Implicit semantic-based personalized micro-videos recommendation

by   Bo Liu, et al.

With the rapid development of mobile Internet and big data, a huge amount of data is generated in the network, but the data that users are really interested in a very small portion. To extract the information that users are interested in from the huge amount of data, the information overload problem needs to be solved. In the era of mobile internet, the user's characteristics and other information should be combined in the massive amount of data to quickly and accurately recommend content to the user, as far as possible to meet the user's personalized needs. Therefore, there is an urgent need to realize high-speed and effective retrieval in tens of thousands of micro-videos. Video data content contains complex meanings, and there are intrinsic connections between video data. For multimodal information, subspace coding learning is introduced to build a coding network from public potential representations to multimodal feature information, taking into account the consistency and complementarity of information under each modality to obtain a public representation of the complete eigenvalue. An end-to-end reordering model based on deep learning and attention mechanism, called interest-related product similarity model based on multimodal data, is proposed for providing top-N recommendations. The multimodal feature learning module, interest-related network module and product similarity recommendation module together form the new model.By conducting extensive experiments on publicly accessible datasets, the results demonstrate the state-of-the-art performance of our proposed algorithm and its effectiveness.


page 1

page 2

page 3

page 4


Interest-Related Item Similarity Model Based on Multimodal Data for Top-N Recommendation

Nowadays, the recommendation systems are applied in the fields of e-comm...

Personalized Hashtag Recommendation for Micro-videos

Personalized hashtag recommendation methods aim to suggest users hashtag...

A multimedia recommendation model based on collaborative graph

As one of the main solutions to the information overload problem, recomm...

Herding Effect based Attention for Personalized Time-Sync Video Recommendation

Time-sync comment (TSC) is a new form of user-interaction review associa...

Modeling High-order Interactions across Multi-interests for Micro-video Recommendation

Personalized recommendation system has become pervasive in various video...

Predicting the Popularity of Micro-videos with Multimodal Variational Encoder-Decoder Framework

As an emerging type of user-generated content, micro-video drastically e...

Needmining: Identifying micro blog data containing customer needs

The design of new products and services starts with the identification o...

Please sign up or login with your details

Forgot password? Click here to reset