International Journal of Data Science and Analytics, Volume 16 (original) (raw)

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Volume 16, Number 1, June 2023

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    Andrei V. Konstantinov, Lev V. Utkin:
    Attention-like feature explanation for tabular data. 1-26
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    Anshul Gupta, Pravin Shrinath:
    A novel recommendation system comprising WNMF with graph-based static and temporal similarity estimators. 27-41
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    Tongyuan Wang:
    The pattern frequency distribution theory: a mathematic establishment toward rational and reliable pattern mining. 43-83
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    Vadim Borisov, Klaus Broelemann, Enkelejda Kasneci, Gjergji Kasneci:
    DeepTLF: robust deep neural networks for heterogeneous tabular data. 85-100
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    Guillaume Staerman, Eric Adjakossa, Pavlo Mozharovskyi, Vera Hofer, Jayant Sen Gupta, Stéphan Clémençon:
    Functional anomaly detection: a benchmark study. 101-117
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    Sajad Fathi Hafshejani, Zahra Moaberfard:
    Initialization for non-negative matrix factorization: a comprehensive review. 119-134

Volume 16, Number 2, August 2023

Special Issue: Data science for next-generation recommender systems

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    Shoujin Wang, Yan Wang, Fikret Sivrikaya, Sahin Albayrak, Vito Walter Anelli:
    Data science for next-generation recommender systems. 135-145
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    Minsung Hong, Namho Chung, Chulmo Koo, Sun-Young Koh:
    TPEDTR: temporal preference embedding-based deep tourism recommendation with card transaction data. 147-162
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    Anton Lysenko, Egor Shikov, Klavdiya Bochenina:
    Combination of individual and group patterns for time-sensitive purchase recommendation. 163-172
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    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. 173-189
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    Xin Wang, Serdar Kadioglu:
    Modeling uncertainty to improve personalized recommendations via Bayesian deep learning. 191-201
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    Mitali Desai, Rupa G. Mehta, Dipti P. Rana:
    ScholarRec: a scholars' recommender system that combines scholastic influence and social collaborations in academic social networks. 203-216
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    Domokos M. Kelen, András A. Benczúr:
    A probabilistic perspective on nearest neighbor for implicit recommendation. 217-235
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    Michael Sun, Andrew Wang:
    Privacy preserving cold-start recommendation for out-of-matrix users via content baskets. 237-253
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    Gebrekirstos G. Gebremeskel, Arjen P. de Vries:
    Pull-push: a measure of over- or underpersonalization in recommendation. 255-269
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    Donglin Zhou, Zhihong Zhang, Yangxin Zheng, Zhenting Zou, Lin Zheng:
    Attenuated sentiment-aware sequential recommendation. 271-283
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    Chaima Laroussi, Raouia Ayachi:
    A deep meta-level spatio-categorical POI recommender system. 285-299

Volume 16, Number 3, September 2023

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    Tri Minh Nguyen, Thin Nguyen, Truyen Tran:
    Learning to discover medicines. 301-316
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    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. 317-332
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    Monika Di Angelo, Gernot Salzer:
    Identification of token contracts on Ethereum: standard compliance and beyond. 333-352
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    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. 353-369
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    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. 371-390
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    Yu-Xuan Zhang, Mei Yang, Zhengchun Zhou, Fan Min:
    Multi-instance embedding learning with deconfounded instance-level prediction. 391-401

Volume 16, Number 4, October 2023

Special Issue: Theoretical and Practical Data Science and Analytics: DSAA 2022

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    Carson K. Leung, Gabriella Pasi, Li Wang:
    Theoretical and practical data science and analytics: challenges and solutions. 403-406
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    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. 407-419
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    Nourhan Ahmed, Lars Schmidt-Thieme:
    Sparse self-attention guided generative adversarial networks for time-series generation. 421-434
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    Dayne Sorvisto:
    Applications of the discrete-time Fourier transform to data analysis. 435-440
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    Mohanned Abduljabbar Hael:
    Unbiased recursive decision tree for supervised functional data classification with applying on electrocardiogram signals. 441-454
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    Alejandro Gabriel Villanueva Zacarias, Peter Reimann, Christian Weber, Bernhard Mitschang:
    AssistML: an approach to manage, recommend and reuse ML solutions. 455-479
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    Nicolás Hernández, Alberto Muñoz, Gabriel Martos:
    Density kernel depth for outlier detection in functional data. 481-488

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