The personal domain of Quintin Siebers

Social Media

You can connect with me on one of the following social media platforms that I use

Open Source

I'm actively involved in several open source projects


I've written several papers during my study at Maastricht Univeristy, and during projects.

  • The application of self-organizing maps on semantic data in the form of a topic map (Master Thesis paper) — 2012
    Self organizing maps (SOMs) is a popular technique for clustering data in the text mining field. Topic Maps is a standard for storing knowledge comparable to RDF. Unlike a document made up of words that indicate semantic value, a topic map stores this semantic value in its different constructs. The application of SOMs on Topic Maps has not yet been researched. This thesis researches the application of SOM networks on Topic Maps based data.
  • A Context Aware Recommender System for Creativity Support Tools — 2011 G.A. Sielis, C. Mettouris, G.A. Papadopoulos, A. Tzanavari R.M.G. Dols, Q.H.J.F. Siebers
    The development of methods that can enhance the creativity process is becoming a continuous necessity. Through the years several researchers modelled and defined creativity focusing to the psychological aspect of the topic. More recent researchers approach creativity as a computerized process by simulating it within creativity support tools (CST). This article supports that usage of context aware recommender system, in creativity support tools and more specifically, collaborative creativity support tools (CCST) can enhance creativity process. In this work we focus on the development of a context awareness recommender system and look into how such a system can be useful for the creativity process, through preliminary evaluation results in regards to its usefulness and usability.
  • Literature review - Automated knowledge generation in Topic Maps
    Reviews three publications that discuss or propose a way of automating knowledge generation in Topic Maps. The presentation of P. Kruijsen offers the use of inference rules as the bases of logical deduction. The paper of Q. Siebers further expands this idea to an implementable solution. The presentation of L. Garshol uses logical induction by means of statistical analysis of keywords. The inference rule method has a strong logical bases. The statistical method has a strong automatization level. The combination of these methods – and with others – might produce better results for automated knowledge generation. More research is needed in this field.
  • Implementing Inference Rules in the Topic Maps Model (Bachelor Thesis paper) — 2006
    This paper supplies a theoretical approach on implementing inference rules in the Topic Maps model. Topic Maps is an ISO standard that allows for the modeling and representation of knowledge in an interchangeable form, that can be extended by inference rules. These rules specify conditions for inferrable facts. Any implementation requires a syntax for stor- age in a file, a storage model and method for processing and a system to keep track of changes in the inferred facts. The most flexible and optimisable storage model is a controlled cache, giving options for processing. Keeping track of changes is done by listeners.