About me

Dominik Kowald

Dr. Dominik Kowald is a post-doctoral researcher in the Social Computing research area at the Know-Center, Austria's leading research center for data-driven business and big data analytics. He has a PhD. (with hons), MSc. (with hons) and BSc. in Computer Science from Graz University of Technology, and before that was attending the College of Industrial Engineering specialising in Manufacturing Computer Science (BULME Graz). He has finished his PhD in October 2017 in the course of the European-funded research projects Learning Layers and AFEL on cognitive-inspired recommender systems for social tagging and microblogging environments. Currently he is working as co-task leader in the AI4EU initiative. Apart from that, he was working in several other industry-driven and European-funded research projects such as Organic Lingua and MoreGrasp. His research interests are in the fields of recommender systems, social tagging and microblogging systems, information retrieval, Big Data, Data Science, Open Science and complex network analytics.
Full cv ( .pdf) and dissertation summary ( .pdf) ( slides).

Selected publications (last five years)

  • Hasani-Mavriqi, I., Kowald, D., Helic, D., & Lex, E. (2018). Consensus Dynamics in Online Collaboration Systems. Computational Social Networks Journal. SpringerOpen. ( .pdf)
  • Kowald, D., Pujari, S., & Lex, E. (2017). Temporal Effects on Hashtag Reuse in Twitter: A Cognitive-Inspired Hashtag Recommendation Approach. In Proceedings of the 26th International World Wide Web Conference (WWW'2017). ACM. ( .pdf)
  • Trattner, C., Kowald, D., Seitlinger, P., Kopeinik, S., & Ley, T. (2016). Modeling Activation Processes in Human Memory to Predict the Reuse of Tags. The Journal of Web Science (JWS). Vol. 2, No. 1, pp 1 – 18. ( .pdf)
  • Kowald, D., & Lex, E. (2015). Evaluating Tag Recommender Algorithms in Real-World Folksonomies: A Comparative Study. In Proceedings of the 9th ACM Conference on Recommender Systems (RecSys'2015). ACM. ( .pdf) ( poster)
  • Kowald, D., Seitlinger, P., Trattner, C., & Ley, T. (2014). Long Time no See: The Probability of Reusing Tags as a Function of Frequency and Recency. In Proceedings of the companion publication of the 23rd international conference on World wide web companion (WWW'2014), pp. 463-468. International World Wide Web Conferences Steering Committee. ( .pdf)


Publications

Please also have a look at my GoogleScholar, ORCID, DBLP, ACM DL, Mendeley, ResearcherID and ResearchGate profiles.

Journal articles and book contributions

  1. Ruiz-Calleja, A., Dennerlein, S., Kowald, D., Theiler, D., Lex, E., & Ley, T. (2019). An Infrastructure for Workplace Learning Analytics: Tracing Knowledge Creation with the Social Semantic Server. Journal of Learning Analytics. SoLAR. ( .pdf)
  2. Hasani-Mavriqi, I., Kowald, D., Helic, D., & Lex, E. (2018). Consensus Dynamics in Online Collaboration Systems. Computational Social Networks Journal. SpringerOpen. ( .pdf)
  3. Kowald, D. (2017). Modeling Activation Processes in Human Memory for Tag Recommendations: Using Models from Human Memory Theory to Implement Recommender Systems for Social Tagging and Microblogging Environments. Suedwestdeutscher Verlag fuer Hochschulschriften. ISBN: 978-620-2-32072-6. ( .pdf)
  4. Seitlinger, P., Ley, T., Kowald, D., Theiler, D., Hasani-Mavriqi, I., Dennerlein, S., Lex, E., & Albert, D. (2017). Balancing the Fluency-Consistency Tradeoff in Collaborative Information Search with a Recommender Approach. International Journal of Human–Computer Interaction (HCI). ( .pdf)
  5. Kopeinik, S., Kowald, D., Hasani-Mavriqi, I., & Lex, E. (2017). Improving Collaborative Filtering Using a Cognitive Model of Human Category Learning. The Journal of Web Science (JWS). Vol. 2, No 4, pp 45 - 61 ( .pdf)
  6. Trattner, C., Kowald, D., Seitlinger, P., Kopeinik, S., & Ley, T. (2016). Modeling Activation Processes in Human Memory to Predict the Reuse of Tags. The Journal of Web Science (JWS). Vol. 2, No. 1, pp 1 – 18. ( .pdf)
  7. Santos, P., Dennerlein, S., Theiler, D., Cook, J., Treasure-Jones, T., Holley, D., Kerr, M., Attwell, G., Kowald, D., & Lex, E. (2016) Going beyond your personal learning network, using recommendations and trust through a multimedia question-answering service for decision-support: A case study in the healthcare. Journal of Universal Computer Science (JUCS). ISSN 0948-695X. ( .pdf)
  8. Kowald, D., Kopeinik, S., Seitlinger, P., Ley, T., Albert, D., & Trattner, C. (2015). Refining Frequency-Based Tag Reuse Predictions by Means of Time and Semantic Context. In Mining, Modeling, and Recommending'Things' in Social Media (pp. 55-74). Springer International Publishing. ( .pdf)
  9. Kowald, D., Seitlinger, P., Kopeinik, S., Ley, T., & Trattner, C. (2015). Forgetting the Words but Remembering the Meaning: Modeling Forgetting in a Verbal and Semantic Tag Recommender. In Mining, Modeling, and Recommending'Things' in Social Media (pp. 75-95). Springer International Publishing. ( .pdf)
  10. Lacic, E., Kowald, D., Eberhard, L., Trattner, C., Parra, D., & Marinho, L. B. (2015). Utilizing Online Social Network and Location-Based Data to Recommend Products and Categories in Online Marketplaces. In Mining, Modeling, and Recommending'Things' in Social Media (pp. 96-115). Springer International Publishing. ( .pdf)

