In this paper, we propose a novel personalized framework to achieve recommendation by re-ranking the video search result list according to user selected one by ...
In this paper, we propose a novel personalized approach, which utilizes multimodal features, to achieve video recommendation by using neighborhood score ...
... Online video recommendation based on multimodal fusion and. relevance feedback. In Proceedings of the 6th ACM international conference on Image and video ...
Oct 30, 2023 · This article presents a comprehensive overview of the current state of video recommender systems (VRS), exploring the algorithms used, their applications, and ...
This paper presents a novel online video recommendation system based on multimodal fusion and relevance feedback, and is able to recommend videos without users' ...
Abstract—Facing with information overload, recommender system has been employed in many fields, from news, e-commerce to videos and musics.
Mar 20, 2024 · The foundation of video recommendation lies in effectively describing and representing both videos and users, ultimately shaping the performance ...
In this section we describe the proposed Hierarchical RNN (HRNN henceforth) model for personalized session-based recommendation. 3.1 Session-based Recurrent ...
Sep 20, 2019 · In this paper, we describe a DNN based ranking system de- signed for real-world recommendations and apply an extension of Mixture-of-Experts ...
Feb 15, 2021 · We propose neural graph personalized ranking (NGPR) which directly makes use of the user–item interaction information in embedding learning.
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