Document Relevance Filtering by Natural Language Processing and Machine Learning: A Multidisciplinary Case Study of Patents

The exponential growth of patent datasets poses a significant challenge in filtering relevant documents for research and innovation. Traditional semantic search methods based on keywords often fail to capture the complexity and variability in multidisciplinary terminology, leading to inefficiencies....

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Bibliographic Details

Published in:	Applied Sciences
Main Author:	Raj Bridgelall
Format:	Article
Language:	English
Published:	MDPI AG 2025-02-01
Subjects:	document search supervised machine learning unsupervised machine learning natural language processing latent Dirichlet allocation non-negative matrix factorization
Online Access:	https://www.mdpi.com/2076-3417/15/5/2357