Intelligent Message Behavioral Identification System
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Abstract (arXiv)
On social media platforms, the act of predicting reposting is seen as a challenging issue related to Short Message Services (SMS). This study examines the issue of predicting picture reposting in SMS and forecasts users' behavior in sharing photographs on Twitter. Several research vary. The paper introduces a network called Image Retweet Modeling (IRM) that models heterogeneous image retransmission. It considers the user's previous reposting of the image tweet, the next contact in the SMS, and the preferences of the reposted person. Three aspects connected to content. A text-guided multimodal neural network is developed to create a novel multi-faceted attention ranking network methodology. This allows for learning the joint image Twitter representation and user preference representation in the prediction job. Multiple experiments conducted on extensive data sets demonstrate that our approach outperforms current methods on Social Network platforms.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 4 of its 52 references that are in the map. First posted on arXiv 14 Apr 2024.
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References · 4
- 2014Adam: A Method for Stochastic Optimizationcited by 36,960
- 2014Going Deeper with Convolutionscited by 4,231
- 2015Effective Approaches to Attention-based Neural Machine Translationcited by 1,024
- 2017Visual Translation Embedding Network for Visual Relation Detectioncited by 112
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