{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,10]],"date-time":"2025-05-10T23:01:09Z","timestamp":1746918069889},"reference-count":13,"publisher":"Association for Computing Machinery (ACM)","issue":"12","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Proc. VLDB Endow."],"published-print":{"date-parts":[[2018,8]]},"abstract":"<jats:p>Crowd-powered database systems can leverage the crowd's ability to address machine-hard problems, e.g., data integration. Existing crowdsourcing systems adopt the traditional tree model to select a good query plan. However, the tree model can optimize the I\/O cost but cannot optimize the monetary cost, latency and quality, which are three important optimization goals in crowdsourcing. To address this limitation, we demonstrate CDB, a crowd-powered database system. CDB proposes a new graph-based model that adopts a fine-grained tuple-level optimization model which significantly outperforms existing coarse-grained tree-based optimization models. Moreover, CDB provides a unified framework to simultaneously optimize the monetary cost, quality and latency. We have deployed CDB on well-known crowd-sourcing platforms and users can easily use our system to deploy their applications. We will demonstrate how to use CDB to address real-world applications, including web table integration and entity collection.<\/jats:p>","DOI":"10.14778\/3229863.3236226","type":"journal-article","created":{"date-parts":[[2018,9,10]],"date-time":"2018-09-10T12:12:28Z","timestamp":1536581548000},"page":"1926-1929","source":"Crossref","is-referenced-by-count":20,"title":["CDB"],"prefix":"10.14778","volume":"11","author":[{"given":"Guoliang","family":"Li","sequence":"first","affiliation":[{"name":"Tsinghua University"}]},{"given":"Chengliang","family":"Chai","sequence":"additional","affiliation":[{"name":"Tsinghua University"}]},{"given":"Ju","family":"Fan","sequence":"additional","affiliation":[{"name":"Renmin University"}]},{"given":"Xueping","family":"Weng","sequence":"additional","affiliation":[{"name":"Tsinghua University"}]},{"given":"Jian","family":"Li","sequence":"additional","affiliation":[]},{"given":"Yudian","family":"Zheng","sequence":"additional","affiliation":[{"name":"Twitter"}]},{"given":"Yuanbing","family":"Li","sequence":"additional","affiliation":[{"name":"Tsinghua University"}]},{"given":"Xiang","family":"Yu","sequence":"additional","affiliation":[{"name":"Tsinghua University"}]},{"given":"Xiaohang","family":"Zhang","sequence":"additional","affiliation":[{"name":"Tsinghua University"}]},{"given":"Haitao","family":"Yuan","sequence":"additional","affiliation":[{"name":"Tsinghua University"}]}],"member":"320","published-online":{"date-parts":[[2018,8]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2018.00039"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/2882903.2915252"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2015.2407353"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/1989323.1989331"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/3035918.3064036"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/3183713.3183762"},{"key":"e_1_2_1_7_1","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 , 2011 . A. Marcus, E. Wu, S. Madden, and R. C. Miller. Crowdsourced databases: Query processing with people. In CIDR, 2011."},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/2396761.2398421"},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/2463676.2465280"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.14778\/2921558.2921559"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.14778\/3025111.3025118"},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.14778\/3055540.3055547"},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/2723372.2749430"}],"container-title":["Proceedings of the VLDB Endowment"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.14778\/3229863.3236226","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,28]],"date-time":"2022-12-28T10:13:37Z","timestamp":1672222417000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.14778\/3229863.3236226"}},"subtitle":["a crowd-powered database system"],"short-title":[],"issued":{"date-parts":[[2018,8]]},"references-count":13,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2018,8]]}},"alternative-id":["10.14778\/3229863.3236226"],"URL":"https:\/\/doi.org\/10.14778\/3229863.3236226","relation":{},"ISSN":["2150-8097"],"issn-type":[{"value":"2150-8097","type":"print"}],"subject":[],"published":{"date-parts":[[2018,8]]}}}