Autor:	Luo, Wencan, Liu, Fei, Liu, Zitao, Litman, Diane
Rok vydání:	2018
Předmět:	Computer Science - Computation and Language
Druh dokumentu:	Working Paper
Popis:	Student course feedback is generated daily in both classrooms and online course discussion forums. Traditionally, instructors manually analyze these responses in a costly manner. In this work, we propose a new approach to summarizing student course feedback based on the integer linear programming (ILP) framework. Our approach allows different student responses to share co-occurrence statistics and alleviates sparsity issues. Experimental results on a student feedback corpus show that our approach outperforms a range of baselines in terms of both ROUGE scores and human evaluation. Comment: 6 pages
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1805.10395 Zobrazit plný text záznamu View this record from Arxiv