Conference contributions

  1. Kopeinik, S., Lex, E., Kowald, D., Albert, D., & Seitlinger, P. (2019). A Real-Life School Study of Confirmation Bias and Polarisation in Information Behaviour. In Proceedings of the 14th European Conference on Technology Enhanced Learning (ECTEL'2019). Springer. (to be published)
  2. Duricic, T., Lacic, E., Kowald, D., & Lex, E. (2018). Trust-Based Collaborative Filtering: Tackling the Cold Start Problem Using Regular Equivalence. In Proceedings of the 12th ACM Conference on Recommender Systems (RecSys'2018). ACM. ( .pdf) ( poster)
  3. Kowald, D., Seitlinger, P., Ley, T., & Lex, E. (2018). The Impact of Semantic Context Cues on the User Acceptance of Tag Recommendations: An Online Study. In Companion Proceedings of the 27th International World Wide Web Conference (WWW'2018). ACM. ( .pdf) ( poster)
  4. D'Aquin, M., Kowald, D., Fessl, A., Lex, E., & Thalmann, S. (2018). AFEL - Analytics for Everyday Learning. In Proceedings of the International Projects Track co-located with the 27th International World Wide Web Conference (WWW'2018). ACM. ( .pdf)
  5. Kowald, D., Kopeinik, S., & Lex, E. (2017). The TagRec Framework as a Toolkit for the Development of Tag-Based Recommender Systems. In Adjunct Publication of the 25th Conference on User Modeling, Adapation and Personalization (UMAP'2017). ACM. ( .pdf) ( poster)
  6. Kowald, D., Pujari, S., & Lex, E. (2017). Temporal Effects on Hashtag Reuse in Twitter: A Cognitive-Inspired Hashtag Recommendation Approach. In Proceedings of the 26th International World Wide Web Conference (WWW'2017). ACM. ( .pdf)
  7. Kopeinik, S., Kowald, D., & Lex, E. (2016). Which Algorithms Suit Which Learning Environments? A Comparative Study of Recommender Systems in TEL. In Proceedings of the 11th European Conference on Technology Enhanced Learning (EC-TEL'2016). Springer. ( .pdf)
  8. Kowald, D., & Lex, E. (2016). The Influence of Frequency, Recency and Semantic Context on the Reuse of Tags in Social Tagging Systems. In Proceedings of the 27th International Conference on Hypertext and Social Media (HT'2016). ACM. ( .pdf)
  9. Lacic, E., Kowald, D., & Lex, E. (2016). High Enough? Explaining and Predicting Traveler Satisfaction in Airline Reviews. In Proceedings of the 27th International Conference on Hypertext and Social Media (HT'2016). ACM. ( .pdf)
  10. Kowald, D., & Lex, E. (2015). Evaluating Tag Recommender Algorithms in Real-World Folksonomies: A Comparative Study. In Proceedings of the 9th ACM Conference on Recommender Systems (RecSys'2015). ACM. ( .pdf) ( poster)
  11. Seitlinger, P., Kowald, D., Kopeinik, S., Hasani-Mavriqi, I., Ley, T., & Lex, E. (2015). Attention Please! A Hybrid Resource Recommender Mimicking Attention-Interpretation Dynamics. In Proceedings of the companion publication of the 24th international conference on World wide web companion (WWW'2015). International World Wide Web Conferences Steering Committee. ( .pdf)
