Work

Statistical Learning-based Approach for Automatic Generation System of Multiple-choice Cloze Questions

Year: 2010

Type: article

Abstract: In this paper, we propose an automatic generation system of multiple-choice cloze questions from English texts. Empirical knowledge is necessary to produce appropriate questions, so machine learning is introduced to acquire knowledge from existing questions. To generate the questions from texts automatically, the system (1) extracts appropriate sentences for questions from texts based on Preference Learning, (2) estimates a blank part based on Conditional Random Field, and (3) generates distracters based on statistical patterns of existing questions.

Source: International Conference on Computers in Education

Authors: KOJIRI, Tomoko, GOTO, Takuya, WATANABE, Toyohide, IWATA, Tomoharu, YAMADA, Takeshi

Institutions: Nagoya University, NTT (Japan)

Language: English

Topic: Natural Language Processing Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: green

OpenAlex ID: W7217335044

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