{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T05:25:25Z","timestamp":1740115525134,"version":"3.37.3"},"reference-count":0,"publisher":"IOS Press","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2008]]},"abstract":"<jats:p>Two approaches have been used to perform approximate inference in Bayesian networks for which exact inference is infeasible: employing an approximation algorithm, or approximating the structure. In this article we compare two structure-approximation techniques, edge-deletion and approximate structure learning based on sub-sampling, in terms of relative accuracy and computational efficiency. Our empirical results indicate that edge-deletion techniques dominate the subsampling\/induction strategy, in both accuracy and performance of generating the approximate network. We show, for several large Bayesian networks, how edge-deletion can create approximate networks with order-of-magnitude inference speedups and relatively little loss of accuracy.<\/jats:p>","DOI":"10.3233\/978-1-58603-891-5-851","type":"book-chapter","created":{"date-parts":[[2025,2,20]],"date-time":"2025-02-20T12:06:08Z","timestamp":1740053168000},"source":"Crossref","is-referenced-by-count":0,"title":["An Analysis of Bayesian Network Model-Approximation Techniques"],"prefix":"10.3233","author":[{"family":"Santana Adamo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Provan Gregory","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","ECAI 2008"],"original-title":[],"deposited":{"date-parts":[[2025,2,20]],"date-time":"2025-02-20T12:17:26Z","timestamp":1740053846000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.medra.org\/servlet\/aliasResolver?alias=iospressISSNISBN&issn=0922-6389&volume=178&spage=851"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2008]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/978-1-58603-891-5-851","relation":{},"ISSN":["0922-6389"],"issn-type":[{"value":"0922-6389","type":"print"}],"subject":[],"published":{"date-parts":[[2008]]}}}