  12. Kowald, D. (2015). Modeling Cognitive Processes in Social Tagging to Improve Tag Recommendations. In Proceedings of the 24th International Conference on World Wide Web Companion (WWW'2015), pp. 505-509. International World Wide Web Conferences Steering Committee. (PhD Symposium) ( .pdf)
  13. Lacic, E., Kowald, D., Traub, M., Luzhnica, G., Simon, J., & Lex, E. (2015). Tackling Cold-Start Users in Recommender Systems with Indoor Positioning Systems. In Proceedings of the 9th ACM Conference on Recommender Systems (RecSys'2015). CEUR-WS. ( .pdf) ( poster)
  14. Traub, M., Kowald, D., Lacic, E., Schoen, P., Supp, G., & Lex, E. (2015). Smart booking without looking: providing hotel recommendations in the TripRebel portal. In Proceedings of the 15th International Conference on Knowledge Technologies and Data-driven Business (i-Know'2015). ACM. (best demo honourable mention). ( .pdf) ( poster)
  15. Dennerlein, S., Kowald, D., Lex, E., Theiler, D., Lacic, E., & Ley, T. (2015). The Social Semantic Server: A Flexible Framework to Support Informal Learning at the Workplace. In Proceedings of the 15th International Conference on Knowledge Technologies and Data-driven Business(i-Know'2015). ACM. ( .pdf)
  16. Kowald, D., Seitlinger, P., Trattner, C., & Ley, T. (2014). Long Time no See: The Probability of Reusing Tags as a Function of Frequency and Recency. In Proceedings of the companion publication of the 23rd international conference on World wide web companion (WWW'2014), pp. 463-468. International World Wide Web Conferences Steering Committee. ( .pdf)
  17. Kowald, D., Lacic, E., & Trattner, C. (2014). TagRec: towards a standardized tag recommender benchmarking framework. In Proceedings of the 25th ACM conference on Hypertext and social media (HT'2014) ,pp. 305-307). ACM. (best poster award). ( .pdf) ( poster)
  18. Lacic, E., Kowald, D., & Trattner, C. (2014). SocRecM: a scalable social recommender engine for online marketplaces. In Proceedings of the 25th ACM conference on Hypertext and social media (HT'2014), pp. 308-310. ACM. ( .pdf) ( poster)
  19. Seitlinger, P., Kowald, D., Trattner, C., & Ley, T. (2013). Recommending tags with a model of human categorization. In Proceedings of the 22nd ACM international conference on information & knowledge management (CIKM'2013), pp. 2381-2386. ACM. ( .pdf)
  20. Kowald, D., Dennerlein, S., Theiler, D., Walk, S., & Trattner, C. (2013). The Social Semantic Server - A Framework to Provide Services on Social Semantic Network Data. In Proceedings of the 9th International Conference on Semantic Systems (i-Semantics'2013). CEUR-WS. ( .pdf) ( poster)

