• Journal of the Korean Society for information Management
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• v.33 no.2
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• pp.135-156
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• 2016

Recently, as the importance of user-oriented archives management is becoming increasingly, government archives try to serve interactive services using social network service (SNS) beyond one-way approaches. This study aims to analyze usage of government archives service in social media and examine users' interestedness. We especially select "National Archives of Korea" and "Presidential Archives" as target government archives and collect tweets from 2010 to 15th April 2016. Our study adopts informetric approaches and social media analysis including buzz analysis, time series analysis. We differentiate between the tweet collection posted by government archives themselves and the other collection generated by general users. Furthermore we conduct correlation analysis of tweet and social issues and propose application plan for government archives services in social media environment.

• Journal of the Korean Society for information Management
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• v.33 no.3
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• pp.263-285
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• 2016

Nowadays, Social Network Service (SNS), which has been in the spotlight as a way of communication, has become a most effective tool to improve easy of information use and accessibility for users. In this paper, we chose Twitter as the most representative SNS services because of automatic crawling and investigated tweet data gathered from domestic and foreign National Archives - NARA of U.S.A., TNA of U.K.. NAA of Australia, and National Archives of Korea. We also conducted information genres analysis and trend analysis by timeline. Information genres analysis shows how archives satisfied users' information needs as well as trends analysis of tweets helps to understand how users' interestedness was changed. Based on comparison results, we distilled four characteristics of National Archives and suggested vitalization ways for National Archives of Korea.

• The Journal of the Korea Contents Association
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• v.11 no.1
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• pp.56-64
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• 2011

It is difficult to discover frequent itemsets based on whole data from data stream since data stream has the characteristics of infinity and continuity. Therefore, a specialized data mining method, which reflects the properties of data and the requirement of users, is required. In this paper, we propose the method of FIMWB discovering the frequent itemsets which are reflecting the property that the recent events are more important than old events. Data stream is splitted into batches according to the given time interval. Our method gives a weighted value to each batch. It reflects user's interestedness for recent events. FP-Digraph discovers the frequent itemsets by using the result of FIMWB. Experimental result shows that FIMWB can reduce the generation of useless items and FP-Digraph method shows that it is suitable for real-time environment in comparison to a method based on a tree(FP-Tree).