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keyword-mining

License: MIT Python 2.7

API - extract keywords from a text or a web page.

The algorithm extracts all nominal groups (candidate keywords) from the text and, for each one, attributes a score based on multiple parameters including the number of occurrences. The final list of keywords is composed of best-scored nominal groups.

Note

For the moment, this tool works only for English and French.

INSTALL AND RUN

REQUIREMENTS

This tool requires Python2.7 (not working for Python3).

WITH PIP

git clone https://github.com/AnthonySigogne/keyword-mining.git
cd keyword-mining
pip install -r requirements.txt

Then, run the tool :

FLASK_APP=index.py flask run

To run in debug mode, prepend FLASK_DEBUG=1 to the command :

FLASK_DEBUG=1 ... flask run

WITH DOCKER

To run the tool with Docker, you can use my DockerHub image : https://hub.docker.com/r/anthonysigogne/keyword-mining/

docker run -p 5000:5000 anthonysigogne/keyword-mining

Or, build yourself a Docker image :

git clone https://github.com/AnthonySigogne/keyword-mining.git
cd keyword-mining
docker build -t keyword-mining .

USAGE AND EXAMPLES

To list all services of API, type this endpoint in your web browser : http://localhost:5000/

FROM A TEXT

Index a web page through its URL.

  • URL

    /keywords_from_text

  • Method

    POST

  • Form Data Params

    Required:

    text=[string], the text to analyze

    Not required:

    hits=[int], limit number of keywords returned, 100 by default

  • Success Response

    • Code: 200
      Content:
      {
        "keywords": [
          "computer science PhD in applied Language",
          "PhD in Computer Science",
          "Creation of ergonomic websites",
          "Modern infrastructure with API",
          "Development of effective application",
          "experience of research laboratories",
          "projects for international clients",
          "Computer courses for individuals",
          ...
        ]
      }
      
  • Error Response

    • Code: 400 INVALID USAGE
  • Sample Call (with cURL)

    curl http://localhost:5000/keywords_from_text --data "text=True programming enthusiast, I quickly oriented to computer studies at the university, until a computer science PhD in applied Language Processing."
    

FROM AN URL

Query engine to find a list of relevant URLs. Return the sublist of matching URLs sorted by relevance, and the total of matching URLs, in JSON.

  • URL

    /search

  • Method

    POST

  • Form Data Params

    Required:

    url=[string], the url to analyze

    Not required:

    hits=[int], limit number of keywords returned, 100 by default

  • Success Response

    • Code: 200
      Content:
      {
        "keywords": [
          "computer science PhD in applied Language",
          "PhD in Computer Science",
          "Creation of ergonomic websites",
          "Modern infrastructure with API",
          "Development of effective application",
          "experience of research laboratories",
          "projects for international clients",
          "Computer courses for individuals",
          ...
        ]
      }
      
  • Error Response

    • Code: 400 INVALID USAGE
  • Sample Call (with cURL)

    curl http://localhost:5000/keywords_from_url --data "url=https://www.byprog.com/en"
    

FUTURE FEATURES

  • more languages
  • compatibility with Python3
  • filter bad keywords (verbs,...)

LICENCE

MIT