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Navid Rekabsaz
Navid Rekabsaz
Assistant Professor, Johannes Kepler University Linz (JKU)
Verified email at jku.at - Homepage
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Cited by
Cited by
Year
Volatility prediction using financial disclosures sentiments with word embedding-based IR models
N Rekabsaz, M Lupu, A Baklanov, A Hanbury, A Dür, L Anderson
arXiv preprint arXiv:1702.01978, 2017
692017
Exploration of a threshold for similarity based on uncertainty in word embedding
N Rekabsaz, M Lupu, A Hanbury
European Conference on Information Retrieval, 396-409, 2017
422017
Investigating gender fairness of recommendation algorithms in the music domain
AB Melchiorre, N Rekabsaz, E Parada-Cabaleiro, S Brandl, O Lesota, ...
Information Processing & Management 58 (5), 102666, 2021
392021
Word embedding causes topic shifting; exploit global context!
N Rekabsaz, M Lupu, A Hanbury, H Zamani
Proceedings of the 40th International ACM SIGIR Conference on Research and …, 2017
342017
Do Neural Ranking Models Intensify Gender Bias?
N Rekabsaz, M Schedl
Proceedings of the 43rd International ACM SIGIR conference on research and …, 2020
332020
On the effect of low-frequency terms on neural-IR models
S Hofstätter, N Rekabsaz, C Eickhoff, A Hanbury
Proceedings of the 42nd International ACM SIGIR Conference on Research and …, 2019
322019
Generalizing translation models in the probabilistic relevance framework
N Rekabsaz, M Lupu, A Hanbury, G Zuccon
Proceedings of the 25th ACM international on conference on information and …, 2016
312016
Societal Biases in Retrieved Contents: Measurement Framework and Adversarial Mitigation of BERT Rankers
N Rekabsaz, S Kopeinik, M Schedl
Proceedings of the 44th International ACM SIGIR Conference on Research and …, 2021
242021
Measuring Societal Biases from Text Corpora with Smoothed First-Order Co-occurrence
N Rekabsaz, R West, J Henderson, A Hanbury
Proceedings of the International AAAI Conference on Web and Social Media, 2021
142021
Toward incorporation of relevant documents in word2vec
N Rekabsaz, B Mitra, M Lupu, A Hanbury
arXiv preprint arXiv:1707.06598, 2017
142017
Analyzing item popularity bias of music recommender systems: Are different genders equally affected?
O Lesota, A Melchiorre, N Rekabsaz, S Brandl, D Kowald, E Lex, ...
Fifteenth ACM Conference on Recommender Systems, 601-606, 2021
132021
Enriching word embeddings for patent retrieval with global context
S Hofstätter, N Rekabsaz, M Lupu, C Eickhoff, A Hanbury
European Conference on Information Retrieval, 810-818, 2019
132019
LFM-2b: A Dataset of Enriched Music Listening Events for Recommender Systems Research and Fairness Analysis
M Schedl, S Brandl, O Lesota, E Parada-Cabaleiro, D Penz, N Rekabsaz
ACM SIGIR Conference on Human Information Interaction and Retrieval, 337-341, 2022
122022
Not all relevance scores are equal: Efficient uncertainty and calibration modeling for deep retrieval models
D Cohen, B Mitra, O Lesota, N Rekabsaz, C Eickhoff
Proceedings of the 44th International ACM SIGIR Conference on Research and …, 2021
102021
TripClick: the log files of a large health web search engine
N Rekabsaz, O Lesota, M Schedl, J Brassey, C Eickhoff
Proceedings of the 44th International ACM SIGIR Conference on Research and …, 2021
92021
Uncertainty in neural network word embedding: Exploration of threshold for similarity
N Rekabsaz, M Lupu, A Hanbury
arXiv preprint arXiv:1606.06086, 2016
82016
On the use of statistical semantics for metadata-based social image retrieval
N Rekabsaz, R Bierig, B Ionescu, A Hanbury, M Lupu
2015 13th International workshop on content-based multimedia indexing (CBMI …, 2015
82015
CEA LIST's Participation at the MediaEval 2014 Retrieving Diverse Social Images Task.
AL Gînsca, A Popescu, N Rekabsaz
MediaEval, 2014
82014
Open government data as a service (GoDaaS): big data platform for mobile app developers
S Qanbari, N Rekabsaz, S Dustdar
2015 3rd International Conference on Future Internet of Things and Cloud …, 2015
72015
Grep-BiasIR: A Dataset for Investigating Gender Representation-Bias in Information Retrieval Results
K Krieg, E Parada-Cabaleiro, G Medicus, O Lesota, M Schedl, ...
arXiv preprint arXiv:2201.07754, 2022
62022
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