Workshop contributions and extended abstracts

  1. Kowald, D., Lacic, E., Theiler, D., & Lex, E. (2018). AFEL-REC: A Recommender System for Providing Learning Resource Recommendations in Social Learning Environments. In Social Interaction-Based Recommender Systems (SIR'2018) Workshop co-located with Conference on Information and Knowledge Management (CIKM'2018) conference. ( .pdf)
  2. Lacic, E., Kowald, D., & Lex, E. (2018). Neighborhood Troubles: On the Value of User Pre-Filtering To Speed Up and Enhance Recommendations. In International Workshop on Entity Retrieval (EYRE'2018) Workshop co-located with Conference on Information and Knowledge Management (CIKM'2018) conference. ( .pdf)
  3. Traub, M., Gursch, H., Kowald, D., Theiler, D., Kern, R., & Lex, E. (2018). Providing Recommendations of Services, Datasets and End-Users in the Data Market Austria (DMA). International Workshop on Decision Making and Recommender Systems (DMRS'2018). ( .pdf)
  4. Fessl, A., Kowald, D., Lopez-Sola, S., Moreno, A., Maturano, R., & Thalmann, S. (2018). Analytics for Everyday Learning from Two Perspectives: Knowledge Workers and Teachers. In Analytics for Everyday Learning (AFEL'2018) Workshop co-located with European Conference on Technology Enhanced Learning (ECTEL'2018) conference. ( .pdf)
  5. Dennerlein, S., Kowald, D., Pammer-Schindler, V., Lex, E., & Ley, T. (2018). Simulation-based Co-Creation of Algorithms. In Workshop on Co-Creation in the Design, Development and Implementation of Technology-Enhanced Learning (CCTEL'2018) co-located with European Conference on Technology Enhanced Learning (ECTEL'2018) conference. ( .pdf)
  6. Lex, E., Ross-Hellauer, T., & Kowald, D. (2018). Recommender Systems as Enabling Technology to Interlink Scholarly Information. In Proceedings of the Workshop on Researcher Centric Scholarly Communication co-located with the 27th International World Wide Web Conference (WWW'2018). ( .pdf) ( link)
  7. Lacic, E., Kowald, D., Reiter-Haas, M., Slawicek, V., & Lex, E. (2018). Beyond Accuracy Optimization: On the Value of Item Embeddings for Student Job Recommendations. In Proceedings of the International Workshop on Multi-dimensional Information Fusion for User Modeling and Personalization (IFUP'2018) co-located with the 11th ACM International Conference on Web Search and Data Mining (WSDM'2018). ( .pdf)
  8. D'Aquin, M., Adamou, A., Dietze, S., Fetahu, B., Gadiraju, U., Hasani-Mavriqi, I., Holtz, P., Kimmerle, J., Kowald, D., Lex, E., Lopez.Sola, S., Maturana, R., Sabol, V., Troullinou, P., & Veas, E. (2017). AFEL: Towards Measuring Online Activities Contributions to Self-directed Learning. In Proceedings of Proceedings of the 7th Workshop on Awareness and Reflection in Technology Enhanced Learning (ARTEL) in conjunction with the 12th European Conference on Technology Enhanced Learning: Adaptive and Adaptable Learning (EC-TEL 2017) ( .pdf)
  9. Lacic, E., Kowald, D., & Lex, E. (2017). Tailoring Recommendations for a Multi-Domain Environment. Workshop on Workshop on Intelligent Recommender Systems by Knowledge Transfer & Learning (RecSysKTL'2017) co-location with the 11th ACM Conference on Recommender Systems (RecSys'2017). ( .pdf)
  10. Traub, M., Lacic, E., Kowald, D., Kahr, M., & Lex, E. (2016). Need Help? Recommending Social Institutions. Workshop on Recommender Systems and Big Data Analytics (RSBDA'2016) co-location with i-KNOW'2016. ( .pdf)
  11. Lacic, E., Traub, M., Kowald, D., & Lex, E. (2015). ScaR: Towards a Real-Time Recommender Framework Following the Microservices Architecture. Workshop on Large Scale Recommender Systems (LSRS'2015) co-located with the 9th ACM Conference on Recommender Systems (RecSys'2015). ( .pdf)
  12. Kowald, D., Lacic, E., Seitlinger, P., Trattner, C. & Parra, D. (2014). Recommending Items in Social Tagging Systems Using Tag and Time Information, In Proceedings of the 1st International Workshop on Social Personalisation (SP'2014) co-located with the 25th ACM Conference on Hypertext and Social Media (HT'2014). CEUR-WS. ( .pdf)
  13. Lacic, E., Kowald, D., Parra, D., Kahr, M., & Trattner, C. (2014). Towards a scalable social recommender engine for online marketplaces: The case of apache solr. In Proceedings of the companion publication of the 23rd international conference on World wide web companion (WWW'2014), pp. 817-822. Workshop on Social Recommender Systems: SRS'2014. ( .pdf)

