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The critic then validates the temporal orders learned and deduces more ranked pairs by chasing the data with currency constraints; it also provides augmented training data as feedback for the creator to improve the ranking in the next round. The process proceeds until the temporal order obtained becomes stable. Using real-life and synthetic datasets, we show that GATE is able to determine temporal orders with<jats:italic>F<\/jats:italic>-measure above 80%, improving deep learning by 7.8% and rule-based methods by 34.4%.<\/jats:p>","DOI":"10.14778\/3594512.3594524","type":"journal-article","created":{"date-parts":[[2023,6,23]],"date-time":"2023-06-23T00:28:36Z","timestamp":1687480116000},"page":"1944-1957","update-policy":"http:\/\/dx.doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["Learning and Deducing Temporal Orders"],"prefix":"10.14778","volume":"16","author":[{"given":"Wenfei","family":"Fan","sequence":"first","affiliation":[{"name":"Shenzhen Institute of Computing Sciences, China University of Edinburgh, United Kingdom and Beihang University, China"}]},{"given":"Resul","family":"Tugay","sequence":"additional","affiliation":[{"name":"University of Edinburgh, United Kingdom"}]},{"given":"Yaoshu","family":"Wang","sequence":"additional","affiliation":[{"name":"Shenzhen Institute of Computing Sciences, China"}]},{"given":"Min","family":"Xie","sequence":"additional","affiliation":[{"name":"Shenzhen Institute of Computing Sciences, China"}]},{"given":"Muhammad Asif","family":"Ali","sequence":"additional","affiliation":[{"name":"King Abdullah University of Science and Technology, Kingdom of Saudi Arabia"}]}],"member":"320","published-online":{"date-parts":[[2023,6,22]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"2022. 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