Crowdsourced Data Management: Overview and Challenges

摘要: Many important data management and analytics tasks cannot be completely addressed by automated processes. Crowdsourcing is an effective way to harness human cognitive abilities process these computer-hard tasks, such as entity resolution, sentiment analysis, image recognition. Crowdsourced has been extensively studied in research industry recently. In this tutorial, we will survey synthesize a wide spectrum of existing studies on crowdsourced management. We first give overview crowdsourcing, then summarize the fundamental techniques, including quality control, cost latency which must considered Next review operators, selection, collection, join, top-k, sort, categorize, aggregation, skyline, planning, schema matching, mining spatial crowdsourcing. also discuss crowdsourcing optimization techniques systems. Finally, provide emerging challenges.