Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: For mobile photos annotation, users are more interested in the context information behind the photos. The user's social circle can provide valuable information for it. Hover, the accompanying textual information of social network is sparse and ambiguous in nature. ,  propose a personalized annotation framework for mobile photos leveraging the user's social circle. To address the unreliability problem of social network,  present an algorithm to generate reliable tags for social photos before assigning tags to the user's unlabeled photos. In the tag generation stage, a multi-modality hierarchical clustering algorithm is performed to detect social events. Besides,  use "Album" instead of individual photo as the basic unit for clustering. Finally,  employ a ighted nearest neighbor model for label propagation.  evaluate our framework on a large-scale, real-world dataset from Renren, the largest Facebook-like social network in China. Our evaluation results show promising results of our proposed framework.
['Yanhui Hong', 'Tiandi Chen', 'Kang Zhang', 'Lifeng Sun']
I am writing a research paper on a idea Personalized Annotation for Mobile Photos Based on User's Social Circle
[{"from": "human", "value": "I am writing a research paper on a idea Personalized Annotation for Mobile Photos Based on User's Social Circle"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: For mobile photos annotation, users are more interested in the context information behind the photos. The user's social circle can provide valuable information for it. Hover, the accompanying textual information of social network is sparse and ambiguous in nature. ,  propose a personalized annotation framework for mobile photos leveraging the user's social circle. To address the unreliability problem of social network,  present an algorithm to generate reliable tags for social photos before assigning tags to the user's unlabeled photos. In the tag generation stage, a multi-modality hierarchical clustering algorithm is performed to detect social events. Besides,  use \"Album\" instead of individual photo as the basic unit for clustering. Finally,  employ a ighted nearest neighbor model for label propagation.  evaluate our framework on a large-scale, real-world dataset from Renren, the largest Facebook-like social network in China. Our evaluation results show promising results of our proposed framework."}]