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Mete Sertkan
Mete Sertkan
PhD student, TU Wien
Verified email at tuwien.ac.at - Homepage
Title
Cited by
Cited by
Year
Improving efficient neural ranking models with cross-architecture knowledge distillation
S Hofstätter, S Althammer, M Schröder, M Sertkan, A Hanbury
arXiv preprint arXiv:2010.02666, 2020
1832020
What is the “Personality” of a tourism destination?
M Sertkan, J Neidhardt, H Werthner
Information Technology & Tourism 21 (1), 105-133, 2019
382019
The Vienna manifesto on digital humanism
H Werthner
Digital Transformation and Ethics, 338-357, 2020
292020
Introducing neural bag of whole-words with colberter: Contextualized late interactions using enhanced reduction
S Hofstätter, O Khattab, S Althammer, M Sertkan, A Hanbury
Proceedings of the 31st ACM International Conference on Information …, 2022
252022
PARM: A paragraph aggregation retrieval model for dense document-to-document retrieval
S Althammer, S Hofstätter, M Sertkan, S Verberne, A Hanbury
European Conference on Information Retrieval, 19-34, 2022
162022
From pictures to travel characteristics: deep learning-based profiling of tourists and tourism destinations
M Sertkan, J Neidhardt, H Werthner
Information and Communication Technologies in Tourism 2020: Proceedings of …, 2020
162020
Eliciting touristic profiles: A user study on picture collections
M Sertkan, J Neidhardt, H Werthner
Proceedings of the 28th ACM Conference on User Modeling, Adaptation and …, 2020
142020
Mapping of tourism destinations to travel behavioural patterns
M Sertkan, J Neidhardt, H Werthner
Information and Communication Technologies in Tourism 2018: Proceedings of …, 2018
142018
Pictoure-A picture-based tourism recommender
M Sertkan, J Neidhardt, H Werthner
Proceedings of the 14th ACM Conference on Recommender Systems, 597-599, 2020
132020
Establishing strong baselines for tripclick health retrieval
S Hofstätter, S Althammer, M Sertkan, A Hanbury
European Conference on Information Retrieval, 144-152, 2022
112022
Fine-grained relevance annotations for multi-task document ranking and question answering
S Hofstätter, M Zlabinger, M Sertkan, M Schröder, A Hanbury
Proceedings of the 29th ACM International Conference on Information …, 2020
102020
Improving efficient neural ranking models with cross-architecture knowledge distillation (2020)
S Hofstätter, S Althammer, M Schröder, M Sertkan, A Hanbury
URL https://arxiv. org/abs, 2010
72010
Pictures as a tool for matching tourist preferences with destinations
W Grossmann, M Sertkan, J Neidhardt, H Werthner
Personalized Human-Computer Interaction, 1-5, 2019
62019
Documents, topics, and authors: Text mining of online news
M Sertkan, J Neidhardt, H Werthner
2019 IEEE 21st Conference on Business Informatics (CBI) 1, 405-413, 2019
62019
From pictures to touristic profiles: A deep-learning based approach
M Sertkan, J Neidhardt, H Werthner
Proceedings of the 1st International Alan Turing Conference on Decision …, 2019
52019
A comparative study of data-driven models for travel destination characterization
LW Dietz, M Sertkan, S Myftija, S Thimbiri Palage, J Neidhardt, W Wörndl
Frontiers in big data 5, 829939, 2022
42022
Diversifying Sentiments in News Recommendation.
M Sertkan, S Althammer, S Hofstätter, J Neidhardt
Perspectives@ RecSys, 2022
32022
Towards an approach for analyzing dynamic aspects of bias and beyond-accuracy measures
J Neidhardt, M Sertkan
International Workshop on Algorithmic Bias in Search and Recommendation, 35-42, 2022
32022
Ranger: A Toolkit for Effect-Size Based Multi-Task Evaluation
M Sertkan, S Althammer, S Hofstätter
arXiv preprint arXiv:2305.15048, 2023
22023
Exploring expressed emotions for neural news recommendation
M Sertkan, J Neidhardt
Adjunct Proceedings of the 30th ACM Conference on User Modeling, Adaptation …, 2022
22022
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