Date of Award
5-2024
Document Type
Thesis
Degree Name
Master of Science (MS)
Department
Electrical Engineering and Computer Science
First Advisor
Thomas C. Eskridge
Second Advisor
Luis Daniel Otero
Third Advisor
Troy R. Weekes
Fourth Advisor
Brian A. Lail
Abstract
This study compares the traditional search methods, which is to search from video recordings of the meetings by moving the slider back and forth or by keyword search in transcripts versus integrated AI video plus transcript search. Based on the previous test results, we introduced some human-centric design features to the AI and built a new enhanced AI search tool for information retrieval. For search technique efficiency testing, the method had two set of experiments. The first results of the experiment showed that AI-based search algorithms were more accurate and faster than conventional search approaches. Participants were also happier with the AI-powered search experience, praising the system’s ability to find relevant material and make targeted recommendations quickly. The second experiment showed what features, if used, can improve the information retrieval process. In summary, this study offers useful insights into the relative effectiveness of conventional search methods, artificial intelligence (AI) search, and advanced AI search strategies. The findings contribute to the continuing discussion about improving information retrieval systems and the possible uses of artificial intelligence to enhance the search for fast, useful, and user-friendly information Retrieval.
Recommended Citation
Ghadge, Srushti Nitin, "AI-Powered Information Retrieval in Meeting Records and Transcripts Enhancing Efficiency and User Experience" (2024). Theses and Dissertations. 1439.
https://repository.fit.edu/etd/1439
Included in
Anthropology Commons, Cognitive Science Commons, Communication Commons, Computer Engineering Commons, Organization Development Commons, Other Social and Behavioral Sciences Commons
Comments
Discover the forthcoming advancements in information retrieval through our latest study that compares traditional methods of search with AI-driven methods. Explore our advanced AI search tool designed to evaluate the factors that promote speed and user-friendliness in information retrieval. See the improved efficiency of enhanced AI search in comparison with traditional methods and existing AI search tools. This tool offers faster and more accurate results, along with a user-friendly experience that is greatly valued by users. Explore the profound impact of artificial intelligence on the search landscape, as it revolutionizes the process of finding information with greater effectiveness and efficiency.
Copyright held by author.