◎演講日期：民國 105/10/27 星期四
◎Speaker ：Prof. Shih-Hung Wu
◎Date ：2016-10-27 (Thu.)
◎Time ：PM 1:30-3:20
◎Location：Room H604, Fu-Tien Building
On the online E-Commerce platform, customer reviews provides valuable opinions and relevant content, which will affect the perches behavior of other customers. Since the amount of online review grow fast, it is hard to read them all, therefore, a system that can find the reviews with better quality is necessary.
In order to better understand the quality of reviews. We proposed a system that can rank the reviews based on a set of linguistic features and a Support vector regression (SVR) model as a scorer. To evaluate our system, we collect 3730 Chinese reviews in eight product categories (books, digital cameras, tablet PC, backpacks, movies, men shoes, toys and cell phones) from Amazon.cn with the voting result of whether the review is helpful or not. Since the voting result might be biased by voting time and total voting number. We defined 4 types of evaluation index and compare the regression result to each index.
Prof. Shih-Hung Wu is an assistant professor at Department of Computer Science and Information Engineering, Chaoyang University of Technology, currently working on natural language processing related researches. He was a Post-Doctoral Fellow at Institute of Information Science, Academia Sinica in Taiwan. He received the B.S. degree from the National Taiwan University, the Master degree and the Ph.D. degree in Computer Science from the National Tsing Hua University, Taiwan, on 1993 and 1999 respectively. His research interests cover information retrieval, natural language processing, learning technology, and robotics.