2023S

• Innovation / 188.915 / VU
• Recommender Systems / 194.035 / VU

• DigHumHub
  2020 – 2021 / MA 7 der Stadt Wien

Note: Due to the rollout of TU Wien’s new publication database, the list below may be slightly outdated. Once the migration is complete, everything will be up to date again.

• Introducing Neural Bag of Whole-Words with ColBERTer: Contextualized Late Interactions using Enhanced Reduction / Hofstätter, S., Khattab, O., Althammer, S., Sertkan, M., & Hanbury, A. (2022). Introducing Neural Bag of Whole-Words with ColBERTer: Contextualized Late Interactions using Enhanced Reduction. In CIKM ’22: Proceedings of the 31st ACM International Conference on Information & Knowledge Management (pp. 737–747). Association for Computing Machinery (ACM). https://doi.org/10.1145/3511808.3557367 / Project: DoSSIER
• The Role of Bias in News Recommendation in the Perception of the Covid-19 Pandemic / Kolb, T. E., Nalis, I., Sertkan, M., & Neidhardt, J. (2022). The Role of Bias in News Recommendation in the Perception of the Covid-19 Pandemic. In Kolb Thomas (Ed.), Unofficial Proceedings of the 5th FAccTRec Workshop on Responsible Recommendation at RecSys 2022. https://doi.org/10.48550/ARXIV.2209.07608 / Project: CDL-RecSys
• Exploring Expressed Emotions for Neural News Recommendation / Sertkan, M., & Neidhardt, J. (2022). Exploring Expressed Emotions for Neural News Recommendation. In UMAP ’22 Adjunct: Adjunct Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization (pp. 22–28). Association for Computing Machinery. https://doi.org/10.1145/3511047.3536414 / Project: CDL-RecSys
• Towards an Approach for Analyzing Dynamic Aspects of Bias and Beyond-Accuracy Measures / Neidhardt, J., & Sertkan, M. (2022). Towards an Approach for Analyzing Dynamic Aspects of Bias and Beyond-Accuracy Measures. In L. Boratto, S. Faralli, M. Marras, & giovanni stilo (Eds.), Advances in Bias and Fairness in Information Retrieval (pp. 35–42). Springer Cham. https://doi.org/10.1007/978-3-031-09316-6_4 / Project: CDL-RecSys
• A Comparative Study of Data-Driven Models for Travel Destination Characterization / Dietz, L. W., Sertkan, M., Myftija, S., Thimbiri Palage, S., Neidhardt, J., & Wörndl, W. (2022). A Comparative Study of Data-Driven Models for Travel Destination Characterization. Frontiers in Big Data, 5, Article 829939. https://doi.org/10.3389/fdata.2022.829939 / Project: CDL-RecSys
• PARM: A Paragraph Aggregation Retrieval Model for Dense Document-to-Document Retrieval / Althammer, S., Hofstätter, S., Sertkan, M., Verberne, S., & Hanbury, A. (2022). PARM: A Paragraph Aggregation Retrieval Model for Dense Document-to-Document Retrieval. In Advances in Information Retrieval (pp. 19–34). Springer. https://doi.org/10.1007/978-3-030-99736-6_2
• PixMeAway 2 / Sertkan, M. (2021). PixMeAway 2. ENTER2021 - The 28th annual eTourism Conference, online, International. http://hdl.handle.net/20.500.12708/87298
• Modeling Users and Items for Recommenders:There Is More than Semantics / Sertkan, M. (2021). Modeling Users and Items for Recommenders:There Is More than Semantics. In Fifteenth ACM Conference on Recommender Systems. RecSys 2021: 15th ACM Conference on Recommender Systems, Amsterdam, Netherlands, EU. ACM. https://doi.org/10.1145/3460231.3473898
• Improving Efficient Neural Ranking Models with Cross-Architecture Knowledge Distillation / Hofstätter, S., Althammer, S., Schröder, M., Sertkan, M., & Hanbury, A. (2020). Improving Efficient Neural Ranking Models with Cross-Architecture Knowledge Distillation (p. 8). arXiv. http://hdl.handle.net/20.500.12708/141680
• PicTouRe - A Picture-Based Tourism Recommender / Sertkan, M., Neidhardt, J., & Werthner, H. (2020). PicTouRe - A Picture-Based Tourism Recommender. In Fourteenth ACM Conference on Recommender Systems. RecSys 2020 - 14th ACM Conference on Recommender Systems, Rio De Janeiro, Brazil (online), Non-EU. Association for Computing Machinery, New York, United States. https://doi.org/10.1145/3383313.3411526
