It has been suggested that text-based computer-mediated communication can help learners to use target language both in classrooms and in social contexts.It’s necessary to investigate the effect of text-based CMC on l...It has been suggested that text-based computer-mediated communication can help learners to use target language both in classrooms and in social contexts.It’s necessary to investigate the effect of text-based CMC on learners’communicative competence by conducting the method of systematic review.The findings implied that text-based CMC settings allowed learners to interact.The interaction provided learners with more opportunities to develop their communicative competence of target language.展开更多
With the development of large scale text processing, the dimension of text feature space has become larger and larger, which has added a lot of difficulties to natural language processing. How to reduce the dimension...With the development of large scale text processing, the dimension of text feature space has become larger and larger, which has added a lot of difficulties to natural language processing. How to reduce the dimension has become a practical problem in the field. Here we present two clustering methods, i.e. concept association and concept abstract, to achieve the goal. The first refers to the keyword clustering based on the co occurrence of展开更多
文摘It has been suggested that text-based computer-mediated communication can help learners to use target language both in classrooms and in social contexts.It’s necessary to investigate the effect of text-based CMC on learners’communicative competence by conducting the method of systematic review.The findings implied that text-based CMC settings allowed learners to interact.The interaction provided learners with more opportunities to develop their communicative competence of target language.
文摘With the development of large scale text processing, the dimension of text feature space has become larger and larger, which has added a lot of difficulties to natural language processing. How to reduce the dimension has become a practical problem in the field. Here we present two clustering methods, i.e. concept association and concept abstract, to achieve the goal. The first refers to the keyword clustering based on the co occurrence of