Media convergence works by processing information from different modalities and applying them to different *** is difficult for the conventional knowledgegraph to utilise multi-media features because the introduction...
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Media convergence works by processing information from different modalities and applying them to different *** is difficult for the conventional knowledgegraph to utilise multi-media features because the introduction of a large amount of information from other modalities reduces the effectiveness of representation learning and makes knowledgegraphinference less *** address the issue,an inference method based on Media Convergence and Rule-guided Joint inference model(MCRJI)has been *** authors not only converge multi-media features of entities but also introduce logic rules to improve the accuracy and interpretability of link ***,a multi-headed self-attention approach is used to obtain the attention of different media features of entities during semantic ***,logic rules of different lengths are mined from knowledgegraph to learn new entity ***,knowledgegraphinference is performed based on representing entities that converge multi-media *** experimental results show that MCRJI outperforms other advanced baselines in using multi-media features and knowledgegraphinference,demonstrating that MCRJI provides an excellent approach for knowledgegraphinference with converged multi-media features.
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