Improving News Headline Text Generation Quality Through Frequent POS-Tag Patterns Analysis

This repository contains the code and data for the research paper "Improving News Headline Text Generation Quality Through Frequent POS-Tag Patterns Analysis". The paper presents a method for enhancing the quality of generated news headlines by analyzing the frequent POS-tag patterns in the training data and integrating them into the text generation model.

The repository includes the following components:

• data: Preprocessed training data used in the paper
• models: Source code for the text generation model, implemented in Python with PyTorch
• HPPE: Headline post-processing script for selecting generated headlines based on POS Tags matching.
• examples: Generated headlines and their corresponding POS-tag patterns

Executing Code

Cloning repository

• Clone this repository using following command:

git clone https://github.com/saifhassan/Headline-Generationg-using-POS.git

Downloading Dataset

The dataset which is used for Urdu News Headlines is taken from here. There are two ways to produce same results as mentioned in paper.

1. First, Download original dataset and process through Notebook.

OR

2. Another way is, we have already pre-processed dataset. You can download pre-processed dataset with POS Tags from here

3. Put downloaded dataset in data folder.

Running notebook

• Go to HPPE directory within main directory and open notebook using terminal and execute code.

The repository is open-source and welcomes contributions from the community.

Note: This repository is provided for research purposes only and is not intended for commercial use.