Extended abstracts

  1. Lex, E., & Kowald, D. (2019). The Impact of Time on Hashtag Reuse in Twitter: A Cognitive-Inspired Hashtag Recommendation Approach. In Proceedings of The 49th GI Annual Conference (INFORMATIK'2019). ( .pdf)
  2. Kowald, D., Lex, E., & Schedl, M. (2019). Modeling Artist Preferences of Users with Different Music Consumption Patterns for Fair Music Recommendations. European Symposium on Computational Social Science (ESCSS'2019). (to be published)
  3. Duricic, T., Lacic, E., & Kowald, D. & Lex, E. (2019). Exploiting weak ties in trust-based recommender systems using regular equivalence. European Symposium on Computational Social Science (ESCSS'2019). ( .pdf)
  4. Kowald, D., & Lex, E. (2018). Studying Confirmation Bias in Hashtag Usage on Twitter. European Symposium on Computational Social Science (ESCSS'2018). ( .pdf) ( poster)
  5. Lex, E., Wagner, M., & Kowald, D. (2018). Mitigating Confirmation Bias on Twitter by Recommending Opposing Views. European Symposium on Computational Social Science (ESCSS'2018). ( .pdf) ( poster)
  6. Kowald, D. (2017). Modeling Activation Processes in Human Memory to Improve Tag Recommendations. SIGIR Forum December 2017, Volume 51, Number 3 (dissertation abstract). ACM. ( .pdf)
  7. Kowald, D., & Lex, E. (2017). Overcoming the Imbalance Between Tag Recommendation Approaches and Real-World Folksonomy Structures with Cognitive-Inspired Algorithms. European Symposium on Computational Social Science (ESCSS'2017). ( .pdf) ( poster)
  8. Trattner, C., Kowald, D., & Lacic, E. (2015). TagRec: Towards a Toolkit for Reproducible Evaluation and Development of Tag-Based Recommender Algorithms. SIGWEB Newsletter. Winter 2015. ( .pdf)
  9. Kowald, D., Seitlinger, P., Ley, T., & Lex, E. (2015). Modeling Activation Processes in Human Memory to Improve Tag Recommendations. 2nd GESIS Computational Social Sciences Winter Symposium (CSSWS’2015). ( .pdf) ( poster)

Proceedings as editor

  1. Alexander Felfernig, Ralf Klamma, Tobias Ley, Dominik Kowald, Elisabeth Lex, & Viktoria Pammer-Schindler (2017). Focused topic on "Recommender systems and social network analysis" in Journal of Universal Computer Science (JUCS). Volume 23. Issue 9. ( link)
  2. Mario Aehnelt, Olivia Bluder, Gert Breitfuss, Rene Kaiser, Roman Kern, Ralf Klamma, Dominik Kowald, Tobias Ley, Elisabeth Lex, Christiana Müller, Viktoria Pammer-Schindler, Romana Rauter, Gerald Reiner, & Eduardo Veas (2017). Proceedings of the Workshop Papers of i-Know 2017, Graz, Austria, October 11-12, 2017. ( link)

Theses

  • Kowald, D. (2017). Modeling Activation Processes in Human Memory to Improve Tag Recommendations. PhD thesis. ( .pdf)
  • Kowald, D. (2012). Combining Computer-Supported, Collaborative Learning with E-Assessment: Enhancing a Wiki System with Flexible Assessment Methods. Master thesis. ( .pdf)
  • Kowald, D., & Maderer, J. (2009). Peer Assessment in Computer Science and Modern Technologies to Build a Flexible E-Learning System around it. Bachelor thesis. ( .pdf)


Services

Organization and chairing

  • CIKM'2018, Recommendation track of the ACM Conference on Information and Knowledge Management, Turin, Italy, 2018 ( link)
  • RSBDA'2017, Second Workshop on Recommender Systems and Big Data Analytics co-located with i-KNOW 2017, Graz, Austria, 2017. ( link)
  • RSBDA'2016, First Workshop on Recommender Systems and Big Data Analytics co-located with i-KNOW 2016, Graz, Austria, 2016. ( link)
  • i-Know'2015, Social Computing track of the 15th International Conference on Knowledge Technologies and Data-Driven Business, Graz, Austria, 2015 ( link)
  • i-Know'2013, Science 2.0 track of the 13th International Conference on Knowledge Technologies and Data-Driven Business, Graz, Austria, 2013 ( link)

