ukss 0.1.1

A library that extracts keywords and summarizes text

UKSS

Unsupervised Keyword Scoring System with PageRank Integration

UKSS (formerly UKSS-PI) is an unsupervised keyword scoring and text summarization library. It combines traditional statistical NLP methods with graph-based ranking to precisely identify and score relevant keywords from text—all without the need for labeled training data.

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📖 Working Method

UKSS relies on a powerful hybrid algorithm to score and extract the most significant keywords from any given text. It processes the text through three main scoring pipelines and fuses their results:

1. Term Frequency (TF) Scoring: Normalizes the frequency of a word relative to the maximum frequency of any word in the text.
2. Graph-Based PageRank Scoring: Builds a co-occurrence network graph using a defined window size and applies the PageRank algorithm to measure the centrality/importance of a word within the textual structure.
3. Dispersion Scoring (Gries' DP): Calculates how evenly a word is distributed across different segments of the text. Words that appear uniformly throughout the text are rewarded, ensuring keywords aren't just isolated to a single localized sentence.

The final score for each word is computed using a weighted combination of these algorithms. Additionally, UKSS uses the extracted top keywords to identify and extract the most important sentences, generating a high-quality summary.

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🚀 Installation

You can easily install ukss via pip:

pip install ukss

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⚡ Quick Start

import ukss
from ukss import UKSS_PI

text = """
The gym is a dedicated space for individuals to enhance their physical fitness, 
mental well-being, and personal health. Gyms offer a variety of equipment and 
facilities designed to cater to a wide range of fitness goals, from weightlifting 
and strength training to cardiovascular and flexibility exercises...
"""

# 1. Initialize the class with your text
analyzer = UKSS_PI(text=text)

# 2. Extract keywords and generate a summary
result = analyzer.get_keywords()

print("Top Keywords:", result["keywords"])
print("Generated Summary:", result["summary"])

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🛠️ API Reference

UKSS_PI Class

The main class used to analyze and process text.

__init__(self, text: str)

Initializes the UKSS_PI object and preprocesses the text (lemmatization, stop-word removal, POS filtering).

• Parameters:
  • text (str): The input text document to be analyzed.

get_keywords(self) -> dict

Extracts the top 3 keywords and generates a text summary based on those keywords.

• Returns: A dictionary containing:
  • "keywords" (list of str): The top 3 ranked keywords.
  • "summary" (str): A summary comprised of the most important sentences.

get_keyword_list(self) -> dict

Returns the complete list of processed words along with their final fused UKSS scores.

• Returns: A dictionary mapping words (str) to their computed scores (float).

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🤝 Contributing

Pull requests are welcome! For major changes, please open an issue first to discuss what you would like to change.

When contributing, please ensure:

• Tests are added or updated.
• Documentation is updated if functionality changes.

📚 References

Wang, J., Liu, J., & Wang, C. (2007). Keyword Extraction Based on PageRank. In: Zhou, ZH., Li, H., Yang, Q. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2007. Lecture Notes in Computer Science, vol 4426. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71701-0_95

📄 License

This project is licensed under the Apache 2.0 License.