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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Enhancing factoid question answering using frame semantic-based approaches

Ofoghi, Bahadorreza January 2009 (has links)
FrameNet is used to enhance the performance of semantic QA systems. FrameNet is a linguistic resource that encapsulates Frame Semantics and provides scenario-based generalizations over lexical items that share similar semantic backgrounds. / Doctor of Philosophy
2

Exploring User Trust in Natural Language Processing Systems : A Survey Study on ChatGPT Users

Aronsson Bünger, Morgan January 2024 (has links)
ChatGPT has become a popular technology among people and gained a considerable user base, because of its power to effectively generate responses to users requests. However, as ChatGPT’s popularity has grown and as other natural language processing systems (NLPs) are being developed and adopted, several concerns have been raised about the technology that could have implications on user trust. Because trust plays a central role in user willingness to adopt artificial intelligence (AI) systems and there is no consensus in research on what facilitates trust, it is important to conduct more research to identify the factors that affect user trust in artificial intelligence systems, especially modern technologies such as NLPs. The aim of the study was therefore to identify the factors that affect user trust in NLPs. The findings from the literature within trust and artificial intelligence indicated that there may exist a relationship between trust and transparency, explainability, accuracy, reliability, automation, augmentation, anthropomorphism and data privacy. These factors were quantitatively studied together in order to uncover what affects user trust in NLPs. The result from the study indicated that transparency, accuracy, reliability, automation, augmentation, anthropomorphism and data privacy all have a positive impact on user trust in NLPs, which both supported and opposed previous findings from literature.

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