摘要：The growth of internet connectivity and bandwidth has now made it possible to harness ”human computation” in near-real time from a vast and ever-growing, distributed population of online internet users. In the process of distributing and managing knowledge online, so many concepts arose in which crowdsourcing is an example that cannot be overlooked. Crowdsourcing depends on human worker but human worker are prone to errors. To leverage the power of crowdsourcing, in this paper, a framework called Crowdsourcing Content Filtering (CrowCFil) System was designed. CrowCFil is a framework designed to exploit the conventional crowdsourcing techniques in order to improve the reliability and integrity of information given by contributors to requesters on a crowdsouring platform. It consists of three major functional modules: Task Initiator Module, Contributor Module and CrowCFil Engine Module, all of which are interdependent. The core part of System is the CrowCFilS Engine Module, which gives the system the power to check for the reliability and integrity of response as submitted by a contributor with the aid well defined algorithm embedded into a set of interrelated functions present in it. The framework is suitable for implementation in a relatively large distributed crowdsourcing platform while keeping the cost of operating a crowdsourcing low
关键词：Crowdsourcing; knowledge management; Contributor; Requester; Filtering System
