IOTA: Interlinking of heterogeneous multilingual open fiscal DaTA
作者：
Highlights：
• IOTA is designed as a scalable framework to interlink translated fiscal concepts.
• There are 19 similarity measures experimented within IOTA.
• Token Sort yields the highest F1 score yet not robust to threshold change.
• TF-IDF has a good and robust F1 score, but it is computationally expensive.
• Results keep highly & positively correlated even as translation pairs are changed.
摘要
•IOTA is designed as a scalable framework to interlink translated fiscal concepts.•There are 19 similarity measures experimented within IOTA.•Token Sort yields the highest F1 score yet not robust to threshold change.•TF-IDF has a good and robust F1 score, but it is computationally expensive.•Results keep highly & positively correlated even as translation pairs are changed.
论文关键词：Data interlinking,Budget and spending data,String similarity measure,Open data,Translated string matching framework,Cluster computing
论文评审过程：Received 26 August 2019, Revised 12 November 2019, Accepted 13 December 2019, Available online 18 December 2019, Version of Record 22 January 2020.
论文官网地址：https://doi.org/10.1016/j.eswa.2019.113135
