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EFFICIENT TRANSFER LEARNING SCHEMES FOR PERSONALIZED LANGUAGE MODELING USING RECURRENT NEURAL NETWORK : 순환신경망을 이용한 개인화 언어모델 학습 방법에 관한 연구
DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | 정교민 | - |
dc.contributor.author | 윤승현 | - |
dc.date.accessioned | 2017-07-14T02:43:41Z | - |
dc.date.available | 2017-07-14T02:43:41Z | - |
dc.date.issued | 2017-02 | - |
dc.identifier.other | 000000140914 | - |
dc.identifier.uri | https://hdl.handle.net/10371/122836 | - |
dc.description | 학위논문 (석사)-- 서울대학교 대학원 : 전기·정보공학부, 2017. 2. 정교민. | - |
dc.description.abstract | In this paper, we propose an efficient transfer leaning methods for training a personalized language model using a recurrent neural network with long short-term memory architecture. With our proposed fast transfer learning schemes, a general language model is updated to a personalized language model with a small amount of user data and a limited computing resource. These methods can be applied especially useful to a mobile device environment while the data is prevented from transferring out of the device for privacy purposes. Through experiments on dialogue data in a drama, it is verified that our transfer learning methods have successfully generated the personalized language model. | - |
dc.description.tableofcontents | 1 INTRODUCTION 1
2 RELATED WORK 3 3 METHODOLOGY 5 3.1 Language Model 5 3.1.1 Sentence Completion Language Model 6 3.1.2 Message-Reply Prediction Language Model 6 3.2 Proposed Methods 7 3.2.1 Fast Transfer Learning Schemes 7 3.3 Measures 8 3.3.1 Cross Entropy Metric 8 4 EXPERIMENTS 11 4.1 Datasets 11 4.2 Test Results 12 4.2.1 Literary-Style to Spoken-Style Sentence Completion 12 4.2.2 General-Style to Personal-Style Message-Reply Prediction 13 5 CONCLUSION 20 Abstract (In Korean) 24 | - |
dc.format | application/pdf | - |
dc.format.extent | 2076815 bytes | - |
dc.format.medium | application/pdf | - |
dc.language.iso | en | - |
dc.publisher | 서울대학교 대학원 | - |
dc.subject | 자연어처리 | - |
dc.subject | 딥러닝 | - |
dc.subject | 순환신경망모델 | - |
dc.subject | 개인정보보호 | - |
dc.subject | 언어모델 | - |
dc.subject.ddc | 621 | - |
dc.title | EFFICIENT TRANSFER LEARNING SCHEMES FOR PERSONALIZED LANGUAGE MODELING USING RECURRENT NEURAL NETWORK | - |
dc.title.alternative | 순환신경망을 이용한 개인화 언어모델 학습 방법에 관한 연구 | - |
dc.type | Thesis | - |
dc.description.degree | Master | - |
dc.citation.pages | 24 | - |
dc.contributor.affiliation | 공과대학 전기·정보공학부 | - |
dc.date.awarded | 2017-02 | - |
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