CNN-based model to realize aspect extraction of restaurant reviews based on pre-trained word embeddings and part-of-speech tagging
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Updated
Jul 12, 2019 - Python
CNN-based model to realize aspect extraction of restaurant reviews based on pre-trained word embeddings and part-of-speech tagging
Project - Data Processing and Analysis in Python Course
Codes for the experiments in our EMNLP 2021 paper "Open Aspect Target Sentiment Classification with Natural Language Prompts"
Code for GenAug: Data Augmentation for Finetuning Text Generators.
🍕Recommend new restaurants to Yelp users, using ratings predicted from reviews.
writing style transfer using cycle gan
Analyzing yelp reviews using topic modelling and aspect mining
Application that predicts the number of stars that of a Yelp Review in realtime as a reviewer types it. Runs as a microservice-based application using Node.js, Python, and Docker. Displays results from Google Natural Language API and a custom trained classification models.
Recurrent Capsule Network for Text Classification
DL, ML, and Rule based approaches for Sentiment analysis
Our goal in this group project is to apply NLP and other features from Yelp reviews into a model that outputs a new 5-star-rating, so that there is less discrepancy between reviews and star ratings. In order to make our model more robust, we will also incorporate new user star-ratings based on reviews read (meaning that someone who did not write…
Analyzing yelp dataset ==> https://www.yelp.com/dataset_challenge
Public Project for the Research Seminar in Data Science
Topic modeling and sentiment analysis on Yelp's reviews using NLTK, sklearn, gesim, LdaMallet, and vaderSentiment libraries.
Big Data coursework using Hadoop/Spark, and concepts of mapreduce, graph theory, text mining, machine learning, etc.
A minimal Flask API to generate random lunch reviews
USC DSCI 553 - Foundations & Applications of Data Mining - Spring 2024 - Prof. Wei-Min Shen
A light-weight PHP Client for Yelp Fusion API
Project for the Big Data Course as part of 5th semester.
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