Giter VIP home page Giter VIP logo

api-sentiment's Introduction

Aspect based sentiment analysis with Tensorflow

The problem is treated in two phases :

  • Aspect extraction consists of extracting and classifying aspect targets in the review
  • Sentiment analysis consists of assigning a tonality (negative, neutral, positive) to each extracted aspect target

Install and api launching

pip install -r requirements.txt
python api.py
curl --request GET --url http://localhost:9090/api-sentiment-1/doc/

Aspect extraction

  1. Build vocab from the data according to the config in sequence_tagging/model/config.py.
python sequence_tagging/build_data.py
  1. Train the model with
python sequence_tagging/train.py
  1. Evaluate and interact with the model with
python sequence_tagging/evaluate.py

Sentiment analysis

Train/test a model according to the config in mem_absa/config_mem.py

python mem_absa/train_test.py --show True

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.