知识图谱顶会论文2005-2019.rar

[{"title":"（ 81 个子文件 43.21MB ） 知识图谱顶会论文2005-2019.rar","children":[{"title":"知识图谱顶会论文2005-2019","children":[{"title":"知识表示","children":[{"title":"2015-TransG：A generative mixture model for knowledge graph embedding.pdf <span style='color:#111;'> 525.71KB </span>","children":null,"spread":false},{"title":"2019-NAACL-Text Generation from Knowledge Graphs with Graph Transforms.pdf <span style='color:#111;'> 442.91KB </span>","children":null,"spread":false},{"title":"2015-CIKM-Learning to represent knowledge graphs with gaussian embedding.pdf <span style='color:#111;'> 841.84KB </span>","children":null,"spread":false},{"title":"2016-AAAI-Knowledge graph completion with adaptive sparse transfer matrix.pdf <span style='color:#111;'> 730.19KB </span>","children":null,"spread":false},{"title":"2014-EMNLP-Knowledge graph and text jointly embedding.pdf <span style='color:#111;'> 375.69KB </span>","children":null,"spread":false},{"title":"2015-ACL-Knowledge graph embedding via dynamic mapping 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291.71KB </span>","children":null,"spread":false}],"spread":false},{"title":"事件抽取","children":[{"title":"2016-NAACL-Joint event extraction via recurrent neural networks.pdf <span style='color:#111;'> 178.03KB </span>","children":null,"spread":false},{"title":"2011-ACL-Using cross-entity inference to improve event extraction.pdf <span style='color:#111;'> 235.69KB </span>","children":null,"spread":false},{"title":"2006-ACL-The stages of event extraction.pdf <span style='color:#111;'> 54.46KB </span>","children":null,"spread":false},{"title":"2016-ACL-A language independent neural network for event detection.pdf <span style='color:#111;'> 285.48KB </span>","children":null,"spread":false},{"title":"2013-ACL-Joint event extraction via structured prediction with global features.pdf <span style='color:#111;'> 465.06KB </span>","children":null,"spread":false},{"title":"2015-ACL-vent extraction via dynamic multi-pooling convolutional neural networks.pdf <span style='color:#111;'> 458.18KB 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Neural Networks with Simple Negative Sampling.pdf <span style='color:#111;'> 265.33KB </span>","children":null,"spread":false},{"title":"2017-ACL-Joint Extraction of Entities and Relations Based on a Novel Tagging Scheme.pdf <span style='color:#111;'> 1.24MB </span>","children":null,"spread":false},{"title":"2016-ACL-Neural Relation Extraction with Selective Attention over Instance.pdf <span style='color:#111;'> 294.70KB </span>","children":null,"spread":false},{"title":"2019-WWW-Knowledge Graph Convolutional Networks for Recommender Systems.pdf <span style='color:#111;'> 912.45KB </span>","children":null,"spread":false},{"title":"2012-ACL-Reducing wrong labels in distant supervision for relation extraction.pdf <span style='color:#111;'> 381.60KB </span>","children":null,"spread":false}],"spread":false},{"title":"命名实体识别","children":[{"title":"2018-ACL-Hybrid semi-Markov CRF for Neural Sequence Labeling.pdf <span style='color:#111;'> 175.37KB 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Bi-directional LSTM-CNNs-CRF.pdf <span style='color:#111;'> 369.52KB </span>","children":null,"spread":false},{"title":"2018-AAAI-Empower Sequence Labeling with Task-Aware Neural Language Model.pdf <span style='color:#111;'> 526.12KB </span>","children":null,"spread":false},{"title":"2016-NAACL-Neural Architectures for Named Entity Recognition.pdf <span style='color:#111;'> 434.08KB </span>","children":null,"spread":false},{"title":"2017-ACL-Semi-supervised sequence tagging with bidirectional language models.pdf <span style='color:#111;'> 391.68KB </span>","children":null,"spread":false},{"title":"2016-ACL-Improving named entity recognition for chinese social media with word segmentation representation learning.pdf <span style='color:#111;'> 553.28KB </span>","children":null,"spread":false},{"title":"2018-Adversarial transfer learning for chinese named entity recognition with selfattention mechanism.pdf <span style='color:#111;'> 422.85KB 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