Files in this item
Files | Description | Format |
---|---|---|
application/pdf ![]() | (no description provided) |
Description
Title: | Trustworthiness and the importance of graph structure |
Author(s): | Mayhew, Stephen |
Advisor(s): | Roth, Dan |
Department / Program: | Computer Science |
Discipline: | Computer Science |
Degree Granting Institution: | University of Illinois at Urbana-Champaign |
Degree: | M.S. |
Genre: | Thesis |
Subject(s): | Trustworthiness
data fusion crowdsourcing machine learning natural language processing |
Abstract: | We begin by giving a comprehensive literature review that ties together many fields which have heretofore remained separate. We comment on the approaches from each field and show which algorithms are similar and which are different. Then, starting from a concrete task, we extend traditional trustworthiness algorithms to deal with the more complex situation of multiclass list-valued trustworthiness. In addition, we introduce a learned predictive method based on standard classification algorithms. In the last section, we explore the theory of trustworthiness and begin to make progress towards charting the space of all trustworthiness graphs. We address the commonly underestimated importance of the structure of a trust- worthiness graph, and define a space in which to work as well as defining the solvability of a trustworthiness graph. Finally, we provide recommendations for future work. |
Issue Date: | 2014-05-30 |
URI: | http://hdl.handle.net/2142/49620 |
Rights Information: | Copyright 2014 Stephen Mayhew |
Date Available in IDEALS: | 2014-05-30 |
Date Deposited: | 2014-05 |
This item appears in the following Collection(s)
-
Dissertations and Theses - Computer Science
Dissertations and Theses from the Dept. of Computer Science -
Graduate Dissertations and Theses at Illinois
Graduate Theses and Dissertations at Illinois