Artificial Intelligence

    

Keyword Extraction with Table based KNN Variants

Authors: Taeho Jo

In this research, we propose and apply the table based KNN variants to the keyword extraction. The initial KNN version was previously modified into the table-based version and applied by mapping the keyword extraction into a binary classification. In this research, we mentioned the three KNN variants, in case of the numerical vector-based versions: one where the selected nearest neighbors are discriminated by their similarities, one where the attributes are discriminated by their correlations with the categories, and one where the training examples are discriminated by their credits. In this research, the three KNN variants are modified into the table- based versions, as well as the initial KNN version. The goal of this research is to improve the keyword extraction performanceby modifying them so.

Comments: 6 Pages.

Download: PDF

Submission history

[v1] 2026-01-27 00:34:30

Unique-IP document downloads: 102 times

Vixra.org is a pre-print repository rather than a journal. Articles hosted may not yet have been verified by peer-review and should be treated as preliminary. In particular, anything that appears to include financial or legal advice or proposed medical treatments should be treated with due caution. Vixra.org will not be responsible for any consequences of actions that result from any form of use of any documents on this website.

Add your own feedback and questions here:
You are equally welcome to be positive or negative about any paper but please be polite. If you are being critical you must mention at least one specific error, otherwise your comment will be deleted as unhelpful.

comments powered by Disqus