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Publication search results
found 30 matches
- 2023
- Nourhan Ahmed, Lars Schmidt-Thieme:
Sparse self-attention guided generative adversarial networks for time-series generation. Int. J. Data Sci. Anal. 16(4): 421-434 (2023) - Monika Di Angelo, Gernot Salzer:
Identification of token contracts on Ethereum: standard compliance and beyond. Int. J. Data Sci. Anal. 16(3): 333-352 (2023) - Andrew Barrick, Isabelle Métais, Hanane-Perrein Ettajani, Jean-Marie Marion, Amélie Châtel:
Establishing FAIR (Findable, Accessible, Interoperable and Reusable) principles for estuarine organisms exposed to engineered nanomaterials. Int. J. Data Sci. Anal. 16(4): 407-419 (2023) - Stefan Bloemheuvel, Jurgen van den Hoogen, Dario Jozinovic, Alberto Michelini, Martin Atzmueller:
Graph neural networks for multivariate time series regression with application to seismic data. Int. J. Data Sci. Anal. 16(3): 317-332 (2023) - Vadim Borisov, Klaus Broelemann, Enkelejda Kasneci, Gjergji Kasneci:
DeepTLF: robust deep neural networks for heterogeneous tabular data. Int. J. Data Sci. Anal. 16(1): 85-100 (2023) - Mitali Desai, Rupa G. Mehta, Dipti P. Rana:
ScholarRec: a scholars' recommender system that combines scholastic influence and social collaborations in academic social networks. Int. J. Data Sci. Anal. 16(2): 203-216 (2023) - Gebrekirstos G. Gebremeskel, Arjen P. de Vries:
Pull-push: a measure of over- or underpersonalization in recommendation. Int. J. Data Sci. Anal. 16(2): 255-269 (2023) - Anshul Gupta, Pravin Shrinath:
A novel recommendation system comprising WNMF with graph-based static and temporal similarity estimators. Int. J. Data Sci. Anal. 16(1): 27-41 (2023) - Mohanned Abduljabbar Hael:
Unbiased recursive decision tree for supervised functional data classification with applying on electrocardiogram signals. Int. J. Data Sci. Anal. 16(4): 441-454 (2023) - Sajad Fathi Hafshejani, Zahra Moaberfard:
Initialization for non-negative matrix factorization: a comprehensive review. Int. J. Data Sci. Anal. 16(1): 119-134 (2023) - Nicolás Hernández, Alberto Muñoz, Gabriel Martos:
Density kernel depth for outlier detection in functional data. Int. J. Data Sci. Anal. 16(4): 481-488 (2023) - Minsung Hong, Namho Chung, Chulmo Koo, Sun-Young Koh:
TPEDTR: temporal preference embedding-based deep tourism recommendation with card transaction data. Int. J. Data Sci. Anal. 16(2): 147-162 (2023) - Domokos M. Kelen, András A. Benczúr:
A probabilistic perspective on nearest neighbor for implicit recommendation. Int. J. Data Sci. Anal. 16(2): 217-235 (2023) - Andrei V. Konstantinov, Lev V. Utkin:
Attention-like feature explanation for tabular data. Int. J. Data Sci. Anal. 16(1): 1-26 (2023) - Chaima Laroussi, Raouia Ayachi:
A deep meta-level spatio-categorical POI recommender system. Int. J. Data Sci. Anal. 16(2): 285-299 (2023) - Carson K. Leung, Gabriella Pasi, Li Wang:
Theoretical and practical data science and analytics: challenges and solutions. Int. J. Data Sci. Anal. 16(4): 403-406 (2023) - Anton Lysenko, Egor Shikov, Klavdiya Bochenina:
Combination of individual and group patterns for time-sensitive purchase recommendation. Int. J. Data Sci. Anal. 16(2): 163-172 (2023) - Tri Minh Nguyen, Thin Nguyen, Truyen Tran:
Learning to discover medicines. Int. J. Data Sci. Anal. 16(3): 301-316 (2023) - Kavita Sahu, R. K. Srivastava, Sarvesh Kumar, Manish Saxena, Bineet Kumar Gupta, Ravi Prakash Verma:
Integrated hesitant fuzzy-based decision-making framework for evaluating sustainable and renewable energy. Int. J. Data Sci. Anal. 16(3): 371-390 (2023) - Dayne Sorvisto:
Applications of the discrete-time Fourier transform to data analysis. Int. J. Data Sci. Anal. 16(4): 435-440 (2023) - Guillaume Staerman, Eric Adjakossa, Pavlo Mozharovskyi, Vera Hofer, Jayant Sen Gupta, Stéphan Clémençon:
Functional anomaly detection: a benchmark study. Int. J. Data Sci. Anal. 16(1): 101-117 (2023) - Michael Sun, Andrew Wang:
Privacy preserving cold-start recommendation for out-of-matrix users via content baskets. Int. J. Data Sci. Anal. 16(2): 237-253 (2023) - Iraklis Varlamis, Christos Sardianos, Christos Chronis, George J. Dimitrakopoulos, Yassine Himeur, Abdullah Alsalemi, Faycal Bensaali, Abbes Amira:
Using big data and federated learning for generating energy efficiency recommendations. Int. J. Data Sci. Anal. 16(3): 353-369 (2023) - Tongyuan Wang:
The pattern frequency distribution theory: a mathematic establishment toward rational and reliable pattern mining. Int. J. Data Sci. Anal. 16(1): 43-83 (2023) - Xin Wang, Serdar Kadioglu:
Modeling uncertainty to improve personalized recommendations via Bayesian deep learning. Int. J. Data Sci. Anal. 16(2): 191-201 (2023) - Shoujin Wang, Yan Wang, Fikret Sivrikaya, Sahin Albayrak, Vito Walter Anelli:
Data science for next-generation recommender systems. Int. J. Data Sci. Anal. 16(2): 135-145 (2023) - Jing Yuan, Christian Geißler, Weijia Shao, Andreas Lommatzsch, Brijnesh J. Jain:
When algorithm selection meets Bi-linear Learning to Rank: accuracy and inference time trade off with candidates expansion. Int. J. Data Sci. Anal. 16(2): 173-189 (2023) - Alejandro Gabriel Villanueva Zacarias, Peter Reimann, Christian Weber, Bernhard Mitschang:
AssistML: an approach to manage, recommend and reuse ML solutions. Int. J. Data Sci. Anal. 16(4): 455-479 (2023) - Yu-Xuan Zhang, Mei Yang, Zhengchun Zhou, Fan Min:
Multi-instance embedding learning with deconfounded instance-level prediction. Int. J. Data Sci. Anal. 16(3): 391-401 (2023) - Donglin Zhou, Zhihong Zhang, Yangxin Zheng, Zhenting Zou, Lin Zheng:
Attenuated sentiment-aware sequential recommendation. Int. J. Data Sci. Anal. 16(2): 271-283 (2023)
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