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Information extraction from semi-structured webpages provides valuable long-tailed facts for augmenting knowledge graph.
Freebase: a collaboratively created graph database for structuring human knowledge. In Proceedings of the 2008 ACM SIGMOD international conference on Management of data . 1247–1250
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Webtables: exploring the power of tables on the web
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Wikidata: a free collaborative knowledgebase
Denny Vrandečić and Markus Krötzsch. 2014 · 2014
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TabEL: entity linking in web tables. In International Semantic Web Conference . Springer, 425–441
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Information extraction
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DBpedia–a large-scale, multilingual knowledge base extracted from Wikipedia
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Making sense of entities and quantities in web tables. In Proceedings of the 25th ACM International on Conference on Information and Knowledge Management . 1703–1712
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A large public corpus of web tables containing time and context metadata. In Proceedings of the 25th International Conference Companion on WWW . 75–76
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Open Information Extraction Systems and Downstream Applications. In Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence (New York, New York, USA) (IJCAI’16) . AAAI Press, 4074–4077
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Profiling the potential of web tables for augmenting cross-domain knowledge bases. In Proceedings of the 25th International Conference on WWW . 251–261
Dominique Ritze, Oliver Lehmberg, Yaser Oulabi, and Christian Bizer. 2016 · 2016
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Matching web tables with knowledge base entities: from entity lookups to entity embeddings. In International Semantic Web Conference . Springer, 260–277
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Sherlock: A deep learning approach to semantic data type detection. In Proceedings of the 25th ACM SIGKDD . 1500–1508
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Openceres: When open information extraction meets the semi-structured web. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 . 3047–3056
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MTab: matching tabular data to knowledge graph using probability models
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Csv2kg: Transforming tabular data into semantic knowledge
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Entity Matching on Web Tables: a Table Embeddings approach for Blocking.. In EDBT . 510–513
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Stitching web tables for improving matching quality
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Understanding the semantic structures of tables with a hybrid deep neural network architecture. In Thirty-First AAAI Conference on Artificial Intelligence
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Attention is all you need. In Advances in neural information processing systems . 5998–6008
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Effective and efficient semantic table interpretation using tableminer+
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Ten years of webtables
Michael Cafarella, Alon Halevy, Hongrae Lee, Jayant Madhavan, Cong Yu, Daisy Zhe Wang, and Eugene Wu. 2018 · 2018
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TabVec: Table Vectors for Classification of Web Tables
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CERES: Distantly Supervised Relation Extraction from the Semi-Structured Web
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Meimei: An efficient probabilistic approach for semantically annotating tables. In Proceedings of the AAAI Conference , Vol. 33. 281–288
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Table2Vec: neural word and entity embeddings for table population and retrieval. In Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval . 1029–1032
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TURL: Table Understanding through Representation Learning
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Multi-Modal Information Extraction from Text, Semi-Structured, and Tabular Data on the Web. In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (Virtual Event, CA, USA) (KDD ’20) . Association for Computing Machinery, New York, NY, USA, 3543–3544
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TAPAS: Weakly Supervised Table Parsing via Pre-training. In ACL
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Web-scale Knowledge Collection
Colin Lockard, Prashant Shiralkar, Xin Dong, and Hannaneh Hajishirzi. 2020a · 2020
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A comprehensive survey on graph neural networks
Zonghan Wu, Shirui Pan, Fengwen Chen, Guodong Long, Chengqi Zhang, and S Yu Philip. 2020 · 2020
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TaBERT: Pretraining for Joint Understanding of Textual and Tabular Data. In ACL
Pengcheng Yin, G. Neubig, W. Yih, and S. Riedel. 2020 · 2020
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Web Table Extraction, Retrieval, and Augmentation: A Survey
Shuo Zhang and Krisztian Balog. 2020 · 2020
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Learning Semantic Annotations for Tabular Data
J Chen, I Horrocks, E Jimenez-Ruiz, and C Sutton. 2019 · 2094
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