A unified learning paradigm for large-scale personalized information management

Statistical-learning approaches such as unsupervised learning, supervised learning, active learning, and reinforcement learning have generally been separately studied and applied to solve application problems. In this paper, we provide an overview of our newly proposed unified learning paradigm (ULP...

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Main Authors:	CHANG, Edward Y., HOI, Steven C. H., WANG, Xinjing, MA, Wei-Ying, LYU, Michael R.
格式:	text
語言:	English
出版:	Institutional Knowledge at Singapore Management University 2005
主題:	Databases and Information Systems
在線閱讀:	https://ink.library.smu.edu.sg/sis_research/4199
標簽:	添加標簽沒有標簽, 成為第一個標記此記錄!
機構:	Singapore Management University
語言:	English

id	sg-smu-ink.sis_research-5202
record_format	dspace
spelling	sg-smu-ink.sis_research-52022018-12-13T09:12:16Z A unified learning paradigm for large-scale personalized information management CHANG, Edward Y. HOI, Steven C. H. WANG, Xinjing MA, Wei-Ying LYU, Michael R. Statistical-learning approaches such as unsupervised learning, supervised learning, active learning, and reinforcement learning have generally been separately studied and applied to solve application problems. In this paper, we provide an overview of our newly proposed unified learning paradigm (ULP), which combines these approaches into one synergistic framework. We outline the architecture and the algorithm of ULP, and explain benefits of employing this unified learning paradigm on personalizing information management. 2005-08-16T07:00:00Z text https://ink.library.smu.edu.sg/sis_research/4199 info:doi/10.1109/EITC.2005.1544372 Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Databases and Information Systems
institution	Singapore Management University
building	SMU Libraries
continent	Asia
country	Singapore Singapore
content_provider	SMU Libraries
collection	InK@SMU
language	English
topic	Databases and Information Systems
spellingShingle	Databases and Information Systems CHANG, Edward Y. HOI, Steven C. H. WANG, Xinjing MA, Wei-Ying LYU, Michael R. A unified learning paradigm for large-scale personalized information management
description	Statistical-learning approaches such as unsupervised learning, supervised learning, active learning, and reinforcement learning have generally been separately studied and applied to solve application problems. In this paper, we provide an overview of our newly proposed unified learning paradigm (ULP), which combines these approaches into one synergistic framework. We outline the architecture and the algorithm of ULP, and explain benefits of employing this unified learning paradigm on personalizing information management.
format	text
author	CHANG, Edward Y. HOI, Steven C. H. WANG, Xinjing MA, Wei-Ying LYU, Michael R.
author_facet	CHANG, Edward Y. HOI, Steven C. H. WANG, Xinjing MA, Wei-Ying LYU, Michael R.
author_sort	CHANG, Edward Y.
title	A unified learning paradigm for large-scale personalized information management
title_short	A unified learning paradigm for large-scale personalized information management
title_full	A unified learning paradigm for large-scale personalized information management
title_fullStr	A unified learning paradigm for large-scale personalized information management
title_full_unstemmed	A unified learning paradigm for large-scale personalized information management
title_sort	unified learning paradigm for large-scale personalized information management
publisher	Institutional Knowledge at Singapore Management University
publishDate	2005
url	https://ink.library.smu.edu.sg/sis_research/4199
_version_	1770574425919324160

A unified learning paradigm for large-scale personalized information management

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