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EmbNum+ maps lists of numerical values of columns into feature vectors in an embedding space, and a similarity metric can be calculated directly on these feature vectors. Evaluations on many datasets of various domains confirmed that EmbNum+ consistently outperformed other state-of-the-art approaches in terms of accuracy. The compact embedding representations also made EmbNum+ significantly faster than others and enable large-scale semantic labeling. Furthermore, attribute augmentation can be used to enhance the robustness and unlock the portability of EmbNum+, making it possible to be trained on one domain but applicable to many different domains.<\/jats:p>","DOI":"10.1007\/s00354-019-00076-w","type":"journal-article","created":{"date-parts":[[2019,11,4]],"date-time":"2019-11-04T18:03:08Z","timestamp":1572890588000},"page":"393-427","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["EmbNum+: Effective, Efficient, and Robust Semantic Labeling for Numerical Values"],"prefix":"10.1007","volume":"37","author":[{"given":"Phuc","family":"Nguyen","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Khai","family":"Nguyen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ryutaro","family":"Ichise","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hideaki","family":"Takeda","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,11,4]]},"reference":[{"issue":"6","key":"76_CR1","doi-asserted-by":"publisher","first-page":"421","DOI":"10.14778\/2536336.2536343","volume":"6","author":"MD Adelfio","year":"2013","unstructured":"Adelfio, M.D., Samet, H.: Schema extraction for tabular data on the web. 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