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5篇 您的检索式：作者名="Seonho Kim"

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		题名	作者	年代	出处	被引量
	1	In vitro experiment of the pressure regulating valve for a glaucoma implant 显示文摘	Bae Byunghoon Kee Hongseok Kim Seonho	2003	Journal of Micromechanics and Microengineer- ing2003，13，5：	1
	2	An Inertial Grade LaterallyDriven MEMS Differential Resonant Accelerometer显示文摘	Seonho Seok ak Kim Kukjin Chun	2004	Sensors and Actuators2004，，：	1
	3	A Study on Resonant Frequency and Q Factor Tunings for MEMS Vibratory Gyroscopes显示文摘	Jeong Chihwan Seok Seonho Lee Byeungleul Kim Hyeonched Chun Kukjin	2004	Journal of Micromechanics and Microengineering2004，14，11：	1
	4	Kemel approaches for genie interaction extraetion显示文摘	Seonho Kim Juntae Yoon Yang Jihoon	2008	Bioinformatics2008，24，1：	1
	5	Information Extraction Based on Multi-turn Question Answering for Analyzing Korean Research Trends显示文摘Analyzing Research and Development(R&D)trends is important because it can influence future decisions regarding R&D direction.In typical trend analysis,topic or technology taxonomies are employed to compute the popularities of the topics or codes over time.Although it is simple and effective,the taxonomies are difficult to manage because new technologies are introduced rapidly.Therefore,recent studies exploit deep learning to extract pre-defined targets such as problems and solutions.Based on the recent advances in question answering(QA)using deep learning,we adopt a multi-turn QA model to extract problems and solutions from Korean R&D reports.With the previous research,we use the reports directly and analyze the difficulties in handling them using QA style on Information Extraction(IE)for sentence-level benchmark dataset.After investigating the characteristics of Korean R&D,we propose a model to deal with multiple and repeated appearances of targets in the reports.Accordingly,we propose a model that includes an algorithm with two novel modules and a prompt.A newly proposed methodology focuses on reformulating a question without a static template or pre-defined knowledge.We show the effectiveness of the proposed model using a Korean R&D report dataset that we constructed and presented an in-depth analysis of the benefits of the multi-turn QA model.	Seongung Jo Heung-Seon Oh Sanghun Im Gibaeg Kim Seonho Kim	2023	Computers, Materials & Continua2023，，2：	0

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