{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,20]],"date-time":"2025-09-20T19:01:59Z","timestamp":1758394919893},"reference-count":25,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2013,12,14]],"date-time":"2013-12-14T00:00:00Z","timestamp":1386979200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Mach Learn"],"published-print":{"date-parts":[[2014,4]]},"DOI":"10.1007\/s10994-013-5424-x","type":"journal-article","created":{"date-parts":[[2013,12,13]],"date-time":"2013-12-13T13:14:03Z","timestamp":1386940443000},"page":"71-86","source":"Crossref","is-referenced-by-count":9,"title":["Collaborative information acquisition for data-driven decisions"],"prefix":"10.1007","volume":"95","author":[{"given":"Danxia","family":"Kong","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Maytal","family":"Saar-Tsechansky","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2013,12,14]]},"reference":[{"key":"5424_CR1","first-page":"1","volume-title":"Proceedings of the fifteenth international conference on machine learning","author":"N. Abe","year":"1998","unstructured":"Abe, N., & Mamitsuka, H. (1998). Query learning strategies using boosting and bagging. In Proceedings of the fifteenth international conference on machine learning (pp. 1\u20139). San Mateo: Morgan Kaufmann"},{"key":"5424_CR2","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1145\/1835804.1835817","volume-title":"Proceedings of the 16th ACM SIGKDD international conference on knowledge discovery and data mining (KDD \u201910)","author":"N. Abe","year":"2010","unstructured":"Abe, N., Melville, P., Pendus, C., Reddy, C. K., Jensen, D. L., Thomas, V. P., Bennett, J. J., Anderson, G. F., Cooley, B. R., Kowalczyk, M., Domick, M., & Gardinier, T. (2010). Optimizing debt collections using constrained reinforcement learning. In Proceedings of the 16th ACM SIGKDD international conference on knowledge discovery and data mining (KDD \u201910) (pp. 75\u201384). New York: ACM."},{"key":"5424_CR3","volume-title":"Cost-sensitive machine learning","author":"J. Attenberg","year":"2011","unstructured":"Attenberg, J., Melville, P., Provost, F., & Saar-Tsechansky, M. (2011). Selective data acquisition for machine learning. In Cost-sensitive machine learning. Boca Raton: CRC Press."},{"key":"5424_CR4","unstructured":"Christie, E., & Holzner, M. (2006). What explains tax evasion? An empirical assessment based on European data. wiiw working papers 40, The Vienna Institute for International Economic Studies, wiiw."},{"issue":"2","key":"5424_CR5","first-page":"201","volume":"15","author":"D. Cohn","year":"1994","unstructured":"Cohn, D., Atlas, L., & Ladner, R. (1994). Improving generalization with active learning. Machine Learning, 15(2), 201\u2013221.","journal-title":"Machine Learning"},{"key":"5424_CR6","unstructured":"Cornelius, T. (2012). Wisconsin budget basics guide, Wisconsin budget project. http:\/\/www.wisconsinbudgetproject.org\/wp-content\/uploads\/2012\/07\/budgetbasics.pdf . Accessed 2013-05-11."},{"key":"5424_CR7","unstructured":"EOI (2012). Washington state budget 101. http:\/\/www.eoionline.org\/tax_reform\/fact_sheets\/WashingtonStateBudget101-Nov12.pdf . Accessed 2013-05-11."},{"key":"5424_CR8","volume-title":"The UCI KDD archive","author":"S. Hettich","year":"1999","unstructured":"Hettich, S., & Bay, S. D. (1999). In The UCI KDD archive."},{"key":"5424_CR9","unstructured":"IRS (2012). IRS releases new tax gap estimates; compliance rates remain statistically unchanged from previous study. http:\/\/www.irs.gov\/uac\/IRS-Releases-New-Tax-Gap-Estimates;-Compliance-Rates-Remain-Statistically-Unchanged-From-Previous-Study . Accessed 2013-05-15."},{"key":"5424_CR10","volume-title":"International joint conference on artificial intelligence","author":"A. Kapoor","year":"2007","unstructured":"Kapoor, A., Horvitz, E., & Basu, S. (2007). Selective supervision: guiding supervised learning with decision-theoretic active learning. In International joint conference on artificial intelligence."},{"key":"5424_CR11","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1038\/nature02236","volume":"427","author":"R. D. King","year":"2004","unstructured":"King, R. D., Whelan, K. E., Jones, F. M., Reiser, P. G. K., Bryant, C. H., Muggleton, S. H., Kell, D. B., & Oliver, S. G. (2004). Functional genomic hypothesis generation and experimentation by a robot scientist. Nature, 427, 247\u2013252.","journal-title":"Nature"},{"key":"5424_CR12","first-page":"231","volume-title":"Advances in neural information processing systems","author":"A. Krogh","year":"1995","unstructured":"Krogh, A., & Vedelsby, J. (1995). Neural network ensembles, cross validation, and active learning. In Advances in neural information processing systems (pp. 231\u2013238). Cambridge: MIT Press."