Crowdsourced Query Processing on Microblogs

MPhil Thesis Defence


Title: "Crowdsourced Query Processing on Microblogs"

By

Mr. Weikeng CHEN


Abstract

Currently, crowdsourced query processing is done on reward-driven 
platforms such as Amazon Mechanical Turk (AMT)} and CrowdFlower. However, 
due to budget constraints for conducting a crowdsourcing task in practice, 
the scalability is inherently poor. In this paper, we exploit microblogs 
for supporting crowdsourced query processing. We leverage the social 
computation power and decentralize the evaluation of the crowdsourcing 
platforms queries towards social networks. We propose a new problem of 
minimizing the cost of processing crowdsourced queries on microblogs, 
given a specified accuracy threshold of users' votes. This problem is 
NP-hard and its computation is #P-hard. To tackle this problem, we develop 
a greedy algorithm with a quality guarantee. We demonstrate the 
performance on real data sets.


Date:			Wednesday, 16 August 2017

Time:			10:00am - 12:00noon

Venue:			Room 2612B
 			Lifts 31/32

Committee Members:	Dr. Wilfred Ng (Supervisor)
 			Dr. Qiong Luo (Chairperson)
 			Dr. Ke Yi


**** ALL are Welcome ****