Please use this identifier to cite or link to this item:
Title: Data Fusion in Managing Crowdsourcing Data Analytics Systems
Authors: LIU XUAN
Keywords: Data Fusion, Crowdsourcing
Issue Date: 2-Aug-2013
Source: LIU XUAN (2013-08-02). Data Fusion in Managing Crowdsourcing Data Analytics Systems. ScholarBank@NUS Repository.
Abstract: Nowadays, the fast growth of the amount of Web data has attracted a lot of research interests. However, among these huge amount of Web data, a lot of the data is dirty and erroneous. Hence, there could be multiple conflicting values representing the same object. As a result, it is crucial important to distinguish the correct value from the conflicting values. In this thesis, we aim to present three techniques to solve the data fusion problem, namely the online data fusion method of the categorical data, the data fusion method of the continuous data and the data fusion method used in designing crowdsourcing based data analytics systems. The research works listed in this thesis have significantly affected both the data fusion area and crowdsourcing data management area.
Appears in Collections:Ph.D Theses (Open)

Show full item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
LiuX.pdf5.8 MBAdobe PDF



Page view(s)

checked on Dec 11, 2017


checked on Dec 11, 2017

Google ScholarTM


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.