• DEXA: Supporting Non-Expert Annotators with Dynamic Examples from Experts / Zlabinger, M., Sabou, M., Hofstätter, S., Sertkan, M., & Hanbury, A. (2020). DEXA: Supporting Non-Expert Annotators with Dynamic Examples from Experts. In J. Huang & Y. Chang (Eds.), Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval. Association for Computing Machinery, New York, NY, United States. https://doi.org/10.1145/3397271.3401334
• Eliciting Touristic Profiles: A User Study on Picture Collections / Sertkan, M., Neidhardt, J., & Werthner, H. (2020). Eliciting Touristic Profiles: A User Study on Picture Collections. In T. Kuflik, I. Torre, R. Burke, & C. Gena (Eds.), Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization. Association for Computing Machinery, New York, NY, USA. https://doi.org/10.1145/3340631.3394868
• From Pictures to Travel Characteristics: Deep Learning-Based Profiling of Tourists and Tourism Destinations / Sertkan, M., Neidhardt, J., & Werthner, H. (2020). From Pictures to Travel Characteristics: Deep Learning-Based Profiling of Tourists and Tourism Destinations. In J. Neidhardt & W. Wörndl (Eds.), Information and Communication Technologies in Tourism 2020 (pp. 142–153). Springer. https://doi.org/10.1007/978-3-030-36737-4_12
• Fine-Grained Relevance Annotations for Multi-Task Document Ranking and Question Answering / Hofstätter, S., Zlabinger, M., Sertkan, M., Schröder, M., & Hanbury, A. (2020). Fine-Grained Relevance Annotations for Multi-Task Document Ranking and Question Answering. In Proceedings of the 29th ACM International Conference on Information & Knowledge Management. CIKM 2020: International Conference on Information & Knowledge Management 2020, Virtual Event, Ireland, EU. Association for Computing Machinery. https://doi.org/10.1145/3340531.3412878
• What is the “Personality” of a tourism destination? / Sertkan, M., Neidhardt, J., & Werthner, H. (2019). What is the “Personality” of a tourism destination? Information Technology and Tourism. https://doi.org/10.1007/s40558-018-0135-6
• Von Reisezielmerkmalen zur Reisezielpersönlichkeit / Sertkan, M., Neidhardt, J., & Werthner, H. (2019). Von Reisezielmerkmalen zur Reisezielpersönlichkeit. Tourismuswissen - Quarterly, APRIL, 91–98. http://hdl.handle.net/20.500.12708/143937
• Classifying and Mapping eTourism Datasets / Sertkan, M. (2019). Classifying and Mapping eTourism Datasets. Pre-Conference Workshop (PhD) of ENTER 2019 The 26th Annual eTourism Conference, Nicosia, Cyprus, EU. http://hdl.handle.net/20.500.12708/86979
• From Pictures to Touristic Profiles: A Deep-Learning Based Approach / Sertkan, M., Neidhardt, J., & Werthner, H. (2019). From Pictures to Touristic Profiles: A Deep-Learning Based Approach. In ProceedingsDSRS-Turing´19. (pp. 75–78). http://hdl.handle.net/20.500.12708/58129
• Documents, Topics, and Authors: Text Mining of Online News / Sertkan, M., Neidhardt, J., & Werthner, H. (2019). Documents, Topics, and Authors: Text Mining of Online News. In 2019 IEEE 21st Conference on Business Informatics (CBI). 21st IEEE International Conference on Business Informatics (CBI 2019), Moscow, Russia, Non-EU. https://doi.org/10.1109/cbi.2019.00053
• Mapping of Tourism Destinations to Travel Behavioural Patterns / Sertkan, M., Neidhardt, J., & Werthner, H. (2018). Mapping of Tourism Destinations to Travel Behavioural Patterns. In Information and Communication Technologies in Tourism 2018 (pp. 422–434). Springer, Cham. https://doi.org/10.1007/978-3-319-72923-7_32
• Pictures as a tool for matching tourist preferences with destinations. / Grossmann, W., Sertkan, M., Neidhardt, J., & Werthner, H. (2018). Pictures as a tool for matching tourist preferences with destinations. In M. Augstein, E. Herder, & W. Wörndl (Eds.), Personalized Human-Computer Interaction. (pp. 1–5). DeGruyter. http://hdl.handle.net/20.500.12708/29973