Improving Anonymized Search Relevance with Natural Language Processing and Machine Learning

Users often sacrifice personal data for more relevant search results, presenting a problem to communities that desire both search anonymity and relevant results. To balance these priorities, this research examines the impact of using Siamese networks to extend word embeddings into document embedding...

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Bibliographic Details

Main Author:	Petrocelli, Niko A.
Format:	text
Published:	AFIT Scholar 2022
Subjects:	Natural language processing Search relevance Machine learning Siamese networks Computer Sciences
Online Access:	https://scholar.afit.edu/etd/5327 https://scholar.afit.edu/context/etd/article/6329/viewcontent/AFIT_ENG_MS_22_M_055_Petrocelli_N.pdf
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