Wild, Fridolin; Ochoa, Xavier ; Heinze, Nina ; Crespo, Raquel and Quick, Kevin
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The amount of information available to researchers today has increased in the last years at an unfathomable speed. Web 2.0 technology, especially social network tools and new communication platforms have added more points of access to the exploding number of informational offers. As scientists are increasingly using Web 2.0 for research, knowledge management, communication, and collaboration it is becoming more and more important for the users of these tools to be able to filter out (from their perspective and in the given situation) unwanted information. Moreover, it is even more important for researchers to filter through known and even unknown content to find relevant information, broaden their scope of knowledge about a certain field, remain up‐to‐date on the state‐of‐the‐art and expand their reach to other institutions or domains.
One possibility to make users aware of content available in their field of interest is through the use of recommender systems. We would like to outline how we propose a new recommender system using a method‐mix of data mining and social network analysis (SNA). This science proxy project is targeted towards resolving unwanted fragmentation with the help of recommendations extracted from publishing data from conferences such as EC‐TEL and – on the intervention side – with the help of the networked communication instrument ‘Flashmeeting’1. This recommender system aims at supporting scientists in the field of TEL to increase the quality of their collaboration in the wider community of peers.
|Item Type:||Conference Item|
|Copyright Holders:||2008 Not known|
|Academic Unit/Department:||Knowledge Media Institute|
|Interdisciplinary Research Centre:||Centre for Research in Computing (CRC)|
|Depositing User:||Kay Dave|
|Date Deposited:||05 Jan 2011 09:52|
|Last Modified:||26 Feb 2016 13:05|
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