URL: https://proceedings.neurips.cc/paper_files/paper/2017/file/5dd9db5e033da9c6fb5ba83c7a7ebea9-Paper.pdf
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/Subject (Neural Information Processing Systems http\072\057\057nips\056cc\057)
/Publisher (Curran Associates\054 Inc\056)
/Language (en\055US)
/Created (2017)
/EventType (Poster)
/Description-Abstract (Low\055dimensional embeddings of nodes in large graphs have proved extremely useful in a variety of prediction tasks\054 from content recommendation to identifying protein functions\056 However\054 most existing approaches require that all nodes in the graph are present during training of the embeddings\073 these previous approaches are inherently transductive and do not naturally generalize to unseen nodes\056 Here we present GraphSAGE\054 a general\054 inductive framework that leverages node feature information \050e\056g\056\054 text attributes\051 to efficiently generate node embeddings\056 Instead of training individual embeddings for each node\054 we learn a function that generates embeddings by sampling and aggregating features from a node\047s local neighborhood\056 Our algorithm outperforms strong baselines on three inductive node\055classification benchmarks\072 we classify the category of unseen nodes in evolving information graphs based on citation and Reddit post data\054 and we show that our algorithm generalizes to completely unseen graphs using a multi\055graph dataset of protein\055protein interactions\056)
/Producer (PyPDF2)
/Title (Inductive Representation Learning on Large Graphs)
/Date (2017)
/ModDate (D\07220180213013748\05508\04700\047)
/Published (2017)
/Type (Conference Proceedings)
/firstpage (1024)
/Book (Advances in Neural Information Processing Systems 30)
/Description (Paper accepted and presented at the Neural Information Processing Systems Conference \050http\072\057\057nips\056cc\057\051)
/Editors (I\056 Guyon and U\056V\056 Luxburg and S\056 Bengio and H\056 Wallach and R\056 Fergus and S\056 Vishwanathan and R\056 Garnett)
/Author (Will Hamilton\054 Zhitao Ying\054 Jure Leskovec)
/lastpage (1034)
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