期刊名称:TELKOMNIKA (Telecommunication Computing Electronics and Control)
印刷版ISSN:2302-9293
出版年度:2015
卷号:13
期号:1
页码:357-363
DOI:10.12928/telkomnika.v13i1.648
语种:English
出版社:Universitas Ahmad Dahlan
摘要:Question generating is the task of automatically generating questions from various inputs such as raw text, database, or semantic representation. In this paper, we attempt to describe a general framework that could help develop and characterize efforts to medical Indonesian generates questions medical text. We propose a new style of question generation that actively uses sentences within a document as a source of answer. We use manually written rules to perform a sequence of general purpose a syntactic transformation (e.g. identification of keywords or key phrase to NER based on PICO frame) to turn a declarative sentence into questions. The final result of this research is a pattern of question and answer pairs, where the test results show the pattern matching algorithm precision value of 0.101 and a recall of 0.712.
其他摘要:Question generating is the task of automatically generating questions from various inputs such as raw text, database, or semantic representation. In this paper, we attempt to describe a general framework that could help develop and characterize efforts to medical Indonesian generates questions medical text. We propose a new style of question generation that actively uses sentences within a document as a source of answer. We use manually written rules to perform a sequence of general purpose a syntactic transformation (e.g. identification of keywords or key phrase to NER based on PICO frame) to turn a declarative sentence into questions. The final result of this research is a pattern of question and answer pairs, where the test results show the pattern matching algorithm precision value of 0.101 and a recall of 0.712.