keywords

Get Started

for Rust

Installation

cargo add keyword-tools

Usage

use keyword_tools::{extract_keywords, load_keywords, load_keywords_from_rsc, Language};
let keywords = load_keywords();
// keywords = load_keywords_from_rsc(PATH_TO_JSON_FILE);
let text = "After the introduction of Large Language Models (LLMs), there have been substantial improvements in the performance of Natural Language Generation (NLG) tasks, including Text Summarization and Machine Translation.";

let extracted_kwds = extract_keywords(text, Language::English);

for Python

Installation

pip install git+ssh://git@github.com/akitenkrad/keywords.git

Usage

• get keywords

  from keywords import Keyword
  keywords: list[Keyword] = Keyword.load_keywords()

• extract keywords from texts

  from keywords import Keyword, extract_keywords
  keywords: list[Keyword] = Keyword.load_keywords()
  extracted_kws = extract_keywords(text, keywords, remove_stopwords=True)

• calculate metrics

  • specialization factor

    from keywords.metrics import SpecializationFactor
    factors = SpecializationFactor.calculate(texts)

Use your keywords

If you want to use your own keywords, just create your a JSON file according to the following instructions:

[
  {
    "category": "Topic",
    "language": "English",
    "word": "Edge AI",
    "alias": "Edge AI",
    "score": 10
  },
]

Then, load the keywords.

let kws = load_keywords_from_rsc("PATH_TO_YOUR JSON_FILE")

The JSON file defines a collection of topic entries used by the crate. Each entry is an object with the following fields:

category

Specifies the category of the entry.
Available options:

• Topic
• Security
• ComputerVision
• Organization
• MachineLearning
• Item
• NaturalLanguageProcessing

Language

Indicates the language of the entry.
Available options:

• Japanese
• English

word

The main term or keyword for the topic.

alias

An alternative name or synonym for the word.

score

A numerical value representing the importance or relevance of the topic. Available options: Any integer or floating-point number (e.g., 1, 10). Higher values may indicate greater importance.