{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,26]],"date-time":"2025-09-26T08:09:01Z","timestamp":1758874141456},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,8]]},"abstract":"<jats:p>Although several effective learning-from-crowd methods have been developed to infer correct labels from noisy crowdsourced labels, a method for post-processed expert validation is still needed. This paper introduces a semi-supervised learning algorithm that is capable of selecting the most informative instances and maximizing the influence of expert labels. Specifically, we have developed a complete uncertainty assessment to facilitate the selection of the most informative instances. The expert labels are then propagated to similar instances via regularized Bayesian inference. Experiments on both real-world and simulated datasets indicate that given a specific accuracy goal (e.g., 95%) our method reduces expert effort from 39% to 60% compared with the state-of-the-art method.<\/jats:p>","DOI":"10.24963\/ijcai.2017\/324","type":"proceedings-article","created":{"date-parts":[[2017,7,28]],"date-time":"2017-07-28T09:14:07Z","timestamp":1501233247000},"page":"2329-2336","source":"Crossref","is-referenced-by-count":18,"title":["Improving Learning-from-Crowds through Expert Validation"],"prefix":"10.24963","author":[{"given":"Mengchen","family":"Liu","sequence":"first","affiliation":[{"name":"School of Software, Tsinghua University, Beijing, P.R. China"},{"name":"Tsinghua National Lab for Information Science and Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Liu","family":"Jiang","sequence":"additional","affiliation":[{"name":"School of Software, Tsinghua University, Beijing, P.R. China"},{"name":"Tsinghua National Lab for Information Science and Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Junlin","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Software, Tsinghua University, Beijing, P.R. China"},{"name":"Tsinghua National Lab for Information Science and Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiting","family":"Wang","sequence":"additional","affiliation":[{"name":"Microsoft Research, Beijing, P.R. China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jun","family":"Zhu","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, Tsinghua University, Beijing, P.R. China"},{"name":"Tsinghua National Lab for Information Science and Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shixia","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Software, Tsinghua University, Beijing, P.R. China"},{"name":"Tsinghua National Lab for Information Science and Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"10584","event":{"number":"26","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)","University of Technology Sydney (UTS)","Australian Computer Society (ACS)"],"acronym":"IJCAI-2017","name":"Twenty-Sixth International Joint Conference on Artificial Intelligence","start":{"date-parts":[[2017,8,19]]},"theme":"Artificial Intelligence","location":"Melbourne, Australia","end":{"date-parts":[[2017,8,26]]}},"container-title":["Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2017,7,28]],"date-time":"2017-07-28T11:53:22Z","timestamp":1501242802000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2017\/324"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2017,8]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2017\/324","relation":{},"subject":[],"published":{"date-parts":[[2017,8]]}}}