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  • Open Access

    ARTICLE

    Data-Driven Probabilistic System for Batsman Performance Prediction in a Cricket Match

    Fawad Nasim1,2,*, Muhammad Adnan Yousaf1, Sohail Masood1,2, Arfan Jaffar1,2, Muhammad Rashid3

    Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2865-2877, 2023, DOI:10.32604/iasc.2023.034258 - 15 March 2023

    Abstract Batsmen are the backbone of any cricket team and their selection is very critical to the team’s success. A good batsman not only scores run but also provides stability to the team’s innings. The most important factor in selecting a batsman is their ability to score runs. It is a generally accepted notion that the future performance of a batsman can be predicted by observing and analyzing their past record. This hypothesis is based on the fact that a player’s batting average is generally considered to be a good indicator of their future performance. We… More >

  • Open Access

    ARTICLE

    Recommendation Algorithm Based on Probabilistic Matrix Factorization with Adaboost

    Hongtao Bai1, 2, Xuan Li1, 2, Lili He1, 2, Longhai Jin1, 2, Chong Wang1, 2, 3, Yu Jiang1, 2, *

    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1591-1603, 2020, DOI:10.32604/cmc.2020.09981 - 20 August 2020

    Abstract A current problem in diet recommendation systems is the matching of food preferences with nutritional requirements, taking into account individual characteristics, such as body weight with individual health conditions, such as diabetes. Current dietary recommendations employ association rules, content-based collaborative filtering, and constraint-based methods, which have several limitations. These limitations are due to the existence of a special user group and an imbalance of non-simple attributes. Making use of traditional dietary recommendation algorithm researches, we combine the Adaboost classifier with probabilistic matrix factorization. We present a personalized diet recommendation algorithm by taking advantage of probabilistic… More >

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