[publication] Finding and Exploring Commonalities Between Researchers Using the ResXplorer

Our publication about „Finding and Exploring Commonalities Between Researchers Using the ResXplorer“ at this year HCII conference in Crete, Greece is now online available.
Abstract:

Researcher community produces a vast of content on the Web. We assume that every researcher interest oneself in events, persons and findings of other related community members who share the same interest. Although research related archives give access to their content most of them lack on analytic services and adequate visualizations for this data. This work resides on our previous achievements we made on semantically and Linked Data driven search and user inter- faces for Research 2.0. We show how researchers can find and visually explore commonalities between each other within their interest domain, by introducing for this matter the user interface of “ResXplorer”, and underlying search infrastructure operating over Linked Data Knowledge Base of research resources. We discuss and test most important com- ponents of “ResXplorer” relevant for detecting commonalities between researchers, closing up with conclusions and outlook for future work.

Reference: Softic, S., De Vocht, L., Mannens, E., Van de Walle, R., Ebner, M. (2014). Finding and Exploring Commonalities Between Researchers Using the ResXplorer. Learning and Collaboration Technologies. Technology-Rich Environments for Learning and Collaboration. Panayiotis, Z., Ioannou, A. (Ed.) Lecture Notes in Computer Science, Volume 8524. Springer, pp. 486-494

[publication] Thought Bubbles: a conceptual prototype for a Twitter based recommender system for research 2.0

The draft version of our publication „Thought Bubbles: a conceptual prototype for a Twitter based recommender system for research 2.0“ at this year i-KNOW conference is now online available. The poster is already published here.
Abstract:

The concept of so called Thought Bubbles deals with the problem of finding appropriate new connections within Social Networks, especially Twitter. As a side effect of exploring new users, Tweets are classified and rated and are used for generating a kind of news feed, which will extend the personal Twitter feed. Each user has several interests that can be classified by evaluating his Tweets in first place and secondly by evaluating user related and already existing contacts. By categorizing a user and concerned connections, one can be placed in an imaginary category specific subset of users, called Thought Bubbles. Following the trace of people who are also active within the same specific Thought Bubble, should reveal interesting and helpful connections between similar minded users.

Reference: Thonhauser, P., Softic, S., Ebner, M. (2012) Thought Bubbles: a conceptual prototype for a Twitter based recommender system for research 2.0. In Proceedings of the 12th International Conference on Knowledge Management and Knowledge Technologies (i-KNOW ’12). ACM, New York, NY, USA, , Article 32 , 4 pages. DOI=10.1145/2362456.2362496

[poster] A Conceptual Prototype for a Twitter Based Recommender System for Research 2.0

Im Rahmen der iKnow 2012 Konferenz in Graz haben wir ein Shortpaper mit einer Posterpräsentation eingereicht. Der Titel lautet: „A Conceptual Prototype for a Twitter Based Recommender System for Research 2.0 “ und wird von Patrick vorgestellt.
Hier einmal das Poster: