Twitter Application to Chinese Language Learning: Lessons and Suggestions

Making a connection between the requirement of 140 characters and the need of intermediate-low learners of Chinese as a second language (CSL) to produce output in a less challenging environment, this action research engaged the college CSL students in tweeting practices. Based on the descriptive statistics of the students’ tweeting behavior and the students’ responses to the survey administered at the end of the semester, this article reflects and summarizes the lessons learned. The authors propose that structural designs in the form of projects or tasks should still be considered for social networking applications such as Twitter to be used as an educational tool. How to make better use of the social-networking aspect of Twitter and build a community of CSL learners and practitioners is also discussed

10,000+ Times Accelerated Robust Subset Selection (ARSS)

Subset selection from massive data with noised information is increasingly popular for various applications. This problem is still highly challenging as current methods are generally slow in speed and sensitive to outliers. To address the above two issues, we propose an accelerated robust subset selection (ARSS) method. Specifically in the subset selection area, this is the first attempt to employ the $\ell_{p}(0<p\leq1)$-norm based measure for the representation loss, preventing large errors from dominating our objective. As a result, the robustness against outlier elements is greatly enhanced. Actually, data size is generally much larger than feature length, i.e. $N\gg L$. Based on this observation, we propose a speedup solver (via ALM and equivalent derivations) to highly reduce the computational cost, theoretically from $O(N^{4})$ to $O(N{}^{2}L)$. Extensive experiments on ten benchmark datasets verify that our method not only outperforms state of the art methods, but also runs 10,000+ times faster than the most related method

前言

2015年春，嶺南大學召開以“明清文學與文論”爲主題的國際研討會，與會者均屬學界資深專家，他們所發表的論文代表著古典文學研究的前沿態勢，具有較高的學術價值。《嶺南學報》編委會經討論，決定以專輯形式，刊登此次會議成果，以與海内外同道切磋分享。 本輯《嶺南學報》之編輯，大致根據會議之主旨，即“小説、戲曲及文化”以及“明清詩學、詞學及文化”，這樣兩個板塊來安排，既凸顯縱向的歷史脈絡，也呈現横向的域内與域外的聯繫