Text Summarization

Implementing Sequence-to-Sequence model with LSTM and Attention Mechanism in Python for Text Summarization Problem.

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This is a NLP project for Text Summarization which is built with Flask(RESTapi) and deployed on Heroku(PaaS) using NLTK for summarizing text applied attention mechanism.

Requirements :

• Flask==2.0.2
• h5py==3.1.0
• joblib==1.1.0
• keras==2.6.0
• Keras-Preprocessing==1.1.2
• matplotlib==3.3.4
• nltk==3.6.7
• numpy==1.19.5
• pandas==1.1.5
• scikit-learn==0.24.2
• scipy==1.5.4
• seaborn==0.11.2
• sklearn==0.0
• tensorboard==2.6.0
• tensorboard-data-server==0.6.1
• tensorflow==2.6.2
• tensorflow-estimator==2.6.0
• tokenizers==0.10.3

Code Demo

Model Training

Layer Architecture

Train & Test

Installation

Make sure you have Python 3.6+ and pip (Windows, Linux) installed.

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Attention Catagories :

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References :

• https://link.springer.com/chapter/10.1007/978-3-030-30952-7_29
• https://towardsdatascience.com/lets-give-some-attention-to-summarising-texts-d0af2c4061d1
• https://web.stanford.edu/class/archive/cs/cs224n/cs224n.1174/reports/2749095.pdf
• https://iopscience.iop.org/article/10.1088/1742-6596/1848/1/012057/pdf
• https://medium.com/analytics-vidhya/seq2seq-abstractive-summarization-using-lstm-and-attention-mechanism-code-da2e9c439711
• https://www.hindawi.com/journals/mpe/2020/9365340/
• https://github.com/uzaymacar/attention-mechanisms

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Final Note :

• Bug fixing, Code error or Anything Raise issue🤚. If it any have.

• Happy to hear your sugesstions🤝 about this project.

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