2,475 research outputs found

    Which Step Do I Take First? Troubleshooting with Bayesian Models

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    Online discussion forums and community question-answering websites provide one of the primary avenues for online users to share information. In this paper, we propose text mining techniques which aid users navigate troubleshooting-oriented data such as questions asked on forums and their suggested solutions. We introduce Bayesian generative models of the troubleshooting data and apply them to two interrelated tasks (a) predicting the complexity of the solutions (e.g., plugging a keyboard in the computer is easier compared to installing a special driver) and (b) presenting them in a ranked order from least to most complex. Experimental results show that our models are on par with human performance on these tasks, while outperforming baselines based on solution length or readability

    James and Dewey on Abstraction

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    A critical Analysis of ChatGPT's Potential and Pitfallss for Business Use Cases

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    This literature review explores the impact of ChatGPT on businesses. ChatGPT has been widely adopted in various companies to generate content. This review examines the existing research on the benefits and drawbacks of ChatGPT in business settings, including its effect on business management and operations. Through an analysis of articles and academic literature, we evaluate the impact of ChatGPT on businesses and provide insights into its potential applications. The findings suggest that ChatGPT can significantly improve sales and production processes. Additionally, the review highlights the need for further research to address the limitations and challenges associated with ChatGPT. Overall, this literature review provides a comprehensive analysis of the impact of ChatGPT on businesses and highlights the opportunities and challenges associated with its adoption

    On the Roles of External Knowledge Representations in Assessment Design

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    Cognitive load theory, educational research, and instructional design: some food for thought

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    Cognitive load is a theoretical notion with an increasingly central role in the educational research literature. The basic idea of cognitive load theory is that cognitive capacity in working memory is limited, so that if a learning task requires too much capacity, learning will be hampered. The recommended remedy is to design instructional systems that optimize the use of working memory capacity and avoid cognitive overload. Cognitive load theory has advanced educational research considerably and has been used to explain a large set of experimental findings. This article sets out to explore the open questions and the boundaries of cognitive load theory by identifying a number of problematic conceptual, methodological and application-related issues. It concludes by presenting a research agenda for future studies of cognitive load

    Uses and applications of artificial intelligence in manufacturing

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    The purpose of the THESIS is to provide engineers and personnels with a overview of the concepts that underline Artificial Intelligence and Expert Systems. Artificial Intelligence is concerned with the developments of theories and techniques required to provide a computational engine with the abilities to perceive, think and act, in an intelligent manner in a complex environment. Expert system is branch of Artificial Intelligence where the methods of reasoning emulate those of human experts. Artificial Intelligence derives it\u27s power from its ability to represent complex forms of knowledge, some of it common sense, heuristic and symbolic, and the ability to apply the knowledge in searching for solutions. The Thesis will review : The components of an intelligent system, The basics of knowledge representation, Search based problem solving methods, Expert system technologies, Uses and applications of AI in various manufacturing areas like Design, Process Planning, Production Management, Energy Management, Quality Assurance, Manufacturing Simulation, Robotics, Machine Vision etc. Prime objectives of the Thesis are to understand the basic concepts underlying Artificial Intelligence and be able to identify where the technology may be applied in the field of Manufacturing Engineering
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