This project crawl the dataset from Korean movie script description and review web service.
This dataset selected because movies have variety of genres which describe different types of situatons. Given the dataset word embedding are implemented using word2vec language model.
Crawling and data storage -> Text processing (removing stop words) -> Dataset one-hot vector encoding -> Neural Network module -> training NN -> resulted embedding -> statistics and visualization