chinese context. This study has significance for pedagogy. Teachers should make language learners aware of their own learning styles and strategy preferences and help them select strategies matching their own style preferences in second language learning. It is hoped that this study can benefit language teachers, learners, and researchers to some extent and can spark more teaching research in the future.展开更多
基金supported by the Natural Science Foundation of Beijing under Grant No.4132048NSFC (61472047),and NSFC (61202435)
文摘Web service recommendation is one of the most important fi elds of research in the area of service computing. The two core problems of Web service recommendation are the prediction of unknown Qo S property values and the evaluation of overall Qo S according to user preferences. Aiming to address these two problems and their current challenges, we propose two efficient approaches to solve these problems. First, unknown Qo S property values were predicted by modeling the high-dimensional Qo S data as tensors, by utilizing an important tensor operation, i.e., tensor composition, to predict these Qo S values. Our method, which considers all Qo S dimensions integrally and uniformly, allows us to predict multi-dimensional Qo S values accurately and easily. Second, the overall Qo S was evaluated by proposing an efficient user preference learning method, which learns user preferences based on users' ratings history data, allowing us to obtain user preferences quantifiably and accurately. By solving these two core problems, it became possible to compute a realistic value for the overall Qo S. The experimental results showed our proposed methods to be more efficient than existing methods.
文摘This study is designed to explore the impact of LLS （Language Learning Styles） on learning strategy preferences through questionnaire and data analysis. The aim of the study is to make an through investigation of Chinese non-English majors＇ learning styles and their learning strategies in English study, and to analyze the impact of learning styles on learning strategy preferences statistically so as to provide empirical evidence in this field, and then present some implications for college English teaching and learning in Chinese context. This study has significance for pedagogy. Teachers should make language learners aware of their own learning styles and strategy preferences and help them select strategies matching their own style preferences in second language learning. It is hoped that this study can benefit language teachers, learners, and researchers to some extent and can spark more teaching research in the future.