Programm committee membership and reviewing

  • TWEB, ACM Transactions on the Web, 2019 ( link)
  • HT'2019, 30th ACM Conference on Hypertext and Social Media, 2019 ( link)
  • WebSci'2019, 11th ACM Conference on Web Science, 2019 ( link)
  • ESCSS'2019, Third European Symposium on Computational Social Science in Zurich, Switzerland ( link)
  • TCSC, IEEE Transactions on Computational Social Systems, 2019 ( link)
  • ASC, Applied Soft Computing, 2019 ( link)
  • MSM'2019, 10th International Workshop on Modeling Social Media - Mining, Modeling and Learning from Social Media co-located with WWW’2019 conference, San Francisco, USA, 2019 ( link)
  • PlosOne, PlosOne Journal, 2018 ( link)
  • Journal of Systems and Software, Elsevier, 2018 ( link)
  • TKDE, IEEE Transactions of Knowledge and Data Management, 2018 ( link)
  • RecSys'2018, 12th ACM Conference on Recommender Systems (poster track), Vancouver, Canada, 2018 ( link)
  • UMAP'2018, 26th Conference on User Modeling, Adaptation and Personalization, Singapore, Singapore, 2018 ( link)
  • SoAPS'2018, Workshop on Social Aspects in Personalization and Search co-located with ECIR'2018 conference, Grenoble, France, 2018 ( link)
  • AFEL'2018, Analytics for Everyday Learning Workshop co-located with ECTEL'2018 conference, Leeds, UK, 2018 ( link)
  • SNAM Journal, Social Network Analysis and Mining, 2018 ( link)
  • INRT Journal, Information Retrieval Journal, 2018 ( link)
  • AJSE, Arabian Journal for Science and Engineering, 2018 ( link)
  • TLT Journal, Transactions on Learning Technologies, 2017 ( link)
  • SNAMS'2017, The Fourth International Symposium on Social Networks Analysis, Management and Security, Prague, Czech Rebublic ( link)
  • WebSci'2017, 9th International ACM Web Science Conference (poster track), Troy, New York, 2017 ( link)
  • OpenSym'2017, 13th International Symposium on Open Collaboration, Galway, Ireland, 2017 ( link)
  • SNAM Journal, Social Network Analysis and Mining, 2017 ( link)
  • Computers & Education Journal, 2017 ( link)
  • MSM'2015, 6th International Workshop on Modeling Social Media - Behavioral Analytics in Social Media, Big Data and the Web co-located with WWW’2015 conference, Florence, Italy, 2015 ( link)
  • UMAP'2014, 22nd Conference on User Modelling, Adaption and Personalization, Aalborg, Denmark, 2014 ( link)
  • EC-TEL'2014, 9th European Conference on Technology Enhanced Learning, Graz, Austria, 2014 ( link)

Talks and presentations

  • ESCSS'2018, Pecha Kucha and poster sessions of the Second European Symposium on Computational Social Science in Cologne, Germany (with travel grant). ( slides) ( poster)
  • CIKM'2018, Social Interaction-Based Recommender Systems Workshop co-located with CIKM'2018 in Turin, Italy. ( slides)
  • WWW'2018, Poster session of the 27th International World Wide Web Conference in Lyon, France. ( poster)
  • ESCSS'2017, Algorithms and poster sessions of the First European Symposium on Computational Social Science in London, Great Britain. ( slides) ( poster)
  • UMAP'2017, Late-Breaking-Results poster session of the 25th Conference on User Modeling, Adaption and Personalization in Bratislava, Slovakia. ( poster)
  • WWW'2017, Data Mining session of the 26th International World Wide Web Conference in Perth, Australia. ( slides)
  • HT'2016, Social Media Analytics session of the 27th ACM Conference on Hypertext and Social Media in Halifax, Canada (with travel grant). ( slides)
  • CSSWS'2015, Pecha Kucha and poster session of the 2nd Computational Social Sciences Winter Symposium, Cologne, Germany. ( poster)
  • RecSys’2015, Short Paper slam and poster session of the 9th ACM Conference on Recommender Systems, Vienna, Austria. ( poster)
  • WWW'2015, PhD Symposium of the 24th International World Wide Web Conference, Florence, Italy. ( slides)
  • i-Know'2015, Demo session of 15th Int. Conference on Knowledge Technologies, Graz, Austria. ( poster)
  • WWW'2014, WebScience track of the 23rd International World Wide Web Conference, Seoul, Korea. ( slides)
  • SRS'2014, Workshop on Social Recommender Systems @ WWW’2014 conference, Seoul, Korea. ( slides)
  • i-Semantics’2013, Poster session of the 9th Int. Conference on Semantic Systems, Graz, Austria. ( poster)

