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Keyword Extraction API

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Detail Description

Abstract

The Keyword Extraction API is an AI-powered service that automatically identifies important words and phrases from text documents using Natural Language Processing (NLP) techniques. By analyzing context, frequency, and semantic relationships, the system extracts meaningful keywords that summarize the core content. This service is useful for search engine optimization (SEO), content categorization, document indexing, and information retrieval.


Existing System

  1. Manual keyword identification
  2. Basic frequency-based methods with low accuracy
  3. Time-consuming for large volumes of text
  4. Inconsistent results due to human interpretation


Proposed System

  1. NLP-based keyword extraction using TF-IDF, RAKE, or transformer models
  2. Context-aware and accurate keyword identification
  3. Real-time API for content platforms and search systems
  4. Scalable processing for large datasets


Software Requirements

  1. Python
  2. Libraries: NLTK, spaCy, Scikit-learn, Transformers, NumPy, Pandas
  3. Jupyter Notebook / VS Code
  4. Flask or FastAPI for API deployment


Hardware Requirements

  1. Minimum 4 GB RAM (8 GB recommended for large datasets)
  2. Multi-core processor
  3. Stable internet connection for API integration
  4. Optional GPU for transformer-based models


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