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Personalization of Social Media Social communities are changing the world. People are starting to create digital identities online to extend or even change their real lives. Fact is, that many people spend hours per day organising their digital lives on sites like YouTube, Flickr, Facebook, Twitter, Del.icio.us and many more.In this ever growing online community, conventional search just cannot cope with the dynamic nature and lack of textual information in these systems. Luckily the information that is stored online can be used to create user profiles that tell us exactly where a user’s interests lie. This knowledge can be used in a system that guides a user in his search or even dynamically recommends items of interest to him. A recommendation system could recommend movies, websites or even introduce you to people with similar interests. Recently, social tagging has appeared to be a promising method to organize data within these user communities. Many people are willing to invest some time in attaching a handful of keywords to the content they upload or view. In my research I am investigating if the tags that are manually added to content within social networks can improve the performance of a recommendation system that is solely based on a users preference. 
Besides the retrieval of interesting content, social media should allow users to click on other people, to explore their preferences and in this way get to know other network users. To meet these requirements, we suggest a framework that can always provide the user with relevant content, tags and people. This framework gives an overview of the user tasks that qualify for personalization in a collaborative tagging system.  Tagging digital content improves social recommendations
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Master thesis on the combination of gene expression profiles and transcription factor binding motifs to advance from co-expression to co-regulation. Thesis |