Machine learning approach for text and document mining

TL;DR

This paper explores machine learning techniques, specifically KNN, for text categorization and document retrieval, highlighting their effectiveness in classifying documents into predefined categories.

Contribution

It introduces a KNN-based approach for text categorization and document retrieval, combining information retrieval tools with machine learning methods.

Findings

KNN effectively classifies documents into categories.

The approach improves document retrieval relevance.

The method demonstrates practical applicability in text mining.

Abstract

Text Categorization (TC), also known as Text Classification, is the task of automatically classifying a set of text documents into different categories from a predefined set. If a document belongs to exactly one of the categories, it is a single-label classification task; otherwise, it is a multi-label classification task. TC uses several tools from Information Retrieval (IR) and Machine Learning (ML) and has received much attention in the last years from both researchers in the academia and industry developers. In this paper, we first categorize the documents using KNN based machine learning approach and then return the most relevant documents.