},{"key":"5424_CR13","volume-title":"Proceedings of the 6th international conference on knowledge discovery and data mining","author":"D. Lewis","year":"1994","unstructured":"Lewis, D., & Gale, W. A. (1994). A sequential algorithm for training text classifiers. In Proceedings of the 6th international conference on knowledge discovery and data mining."},{"key":"5424_CR14","volume-title":"Proceedings of the 19th conference on knowledge uncertainty in artificial intelligence","author":"D. Lizotte","year":"2003","unstructured":"Lizotte, D., Madani, O., & Greiner, R. (2003). Budgeted learning of naive-Bayes classifiers. In Proceedings of the 19th conference on knowledge uncertainty in artificial intelligence."},{"key":"5424_CR15","volume-title":"Proceedings of the 3rd international conference on data mining","author":"P. Melville","year":"2004","unstructured":"Melville, P., Saar-Tsechansky, M., Provost, F., & Mooney, R. (2004). Active feature-value acquisition for classifier induction. In Proceedings of the 3rd international conference on data mining."},{"key":"5424_CR16","unstructured":"Micci-Barreca, D., & Ramachandran, S. (2004). Improving tax administration with data mining. White paper. Elite Analytics LLC."},{"key":"5424_CR17","volume-title":"C4.5: programs for machine learning","author":"J. R. Quinlan","year":"1993","unstructured":"Quinlan, J. R. (1993). C4.5: programs for machine learning. San Mateo: Morgan Kaufmann."},{"key":"5424_CR18","volume-title":"ACL","author":"R. Reichart","year":"2008","unstructured":"Reichart, R., Tomanek, K., & Hahn, U. (2008). Multi-task active learning for linguistic annotations. In ACL."},{"key":"5424_CR19","first-page":"441","volume-title":"Proceedings of the 18th international conference on machine learning","author":"N. Roy","year":"2001","unstructured":"Roy, N., & McCallum, A. (2001). Toward optimal active learning through sampling estimation of error reduction. In Proceedings of the 18th international conference on machine learning (pp. 441\u2013448)."},{"issue":"1","key":"5424_CR20","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1287\/isre.1070.0111","volume":"18","author":"M. Saar-Tsechansky","year":"2007","unstructured":"Saar-Tsechansky, M., & Provost, F. (2007). Decision-centric active learning of binary-outcome models. Information Systems Research, 18(1), 1\u201319.","journal-title":"Information Systems Research"},{"issue":"4","key":"5424_CR21","doi-asserted-by":"crossref","first-page":"664","DOI":"10.1287\/mnsc.1080.0952","volume":"55","author":"M. Saar-Tsechansky","year":"2009","unstructured":"Saar-Tsechansky, M., Melville, P., & Provost, F. J. (2009). Active feature-value acquisition. Management Science, 55(4), 664\u2013684.","journal-title":"Management Science"},{"key":"5424_CR22","unstructured":"Settles, B. (2009). Active learning literature survey. Tech. rep., University of Wisconsin-Madison."},{"key":"5424_CR23","doi-asserted-by":"crossref","first-page":"614","DOI":"10.1145\/1401890.1401965","volume-title":"KDD","author":"V. S. Sheng","year":"2008","unstructured":"Sheng, V. S., Provost, F., & Ipeirotis, P. G. (2008). Get another label? Improving data quality and data mining using multiple, noisy labelers. In KDD (pp. 614\u2013622)."},{"key":"5424_CR24","volume-title":"Data mining: practical machine learning tools and techniques with Java implementations","author":"I. H. Witten","year":"1999","unstructured":"Witten, I. H., & Frank, E. (1999). Data mining: practical machine learning tools and techniques with Java implementations. San Mateo: Morgan Kaufmann."},{"key":"5424_CR25","first-page":"204","volume-title":"Proceedings of the 7th international conference on knowledge discovery and data mining","author":"B. Zadrozny","year":"2001","unstructured":"Zadrozny, B., & Elkan, C. (2001). Learning and making decisions when costs and probabilities are both unknown. In Proceedings of the 7th international conference on knowledge discovery and data mining (pp. 204\u2013212). New York: ACM."}],"container-title":["Machine Learning"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10994-013-5424-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10994-013-5424-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10994-013-5424-x","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,4]],"date-time":"2019-08-04T18:29:40Z","timestamp":1564943380000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10994-013-5424-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013,12,14]]},"references-count":25,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2014,4]]}},"alternative-id":["5424"],"URL":"https:\/\/doi.org\/10.1007\/s10994-013-5424-x","relation":{},"ISSN":["0885-6125","1573-0565"],"issn-type":[{"value":"0885-6125","type":"print"},{"value":"1573-0565","type":"electronic"}],"subject":[],"published":{"date-parts":[[2013,12,14]]}}}