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Collaborative tagging have emerged as a ubiquitous way to annotate and organize online resources. As a kind of descriptive keyword, large amount of tags are created and associated to multiple types of resources, e.g., web pages, photos, videos and tweets. Users’ tagging actions over time reflect their changing interests. Monitoring and analyzing the(More)
Collaborative tagging becomes a common feature of current web sites, facilitating ordinary users to annotate and represent online resources. The large collection of tags and their relationships form a tag space. In this kind of tag space, the popularity and correlation amongst tags capture the current social interests. Tags are freely chosen keywords and(More)
— Web 2.0 users generate and spread huge amounts of messages in online social media. Such user-generated contents are mixture of temporal topics (e.g., breaking events) and stable topics (e.g., user interests). Due to their different natures, it is important and useful to distinguish temporal topics from stable topics in social media. However, such a(More)
Burst detection is an important topic in temporal stream analysis. Usually, only the textual features are used in burst detection. In the theme extraction from current prevailing social media content, it is necessary to consider not only textual features but also the pervasive collaborative context, e.g., resource lifetime and user activity. This paper(More)
— Textual web pages dominate web search engines nowadays. However, there is also a striking increase of struc-tured data on the web. Efficient keyword query processing on structured data has attracted enough attention, but effective query understanding has yet to be investigated. In this paper, we focus on the problem of keyword query reformulation in the(More)
— Collaborative tagging systems have emerged as an ubiquitous way to annotate and organize online resources. The users' tagging actions over time reflect the changing of their interests. In this paper, we propose to detect bursty tagging event, which captures the relations among a group of correlated tags where the tags are either bursty or associated with(More)
We address the following two research questions: (1) under what circumstances will firms prefer internal SaaS development to external sourcing? and (2) how does the SaaS development mode affect firm performance? We examine the SaaS development actions in the computer industry (SIC code 737) from 2003 to 2012. The preliminary analysis results suggest that(More)
Collaborative tagging systems allow users to label online resources. The tags are generally correlated and evolving according to the change of web contents, and the popularity of tags represent evolution of social interests. Tag taxonomy is a promising solution to organize the data in tagging systems. In this demonstration, we propose to construct the(More)
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