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62 ta ish

Ish: Modeling and Applying Implicit Dormant Features for Recommendation via Clustering and Deep Factorization

  1. An Improvement of the Fire Detection and Classification Method Using YOLOv3 for Surveillance Systems

    Akmalbek Abdusalomov, Nodirbek Baratov, Alpamis Kutlimuratov +1

    MaqolaFire Detection and Safety SystemsSensors202118 iqtibos
    ABI

  2. Improved Real-Time Fire Warning System Based on Advanced Technologies for Visually Impaired People

    Akmalbek Abdusalomov, Mukhriddin Mukhiddinov, Alpamis Kutlimuratov +1

    Maqola202218 iqtibos
    ABI

  3. Evolving Hierarchical and Tag Information via the Deeply Enhanced Weighted Non-Negative Matrix Factorization of Rating Predictions

    Alpamis Kutlimuratov, Akmalbek Abdusalomov, Taeg Keun Whangbo

    Maqola202010 iqtibos
    ABI

  4. Matrix Factorization Techniques for Recommender Systems

    Yehuda Koren, Robert Bell, Chris Volinsky

    Maqola20097 iqtibos
    ABI

  5. Deep-Sequence–Aware Candidate Generation for e-Learning System

    Aziz Ilyosov, Alpamis Kutlimuratov, Taeg Keun Whangbo

    Maqola20216 iqtibos
    ABI

  6. Recommender Systems Handbook

    Francesco Ricci⋆

    Kitob20102 iqtibos
    ABI

  7. A collaborative filtering recommendation algorithm based on information theory and bi-clustering

    Mingyang Jiang, Zhifeng Zhang, Jingqing Jiang +2

    Maqola20192 iqtibos
    ABI

  8. Design and Analysis of a Cluster-Based Intelligent Hybrid Recommendation System for E-Learning Applications

    S. Bhaskaran, Raja Marappan, Balachandran Santhi

    Maqola20212 iqtibos
    ABI

  9. Recommender systems survey

    Jesús Bobadilla, Fernando Ortega, Antonio Hernando +1

    Maqola20132 iqtibos
    ABI

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