Computer Science Department

Lehrstuhl für Dienstleistungsinformatik / e-Services Research Group

Navigation


Chair endowed by

  • Westfälisch-Lippischer Sparkassen- und Giroverband
  • Sparkasse Dortmund
  • Gesellschaft der Freunde der TU Dortmund e.V.

Lehrstuhl 13 - Dienstleistungsinformatik, Prof. Dietmar Jannach

The research focus of the e-services Research Group lies the areas of recommender systems and, more generally, the application of intelligent systems technology and artificial intelligence to practical problems.

In the area of teaching, the group is responsible for a business- and application-oriented specialization area in the Computer Science curriculum at TU Dortmund (Dienstleistungsinformatik). Courses include Web technologies, Business Information Systems and SAP ERP and SAP Netweaver, as well as IT Management, IT Service Management and the Information Technology Infrastructure Library (ITIL).

The group is headed by Prof. Dr. Dietmar Jannach (Chair).


Quick-links teaching LS13

Sommersemester 2017

Quick-links research

TU-Startup

News

24.03.2017: Paper on optimization of recommendation lists accepted for publication in Expert Systems With Applications

04.02.2017: Paper on user interation with recommender systems accepted for publication in ACM TiiS

24.01.2017: Paper on search result personalization accepted for FLAIRS 2017

21.11.2016: Three papers accepted for the Recommender Systems Track of ACM SAC 2017

21.11.2016: Our group will give a tutorial on interactive recommender systems at ACM IUI 2017

17.11.2016: Our new book on Music Data Analysis is out.

06.10.2016: Our paper on interactive model-based diagnosis received a best paper award at DX'16 (pdf)

03.09.2016: Paper on trust in recommender systems accepted for E-Commerce Research and Applications.

18.07.2016: Paper on mere presence effects of recommenders accepted for IntRS 2016 workshop.

18.07.2016: Paper on sequential model-based diagnosis accepted at DX 2016 workshop.

14.07.2016: Received the 2015 James Chen Award for best UMUAI paper for our work on recommendation biases.

14.07.2016: Our paper on reminders in recommendations received the Best Student Paper award at UMAP '16.

14.06.2016: Paper on past, present and future of recommender systems accepted at ACM RecSys 2016.