This is a small project to find similar terms in corpus of documents.
For the project I have used some tags based on news articles. These tags are extracted from various news aggregation methods. You can easily create custom dataset using the
How to Use
Clone the Repository:
git clone https://github.com/OmkarPathak/A-Simple-Note-Taking-Web-App.git
Install the dependencies by simply executing:
pip3 install -r requirements.txt
Run the Term Similarity:
python3 find_word_similarity.py <word_to_search_for_similar_words>
# Suppose you have to find the similar terms for the word 'machine learning' # Then run the following command $python3 find_word_similarity.py 'machine learning' # Output would be distance name 0 0.000000 Machine Learning 1 0.000000 machine learning 2 1.213289 software 3 1.213289 Software 4 1.216590 Artificial Intelligence 5 1.216590 artificial intelligence 6 1.219796 predictive analytics 7 1.224047 data & analytics 8 1.224047 data analytics 9 1.241769 big data analytics # As we can see in the above output 'machine learning' is closely related to # terms or words as 'big data' and 'artificial intelligence'
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