Trustworthiness and the importance of graph structure

Trustworthiness;data fusion;crowdsourcing;machine learning;natural language processing

Mayhew, Stephen ; Roth ; Dan

关键词: Trustworthiness;    data fusion;    crowdsourcing;    machine learning;    natural language processing;   

Others  :  https://www.ideals.illinois.edu/bitstream/handle/2142/49620/Stephen_Mayhew.pdf?sequence=1&isAllowed=y

美国|英语

来源: The Illinois Digital Environment for Access to Learning and Scholarship

【 摘 要 】

We begin by giving a comprehensive literature review that ties together manyfields which have heretofore remained separate. We comment on the approachesfrom each field and show which algorithms are similar and which are different.Then, starting from a concrete task, we extend traditional trustworthinessalgorithms to deal with the more complex situation of multiclass list-valuedtrustworthiness. In addition, we introduce a learned predictive method basedon standard classification algorithms.In the last section, we explore the theory of trustworthiness and begin tomake progress towards charting the space of all trustworthiness graphs. Weaddress the commonly underestimated importance of the structure of a trust-worthiness graph, and define a space in which to work as well as defining thesolvability of a trustworthiness graph. Finally, we provide recommendations forfuture work.