MULTIMODAL RECOMMENDATION SYSTEMS: ENHANCING RECOMMENDATION QUALITY THROUGH DATA FUSION

Qudrat Yuldashov; Alpamis Kutlimuratov

##article.authors##

Qudrat Yuldashov Muallif
Alpamis Kutlimuratov Muallif

##article.abstract##

In today's digital age, users interact with platforms using varied content types—text, images, audio, and even video. Capturing the essence of this diverse data for recommendation can yield richer user profiles and more relevant suggestions. This paper investigates the potential of Multimodal Recommendation Systems, which integrate information from multiple sources to enhance recommendation quality. We delve into methods for data fusion, the challenges of multimodal systems, and their application across different sectors.

##plugins.themes.default.displayStats.downloads##

##plugins.themes.default.displayStats.noStats##

##submission.citations##

Kutlimuratov, A.; Abdusalomov, A.; Whangbo, T.K. Evolving Hierarchical and Tag Information via the Deeply Enhanced Weighted Non-Negative Matrix Factorization of Rating Predictions. Symmetry 2020, 12, 1930.

Ilyosov, A.; Kutlimuratov, A.; Whangbo, T.-K. Deep-Sequence–Aware Candidate Generation for e-Learning System. Processes 2021, 9, 1454. https://doi.org/10.3390/pr9081454.

Safarov F, Kutlimuratov A, Abdusalomov AB, Nasimov R, Cho Y-I. Deep Learning Recommendations of E-Education Based on Clustering and Sequence. Electronics. 2023; 12(4):809. https://doi.org/10.3390/electronics12040809

Kutlimuratov, A.; Abdusalomov, A.B.; Oteniyazov, R.; Mirzakhalilov, S.; Whangbo, T.K. Modeling and Applying Implicit Dormant Features for Recommendation via Clustering and Deep Factorization. Sensors 2022, 22, 8224. https://doi.org/10.3390/s22218224.

Abdusalomov, A.; Baratov, N.; Kutlimuratov, A.; Whangbo, T.K. An Improvement of the Fire Detection and Classification Method Using YOLOv3 for Surveillance Systems. Sensors 2021, 21, 6519. https://doi.org/10.3390/s21196519.

Abdusalomov, A.B.; Mukhiddinov, M.; Kutlimuratov, A.; Whangbo, T.K. Improved Real-Time Fire Warning System Based on Advanced Technologies for Visually Impaired People. Sensors 2022, 22, 7305. https://doi.org/10.3390/s22197305.

Mamieva, D.; Abdusalomov, A.B.; Kutlimuratov, A.; Muminov, B.; Whangbo, T.K. Multimodal Emotion Detection via Attention-Based Fusion of Extracted Facial and Speech Features. Sensors 2023, 23, 5475. https://doi.org/10.3390/s23125475

Makhmudov, F.; Kutlimuratov, A.; Akhmedov, F.; Abdallah, M.S.; Cho, Y.-I. Modeling Speech Emotion Recognition via Attention-Oriented Parallel CNN Encoders. Electronics 2022, 11, 4047. ttps://doi.org/10.3390/electronics1123404

Alpamis Kutlimuratov, Elyor Gaybulloev. (2023). CHALLENGES OF SPEECH EMOTION RECOGNITION SYSTEM MODELING AND ITS SOLUTIONS. https://doi.org/10.5281/zenodo.7856088

Valentina Mamutova, Alpamis Kutlimuratov, Temur Ochilov. (2023). DEVELOPING A SPEECH EMOTION RECOGNITION SYSTEM USING CNN ENCODERS WITH ATTENTION FOCUS. https://doi.org/10.5281/zenodo.7864652

Alpamis Kutlimuratov, Nozima Atadjanova. (2023). MOVIE RECOMMENDER SYSTEM USING CONVOLUTIONAL NEURAL NETWORKS ALGORITHM. https://doi.org/10.5281/zenodo.7854603

Alpamis Kutlimuratov, Makhliyo Turaeva. (2023). MUSIC RECOMMENDER SYSTEM. https://doi.org/10.5281/zenodo.7854462