MANAGING CROWD WISDOM IN CROWDSOURCING SYSTEM

MPhil Thesis Defence


Title: "MANAGING CROWD WISDOM IN CROWDSOURCING SYSTEM"

By

Miss Ye YUAN


Abstract

The huge amount of online users, with diverse backgrounds, act as powerful 
resources that Mobile Social Networks (MSNs) can utilize for 
crowdsourcing. Exploiting these on-line users as crowd workers is 
promising yet nontrivial. To efficiently leverage human intelligence or 
crowd wisdom, we need to address the following issues: 1) how to motivate 
users to participate, and 2) how to discourage malicious behaviors such as 
copying an- swers or making guesses. Furthermore, as low-quality answers 
may sharply degrade the accuracy of synthetic results, the last issue is 
3) how to weed these out. In this thesis, we present MacroWiz, a simple 
yet effective platform to manage crowd wisdom on MSNs. Given a task, 
MacroWiz motivates online users to contribute their knowledge or opinions, 
and assists the task holder in collecting answers, selecting reliable 
ones, and drawing ul- timate decisions. The platform consists of two 
functional units: online wisdom collection and offline answer selection. 
The former estimates and gathers the minimum number of answers required to 
satisfy the task requirement, while the latter analyzes the accuracy, the 
effectiveness, and the cost of each answer, based on which it selects 
those with high accuracy and low cost by solving a double target 
optimization problem. We validate the effectiveness of our platform using 
MovieLens Data sets which contain over one million anonymous ratings of 
movies. Our result shows that this platform significantly reduces the 
latency in making decisions and provides high-quality answers with low 
cost.


Date:			Thursday, 26 November 2015

Time:			12:00noon - 2:00pm

Venue:			Room 4621
 			Lifts 31/32

Committee Members:	Dr. Lei Chen (Supervisor)
 			Dr. Pan Hui (Chairperson)
 			Dr. Ke Yi


**** ALL are Welcome ****