Trustworthiness and the importance of graph structure
Mayhew, Stephen
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https://hdl.handle.net/2142/49620
Description
Title
Trustworthiness and the importance of graph structure
Author(s)
Mayhew, Stephen
Issue Date
2014-05-30T16:52:43Z
Director of Research (if dissertation) or Advisor (if thesis)
Roth, Dan
Department of Study
Computer Science
Discipline
Computer Science
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(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.
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