Artificial Intelligence

    

Table based K Nearest Neighbor for Text Classification

Authors: Taeho Jo

This article proposes the modified KNN (K Nearest Neighbor) algorithm which receives a table as its input data and is applied tothe text categorization. The motivations of this research are the successful results from applying the table based algorithms to thetext categorizations in previous works and the expectation of synergy effect between the text categorization and the word categorization. In this research, we define the similarity metricbetween two tables representing texts, modify the KNN algorithm by replacing the exiting similarity metric by the proposed one, andapply it to the text categorization. The proposed KNN is empirically validated as the better approach in categorizing texts in newsarticles and opinions. In using the table based KNN algorithm, it is easier to trace results from categorizing texts.

Comments: 13 Pages.

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Submission history

[v1] 2024-05-31 02:38:19

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