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    Improved Hybrid Deep Collaborative Filtering Approach for True Recommendations

    Muhammad Ibrahim1, Imran Sarwar Bajwa1, Nadeem Sarwar2,*, Haroon Abdul Waheed3, Muhammad Zulkifl Hasan4, Muhammad Zunnurain Hussain4

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5301-5317, 2023, DOI:10.32604/cmc.2023.032856

    Abstract Recommendation services become an essential and hot research topic for researchers nowadays. Social data such as Reviews play an important role in the recommendation of the products. Improvement was achieved by deep learning approaches for capturing user and product information from a short text. However, such previously used approaches do not fairly and efficiently incorporate users’ preferences and product characteristics. The proposed novel Hybrid Deep Collaborative Filtering (HDCF) model combines deep learning capabilities and deep interaction modeling with high performance for True Recommendations. To overcome the cold start problem, the new overall rating is generated by aggregating the Deep Multivariate… More >

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