{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T14:50:28Z","timestamp":1777733428597,"version":"3.51.4"},"reference-count":29,"publisher":"Association for Computing Machinery (ACM)","issue":"11","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Proc. VLDB Endow."],"published-print":{"date-parts":[[2012,7]]},"abstract":"<jats:p>It is universal to see people obtain knowledge on micro-blog services by asking others decision making questions. In this paper, we study the Jury Selection Problem(JSP) by utilizing crowdsourcing for decision making tasks on micro-blog services. Specifically, the problem is to enroll a subset of crowd under a limited budget, whose aggregated wisdom via Majority Voting scheme has the lowest probability of drawing a wrong answer(Jury Error Rate-JER).<\/jats:p>\n          <jats:p>\n            Due to various individual error-rates of the crowd, the calculation of JER is non-trivial. Firstly, we explicitly state that JER is the probability when the number of wrong jurors is larger than half of the size of a jury. To avoid the exponentially increasing calculation of\n            <jats:italic>JER<\/jats:italic>\n            , we propose two efficient algorithms and an effective bounding technique. Furthermore, we study the Jury Selection Problem on two crowdsourcing models, one is for altruistic users(\n            <jats:italic>AltrM<\/jats:italic>\n            ) and the other is for incentive-requiring users(\n            <jats:italic>PayM<\/jats:italic>\n            ) who require extra payment when enrolled into a task. For the\n            <jats:italic>AltrM<\/jats:italic>\n            model, we prove the monotonicity of JER on individual error rate and propose an efficient exact algorithm for JSP. For the\n            <jats:italic>PayM<\/jats:italic>\n            model, we prove the NP-hardness of JSP on\n            <jats:italic>PayM<\/jats:italic>\n            and propose an efficient greedy-based heuristic algorithm. Finally, we conduct a series of experiments to investigate the traits of JSP, and validate the efficiency and effectiveness of our proposed algorithms on both synthetic and real micro-blog data.\n          <\/jats:p>","DOI":"10.14778\/2350229.2350264","type":"journal-article","created":{"date-parts":[[2014,6,24]],"date-time":"2014-06-24T12:17:57Z","timestamp":1403612277000},"page":"1495-1506","source":"Crossref","is-referenced-by-count":101,"title":["Whom to ask?"],"prefix":"10.14778","volume":"5","author":[{"given":"Caleb Chen","family":"Cao","sequence":"first","affiliation":[{"name":"The Hong Kong University of Science and Technology, Kowloon, Hong Kong SAR, PR China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jieying","family":"She","sequence":"additional","affiliation":[{"name":"The Hong Kong University of Science and Technology, Kowloon, Hong Kong SAR, PR China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yongxin","family":"Tong","sequence":"additional","affiliation":[{"name":"The Hong Kong University of Science and Technology, Kowloon, Hong Kong SAR, PR China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lei","family":"Chen","sequence":"additional","affiliation":[{"name":"The Hong Kong University of Science and Technology, Kowloon, Hong Kong SAR, PR China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2012,7]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/1480506.1480508"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1177\/1354856507084420"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/956863.956965"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/1963405.1963500"},{"key":"e_1_2_1_5_1","first-page":"10","volume-title":"ICWSM","author":"Cha M.","year":"2010","unstructured":"M. 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In COCOON, pages 1--17, 1999."},{"key":"e_1_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/1557019.1557074"},{"key":"e_1_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1083-6101.2007.00395.x"},{"key":"e_1_2_1_18_1","volume-title":"MIT Sloan Research Paper No. 4732--09","author":"Malone T. W.","year":"2009","unstructured":"T. W. Malone , R. Laubacher , and C. Dellarocas . Harnessing crowds: mapping the genome of collective intelligence. Technical report , MIT Sloan Research Paper No. 4732--09 , 2009 . T. W. Malone, R. Laubacher, and C. Dellarocas. Harnessing crowds: mapping the genome of collective intelligence. Technical report, MIT Sloan Research Paper No. 4732--09, 2009."},{"key":"e_1_2_1_19_1","first-page":"211","volume-title":"CIDR","author":"Marcus A.","year":"2011","unstructured":"A. Marcus , E. Wu , S. Madden , and R. C. Miller . Crowdsourced databases: Query processing with people . In CIDR , pages 211 -- 214 , 2011 . A. Marcus, E. Wu, S. Madden, and R. C. Miller. Crowdsourced databases: Query processing with people. In CIDR, pages 211--214, 2011."},{"key":"e_1_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/1718487.1718519"},{"key":"e_1_2_1_21_1","doi-asserted-by":"crossref","DOI":"10.1017\/CBO9780511813603","volume-title":"Probability and Computing: Randomized Algorithms and Probabilistic Analysis","author":"Mitzenmacher M.","year":"2005","unstructured":"M. Mitzenmacher and E. Upfal . Probability and Computing: Randomized Algorithms and Probabilistic Analysis . Cambridge Univ. Press , NY , USA, 2005 . M. Mitzenmacher and E. Upfal. Probability and Computing: Randomized Algorithms and Probabilistic Analysis. Cambridge Univ. Press, NY, USA, 2005."},{"key":"e_1_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.14778\/1952376.1952377"},{"key":"e_1_2_1_24_1","volume-title":"Detecting and tracking the spread of astroturf memes in microblog streams. CoRR, abs\/1011.3768","author":"Ratkiewicz J.","year":"2010","unstructured":"J. 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