{"type":"ScholarlyArticle","title":"How to Keep a Knowledge Base Synchronized with Its Encyclopedia Source","authors":[{"name":"Jiaqing Liang","slug":"jiaqing-liang","given":"Jiaqing","family":"Liang","affiliation":"Fudan University , Shanghai , China"},{"name":"Sheng Zhang","slug":"sheng-zhang","given":"Sheng","family":"Zhang","affiliation":"School of Computer Science , Shanghai Key Laboratory of Data Science; Shuyan Technology , Shanghai , China; Shanghai Internet Big Data Engineering Technology Research Center , China; Xiaoi Research , Shanghai , China"},{"name":"Yanghua Xiao","slug":"yanghua-xiao","given":"Yanghua","family":"Xiao","affiliation":"Fudan University , Shanghai , China"}],"abstract":"Knowledge bases are playing an increasingly important role in many real-world applications.\r\nHowever, most of these knowledge bases tend to be outdated, which limits the utility of these knowledge bases.\r\nIn this paper, we investigate how to keep the freshness of the knowledge base by synchronizing it with its data source (usually encyclopedia websites).\r\nA direct solution is revisiting the whole encyclopedia periodically and rerun the entire pipeline of the construction of knowledge base like most existing methods.\r\nHowever, this solution is wasteful and incurs massive overload of the network, which limits the update frequency and leads to knowledge obsolescence.\r\nTo overcome the weakness, we propose a set of synchronization principles upon which we build an Update System for knowledge Base (USB) with an update frequency predictor of entities as the core component. \r\nWe also design a set of effective features and realize the predictor. \r\nWe conduct extensive experiments to justify the effectiveness of the proposed system, model, as well as the underlying principles.\r\nFinally, we deploy USB on a Chinese knowledge base to improve its freshness.","doi":"10.24963/ijcai.2017/524","url":"https://ijcai.org/proceedings/2017/524","pdf":"https://ijcai.org/proceedings/2017/0524.pdf","markdown":"https://ijcai.org/proceedings/2017/524.md","bibtex":"https://ijcai.org/proceedings/2017/bibtex/524","volume":{"slug":"2017","title":"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2017","url":"https://ijcai.org/proceedings/2017/","year":2017,"location":"Melbourne, Australia","dates":"19-25 August 2017","editors":"Carles Sierra","isbn":"978-0-9992411-0-3","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2017"},"section":"Multidisciplinary Topics and Applications","track":"Main track","number":524,"pages":{"first":3749,"last":3755},"keywords":["Multidisciplinary Topics and Applications: Real-Time Systems","Natural Language Processing: Information Extraction","Multidisciplinary Topics and Applications: Multidisciplinary Topics and Applications"],"videos":[],"references":[{"position":1,"raw":"[Auer et al., 2007] Sören Auer, Christian Bizer, Georgi Ko- bilarov, Jens Lehmann, Richard Cyganiak, and Zachary Ives. 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