2026-09-21T06:37:36Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/49620 2023-07-11 col_2142_5131 col_2142_10761 com_2142_5130 com_2142_10755 com_2142_234

Roth, Dan Mayhew, Stephen 2014-05-30T16:52:43Z 2014-05-30T16:52:43Z 2014-05 2014-05-30T16:52:43Z 2014-05 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. Item withdrawn by Mark Zulauf (zulauf@illinois.edu) on 2014-04-30T17:10:06Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 6 Makefile: 805 bytes, checksum: b0e8244611e1219b067b99c8fa588cbc (MD5) uiucthesis2009.sty: 16947 bytes, checksum: e6071d028db7167274c9f3aa9d83fb5f (MD5) uiucthesis2009.cls: 17122 bytes, checksum: 1020a993eb754707c3a9fedaafac8c46 (MD5) Mayhew_Stephen.tex: 83289 bytes, checksum: 591a93167cd51caa4ad82c846458a5d5 (MD5) thesis.pdf: 306369 bytes, checksum: 47ffc6ba80ed5854c59d2ddee2e6df15 (MD5) Mayhew_Stephen.pdf: 306369 bytes, checksum: 47ffc6ba80ed5854c59d2ddee2e6df15 (MD5) Made available in DSpace on 2014-05-30T16:52:43Z (GMT). No. of bitstreams: 6 Stephen_Mayhew.pdf: 306369 bytes, checksum: 47ffc6ba80ed5854c59d2ddee2e6df15 (MD5) Makefile: 805 bytes, checksum: b0e8244611e1219b067b99c8fa588cbc (MD5) uiucthesis2009.sty: 16947 bytes, checksum: e6071d028db7167274c9f3aa9d83fb5f (MD5) uiucthesis2009.cls: 17122 bytes, checksum: 1020a993eb754707c3a9fedaafac8c46 (MD5) Mayhew_Stephen.tex: 83289 bytes, checksum: 591a93167cd51caa4ad82c846458a5d5 (MD5) license.txt: 4063 bytes, checksum: 1d941b001c1d7ad616d8659ead1a0ef0 (MD5) http://hdl.handle.net/2142/49620 en Copyright 2014 Stephen Mayhew Trustworthiness data fusion crowdsourcing machine learning natural language processing Trustworthiness and the importance of graph structure text Computer Science 1434 Computer Science 0112 University of Illinois at Urbana-Champaign Thesis M.S. MS:Computer Science -UIUC 10KS0112MS