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From the last few decades Recommender System has tremendous rise in many of the webservices. Now -a-days most of              the people uses e-commerce sites or online advertisements and the famous websites like Netflix, You-tube makes use of recommendation systems. It is a field of increasing importance with intense potential. Recommender System are created              to solve the immense issues of the customer to make a best and easiest decision by analysing information  and  provides              the more relevant and personalized information according to the user’s choice.Most of the recommend system works by considering the feedback from the customers or content of items. Multimodal machine learning aims to build model that            can process and relate the information from multiple modalities.Recommend System makes use multi- modality where we      have very different types of inputs such as image, text, speech, graph etc, which are modalities and processed by the same machine  learning  model. Our  paper  focuses  on  recommendation methods that can be used in Multimodal Recommend      System. A recommender system  compels information  filtering  system  running on machine learning (ML) algorithms that            can predict a customer’s ratings or preferences for a product.


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BHAVANTHI, S. K., V. KOMMULA, N. SURABI, S. GAJUMUGGA, and R. K. TIRUNAGARI. “MULTIMODEL RECOMMEND SYSTEM”. Technix International Journal for Engineering Research, vol. 9, no. 6, June 2022, pp. 90-94,
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