Reeder, Samuel_MCS_2020

Title Reeder, Samuel_MCS_2020
Alternative Title Effects of Explanations of Recommendation Engines
Creator Reeder, Samuel
Collection Name Master of Computer Science
Description Recommendation engines are a ubiquitous feature in the modern era. The advent of the internet as a means of buying and selling products has pushed the field of artificial intelligence to produce software and algorithms that produce accurate predictions with respect to consumer's desirers and buying tendencies. Producing accurate recommendation engines generally involves the use of complex algorithms and machine learning driven models. The complexity of these models brings with it several disadvantages, one of these, is the lack of human comprehensibility. To resolve this issue research teams in the field are involved in programs that attempt to make artificial intelligence systems explainable. In the context of recommendation engines an explainable system would be one that provides users with a recommendation paired with an explanation that is relevant to the user. In this paper research is presented that gives insight into what types of explanations are most effective in changing a user's trust and understanding in recommendation engines.
Subject Computer science
Keywords Recommendation engines; Internet; Buying patterns
Digital Publisher Stewart Library, Weber State University
Date 2020
Language eng
Rights The author has granted Weber State University Archives a limited, non-exclusive, royalty-free license to reproduce their theses, in whole or in part, in electronic or paper form and to make it available to the general public at no charge. The author retains all other rights.
Source University Archives Electronic Records; Master of Computer Science. Stewart Library, Weber State University
OCR Text Show
Format application/pdf
ARK ark:/87278/s62wfnq7
Setname wsu_smt
ID 96827
Reference URL https://digital.weber.edu/ark:/87278/s62wfnq7