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Knowl. Discov. Data"],"published-print":{"date-parts":[[2025,1,31]]},"abstract":"<jats:p>\n            <jats:bold>Conditional Independence (CI)<\/jats:bold>\n            tests play an essential role in causal discovery from observational data, enabling the measurement of independence between two nodes. However, traditional CI tests ignore the imbalanced occurrence probabilities of node values, which may affect the accuracy of determining independence between nodes. To address this problem, we first introduce a new concept of the Node-imbalance phenomenon to describe the imbalance of node values in the Bayesian network data and analyze the influence of the Node-imbalance phenomenon on the traditional CI tests, then we propose a\n            <jats:bold>Weight-Based Conditional Independence (WCI)<\/jats:bold>\n            test to improve the accuracy of CI tests in the presence of Node-imbalance. In the experiments, we verify that WCI effectively measures the dependency between nodes in the Node-imbalance phenomenon compared with the traditional independence tests, and the state-of-the-art causal discovery algorithms reduce the number of false causal orientations through WCI.\n          <\/jats:p>","DOI":"10.1145\/3687467","type":"journal-article","created":{"date-parts":[[2024,8,28]],"date-time":"2024-08-28T18:22:55Z","timestamp":1724869375000},"page":"1-24","update-policy":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["Causal Discovery Using Weight-Based Conditional Independence Test"],"prefix":"10.1145","volume":"19","author":[{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0003-4812-6676","authenticated-orcid":false,"given":"Zhaolong","family":"Ling","sequence":"first","affiliation":[{"name":"Anhui University, Hefei, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0002-0241-4931","authenticated-orcid":false,"given":"Bo","family":"Li","sequence":"additional","affiliation":[{"name":"Anhui University, Hefei, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0001-8709-1088","authenticated-orcid":false,"given":"Yiwen","family":"Zhang","sequence":"additional","affiliation":[{"name":"Anhui University, Hefei, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0002-3607-0022","authenticated-orcid":false,"given":"Peng","family":"Zhou","sequence":"additional","affiliation":[{"name":"Anhui University, Hefei, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0002-8204-6197","authenticated-orcid":false,"given":"Xingyu","family":"Wu","sequence":"additional","affiliation":[{"name":"The Hong Kong Polytechnic University, Hong Kong SAR, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0009-0006-4689-534X","authenticated-orcid":false,"given":"Yuee","family":"Huang","sequence":"additional","affiliation":[{"name":"Wannan Medical College, Wuhu, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0003-2442-4572","authenticated-orcid":false,"given":"Kui","family":"Yu","sequence":"additional","affiliation":[{"name":"Hefei University of Technology, Hefei, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0003-2396-1704","authenticated-orcid":false,"given":"Xindong","family":"Wu","sequence":"additional","affiliation":[{"name":"Hefei University of Technology, Hefei, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2024,11,29]]},"reference":[{"issue":"1","key":"e_1_3_2_2_2","first-page":"171","article-title":"Local causal and Markov blanket induction for causal discovery and feature selection for classification part I: Algorithms and empirical evaluation","volume":"11","author":"Aliferis Constantin F.","year":"2010","unstructured":"Constantin F. 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