PUMA publications for /author/Eugene%20Wu/queryhttps://puma.uni-kassel.de/author/Eugene%20Wu/queryPUMA RSS feed for /author/Eugene%20Wu/query2024-03-29T13:22:15+01:00Crowdsourced Databases: Query Processing with Peoplehttps://puma.uni-kassel.de/bibtex/229723ba38aa6039091769cd2f69a1514/jaeschkejaeschke2012-06-19T16:29:05+02:00database crowdsourcing intelligence social computing cirg collective query <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Adam Marcus" itemprop="url" href="/author/Adam%20Marcus"><span itemprop="name">A. Marcus</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Eugene Wu" itemprop="url" href="/author/Eugene%20Wu"><span itemprop="name">E. Wu</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Samuel Madden" itemprop="url" href="/author/Samuel%20Madden"><span itemprop="name">S. Madden</span></a></span>, und <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Robert C. Miller" itemprop="url" href="/author/Robert%20C.%20Miller"><span itemprop="name">R. Miller</span></a></span>. </span><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">Proceedings of the 5th Biennial Conference on Innovative Data Systems Research</span>, </em></span><em>Seite <span itemprop="pagination">211--214</span>. </em><em><span itemprop="publisher">CIDR</span>, </em>(<em><span>Januar 2011<meta content="Januar 2011" itemprop="datePublished"/></span></em>)Tue Jun 19 16:29:05 CEST 2012Proceedings of the 5th Biennial Conference on Innovative Data Systems Researchjan211--214Crowdsourced Databases: Query Processing with People2011database crowdsourcing intelligence social computing cirg collective query Amazon's Mechanical Turk (\MTurk") service allows users to post short tasks (\HITs") that other users can receive a small amount of money for completing. Common tasks on the system include labelling a collection of images, com- bining two sets of images to identify people which appear in both, or extracting sentiment from a corpus of text snippets. Designing a work ow of various kinds of HITs for ltering, aggregating, sorting, and joining data sources together is common, and comes with a set of challenges in optimizing the cost per HIT, the overall time to task completion, and the accuracy of MTurk results. We propose Qurk, a novel query system for managing these work ows, allowing crowd- powered processing of relational databases. We describe a number of query execution and optimization challenges, and discuss some potential solutions.