# Web-page-classification

**Repository Path**: bit212/Web-page-classification

## Basic Information

- **Project Name**: Web-page-classification
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2025-01-07
- **Last Updated**: 2025-01-07

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Topical Web-page classification of the DMOZ Dataset

### [Read the paper](paper.pdf)

This repository contains all scripts associated with my research on topical Web-page classification. You can read the full paper describing the task, experiments, and results [here](paper.pdf).

## Abstract
Multi-class topical web-page classification is a difficult task with widespread application. Throughout this paper, I analyze the performance of well-studied techniques on two different representations of web-pages: hand-written meta-descriptions and on-page text content. I acquired all of the training labels and website descriptions from the DMOZ dataset and all of the on-page content from scraping the actual web-pages. I achieved 74.035% and 79.121% accuracy for on-page content and website descriptions respectively in a 16-way classification task with a 42.032% most frequently tagged baseline accuracy.