Graz University of Technology

Recommendation engine providers for the IoT

logo-200x200-TU GrazMore than 200 years of research and teaching in the service of society has made Graz University of Technology (TU Graz) a top scientific establishment embodying one of the richest traditions in Austria. TU Graz is currently organised into 7 faculties with a total of 104 institutes. It has more than 10.200 students in the current academic year. TU Graz currently employs almost 1.300 scientific staff and more than 800 non-scientific staff. Institutes of TU Graz are involved in numerous FP7 research projects. The competences of the Applied Software Engineering group (Prof. Felfernig) at the Institute for Software Technology (IST) are in the areas of recommender systems, model-based diagnosis and repair, configuration of complex products & services, and Semantic Web. In these areas numerous scientific projects were performed, in particular the following. In the EU IST-5 project CAWICOMS (1999-2002) personalized configuration algorithms have been developed. The nationally funded project COHAVE (2006-2009) deals with the improvement of sales dialogs of recommender systems based on theories of decision psychology. The nationally funded project Koba4MS (2004-2007) aimed at advancing the state-of- the-art of knowledge-based recommendation. Its focus was to improve knowledge acquisition processes. The EU IST-6 FET project WS-Diamond (2005-2007) dealt with the diagnosis and repair of conversationally complex Web services. SoftNet (2003-2013) is the national competence cluster on Software Engineering. The nationally funded project WECARE (2009-2011) focuses on the exploitation of recommendation technologies for the personalization of re-configuration tasks. The nationally funded projects IntelliReq (2011-2013) and ICONE (2010-2013) focus on the development of recommendation algorithms for personalized requirements elicitation and knowledge engineering scenarios. PeopleViews (2014-2016) focuses on the integration of Human Computation techniques into recommender application development.

Role in project

Research in Recommender Systems and Configuration Systems has a long tradition and is manifested in numerous research projects on the EU level as well as on the national level. The Institute of Software Technology has co-organized the ACM Conference on Recommender Systems in 2009 (Prof. Felfernig as program co-chair). The institute contributed numerous publications in international journals and conferences such as Artificial Intelligence, Applied Intelligence, UMUAI, IJCAI, ECAI, and ACM Recommender Systems. Furthermore, Prof. Felfernig is one of the co- authors of the books on “Recommender Systems” published by Cambridge University Press in 2010 and “Knowledge-based Configuration” published by Elsevier/Morgan Kaufmann in 2014. Core competences that are contributed to the project are recommender systems, configuration systems, knowledge engineering, and machine learning.
TuGRaz will develop and integrate a recommender system on AGILE for automatic recommendations on software workflows (IoT apps) and modules to be used based on gateway configuration and user context.

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