Conference on Automated Knowledge Base Construction最新文献

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The Vagueness of Vagueness in Noun Phrases 名词短语中模糊性的模糊性
Conference on Automated Knowledge Base Construction Pub Date : 1900-01-01 DOI: 10.24432/C5T884
Pierre-Henri Paris, Syrine El Aoud, Fabian M. Suchanek
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引用次数: 2
Enterprise Alexandria: Online High-Precision Enterprise Knowledge Base Construction with Typed Entities Enterprise Alexandria:基于类型化实体的在线高精度企业知识库构建
Conference on Automated Knowledge Base Construction Pub Date : 1900-01-01 DOI: 10.24432/C5JS3X
J. Winn, M. Venanzi, T. Minka, Ivan Korostelev, J. Guiver, Elena Pochernina, Pavel Mishkov, Alex Spengler, Denise J. Wilkins, Siân E. Lindley, Richard Banks, Sam Webster, Yordan Zaykov
{"title":"Enterprise Alexandria: Online High-Precision Enterprise Knowledge Base Construction with Typed Entities","authors":"J. Winn, M. Venanzi, T. Minka, Ivan Korostelev, J. Guiver, Elena Pochernina, Pavel Mishkov, Alex Spengler, Denise J. Wilkins, Siân E. Lindley, Richard Banks, Sam Webster, Yordan Zaykov","doi":"10.24432/C5JS3X","DOIUrl":"https://doi.org/10.24432/C5JS3X","url":null,"abstract":"We present Enterprise Alexandria, a new system for automatically constructing a knowledge base with high-precision and typed entities from private enterprise data such as emails, documents and intranet pages. Built as an extension of Alexandria [Winn et al., 2019], the key novelty of Enterprise Alexandria is the ability in processing both the textual information and the structured metadata available in each document in an online learning fashion, making use of any manual curations that have happened in the interim. This task is performed entirely eyes-off to respect the privacy of the user and the restricted access their documents. The knowledge discovery process uses a probabilistic program defining the process of generating the data item from a set of unknown typed entities. Using probabilistic inference, Enterprise Alexandria can jointly discover a large set of entities with custom types specific to the organization. Experiments on three real-world datasets show that the system outperforms alternative methods with the ability to work effectively at large scale.","PeriodicalId":371465,"journal":{"name":"Conference on Automated Knowledge Base Construction","volume":"01 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131705728","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
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