Investigating Machine Learning Clustering Methods to Replicate the Human Idea of Structure to Documents
Anyone trying to maintain a set of text documents in an information retrieval system will run into problems keeping it relevant and up to date as the amount of data increases. This thesis investigates how a collection of documents can be clustered in a way that resembles how a human would organize it. It also assesses how difficult it is to implement this into an existing information retrieval sys
