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Word clouds have emerged as a straightforward and visually appealing visualization method for text. They are used in various contexts as a means to provide an overview by distilling text down to those words that appear with highest frequency. Typically, this is done in a static way as pure text summarization. We think, however, that there is a larger potential to this simple yet powerful visualization...
In this contribution, we present a new application based on fuzzy linguistic information to evaluate the quality of digital libraries. The quality evaluation of digital libraries is defined using users' perceptions on the quality of digital services provided through their Web sites. We assume a fuzzy linguistic modeling to represent the users' perception and apply automatic tools of fuzzy computing...
The recent growing of multimedia in our lives requires an extensive use of metadata for multimedia management. Consequently, many metadata standards have appeared. Using these standards has become very complicated since they have been developed by independent communities. The content and context are usually described using several metadata standards. Accordingly, a multimedia user must be able to...
The service-oriented approach with his essential advantages of a uniform interface and the possibility to reuse distributed and heterogeneous services in other contexts has led to a high popularity in Business-to-Business (B2B) scenarios. However, the development of user interfaces (UI) lacks of comparable efforts for the Business-to-Consumer (B2C) interaction because B2C is not properly reflected...
In this paper we present Double Tree, a new visualization of Key Word In Context (KWIC) displays targeted to support linguistic analysis. Inspired by Wattenberg's and Viégas' [1] Word Tree visualization, Double Tree extends the idea of representing KWIC results as trees. We address several issues with Word Trees with respect to the specific demands of linguists and discuss the design decisions and...
Mining information from very large databases poses numerous challenges. In fact, systems that can mine such voluminous databases are increasingly desirable. In this context, we propose a generic approach of database summarization that takes into account the user's interest topic. Innovation in our work consists in the generation of a set of database summaries having different levels of granularity...
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