文章基本信息

标题：Efficient Query Optimization for Easy Retrieval of Crowd Resources
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作者：G.Archana ; P.Srinivasan
期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2016
卷号：4
期号：2
页码：1410
DOI：10.15680/IJIRCCE.2016.0402104
出版社：S&S Publications
摘要：Declarative crowdsourcing is intended to cover the complexities and relieve the user of the burden of addressing the group. The user is simply needed to submit anSQL-like question and therefore the system takes the responsibility of assembling the question, generating the execution set up and evaluating within the crowdsourcing marketplace. A given question will have many different execution plans and therefore the distinction in crowdsourcing value between the most effective and therefore the worst plans could also be many orders of magnitude. Previously, we tend to proposedCROWDOP, a cost-based question optimization approach for declarative crowdsourcing systems. We incline to develop efficient algorithms within the CROWDOP for optimizing 3 forms of queries: choice queries, join queries, and complicated selection-join queries. In this paper we propose, extract the information from the CROWDOP using preprocessing.Suggestions given by the statistical analysis of car buyers. This suggestionsincludes the various car's attributes like, price, model, colour, speed, fuel type.Itconsists of system performance and query suggestions for consumer liking
关键词：Declarative crowdsourcing; Query Optimization; CROWDOP