Awards

  • Nominated for ACM SIGCHI Outstanding Dissertation award by Institute of Interactive Systems and Data Science of Graz University of Technology (2018). ( link)
  • Nominated for Award of Excellence by Faculty of Informatics of Graz University of Technology for dissertation. ( link)
  • Dissertation Award by Arbeiterkammer Steiermark, Austria. ( link)
  • Nominated for Heinz Zemanek Award by Faculty of Informatics of Graz University of Technology for dissertation. ( link)
  • Best Demo Honourable Mention at the 15th International Conference on Knowledge Technologies and Data-Driven Business (i-Know’2015) in Graz, Austria. ( link)
  • Best Poster Award at the 25th ACM Conference on Hypertext and Social Media (HT’2014) in Santiago, Chile. ( link)

Grants

  • Project Grant for TRIPLE, H2020 (2019 - 2022), 377k for the Know-Center as co-writer. (to be published)
  • Travel Grant for the European Symposium on Computational Social Science (ESCSS'2019) in Zurich, Switzerland. ( link)
  • FFG – K1 Research Center Grant, 20,4M for second funding period (2019 - 2022) of the Know-Center GmbH as co-writer ( link)
  • Project Grant for AI4EU, H2020 (2019 - 2021), 147k for the Know-Center as co-writer. ( link)
  • Travel Grant for the European Symposium on Computational Social Science (ESCSS'2018) in Cologne, Germany. ( link)
  • Submitted FWF YIRG grant Young Independent Researcher Group, passed first stage for 2M Postdoc programme (2018). ( link)
  • Project Grant for OpenAIRE Matchmaker: An innovative recommendation service for finding new scientific collaborators, OpenAIRE Open Tender Calls LOT II Value-added services (2018), 15k for the Know-Center as co-writer. ( link)
  • Project Grant for Health-Literacy und Diversity fuer SchuelerInnen der Sekundaerstufe I (HeLi-D), Gesundheitsfonds Steiermark (2018 - 2020), 75k for the Know-Center as co-writer. ( link)
  • Travel Grant for the 27th ACM Conference on Hypertext and Social Media (HT'2016) in Halifax, Canada. ( link)
  • Project Grant for Data Market Austria (DMA), IKT der Zukunft (2015 - 2019), 286k for the Know-Center as co-writer. ( link)

Co-supervised theses

  • Muellner, P. (2019). Fair Music Recommendations. Master thesis. Graz University of Technology. (to be published)
  • Wagner, M. (2019). Diversity-Aware Recommendation of Tweets. Master thesis. Graz University of Technology. (to be published)
  • Punz, A. (2016). Detection and Analysis of Communities on Twitter. Bachelor thesis. Graz University of Technology. ( .pdf)

Software projects

  • TagRec, Towards A Standardized Tag Recommender Benchmarking Framework. ( link)
  • ScaR, Scalable Recommendation-as-a-Service. ( link)
  • SNA, Computational Social Networks and Demand Forecasting. ( link)
  • Layers, The Learning Layers Technical Infrastructure. ( link)
  • Matchmaker, Spark scientific collaboration. ( link)


Contact

dkowald [AT] know [MINUS] center [DOT] at / dominik.kowald [AT] gmail [DOT] com

+43 (316) 873-30846

dkowald1

Dominik Kowald

Dominik Kowald, Know-Center GmbH, Inffeldgasse 13/6, 8010 Graz, Austria