An LSTM model for cloze-style machine comprehension

• Main Authors: WANG, Shuohang, JIANG, Jing
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2018
• Subjects: Artificial Intelligence and Robotics; Databases and Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/4084; https://ink.library.smu.edu.sg/context/sis_research/article/5087/viewcontent/13._Jul042018___An_LSTM_Model_for_Cloze_Style_Machine_Comprehension__CICling2018_.pdf
• Institution: Singapore Management University

Machine comprehension is concerned with teaching machines to answer reading comprehension questions. In this paper we adopt an LSTM-based model we designed earlier for textual entailment and propose two new models for cloze-style machine comprehension. In our first model, we treat the document as a...