Title:	AUTOMATIC TOPIC IDENTIFICATION-ENABLED INTELLIGENT DOCUMENT ARCHIVING FOR THE THIN CLIENT-BASED CLOUD STORAGE
Author(s):	Keedong Yoo, Yungmok Yu
ISBN:	978-989-8533-14-2
Editors:	Hans Weghorn and Pedro Isaías
Year:	2012
Edition:	Single
Keywords:	Document centralization; Automatic archiving; Topic identification; Cloud storage
Type:	Short Paper
First Page:	400
Last Page:	404
Language:	English
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Paper Abstract:	The cloud storage which constitutes the structure for centralized management of organizational documents is gaining much interest because of its benefits in managing and securing information resources. However, cloud storage-based centralized repository also has problems in utilization, which are the difficulty in determining the proper category to store working documents and the complexity in retrieving a document. This paper proposes a methodology to resolve the problem by automating the processes of identifying the topic of working documents and storing them under the identified topic-based category of the cloud storage-based central repository. Without user’s direct definition about the title of a working document, it can be automatically stored under the identified topic-based category in the central repository. To demonstrate the validity of the proposed concepts, a prototype system enabling the function of automatic topic identification, automatic category searching, and automatic archiving is implemented.
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