Extracting useful insights by mining IMDb datasets

CSCI 5502 Coursework project on applying data mining techniques on IMDb datasets

#Contributors Bader Alshemaimri

Saish Redkar

Siddharth Pant

Sneha Parmar

##Methodology

Download IMDb text files from http://www.imdb.com/interfaces
Extract the text files into MySQL Database on local machine using IMDbPy.
Identify the key tables and attributes and explore relationships between tables.
Export data from the tables into CSV files.
Use tools like Weka and RapidMiner to apply data mining techniques on the dataset.
Use tools like Tableau to visualize the patterns and trends from our dataset.

##Data and Tools

Name		Name	Last commit message	Last commit date
Latest commit History 95 Commits
IMDbPy		IMDbPy
["DBFiles"]		["DBFiles"]
DB_Setup.md		DB_Setup.md
Differences-Bader.txt		Differences-Bader.txt
ER diagram_Bader		ER diagram_Bader
MySQL_Commands.md		MySQL_Commands.md
README.md		README.md
Relations and Queries.txt		Relations and Queries.txt
Setup.png		Setup.png
Table_Relations		Table_Relations
Useful tables and attributes		Useful tables and attributes
cleanBudgetAndGross.py		cleanBudgetAndGross.py
dm_imdb_er dgm.pdf		dm_imdb_er dgm.pdf
erdiagrammodified.png		erdiagrammodified.png
getAllMovieDetails.py		getAllMovieDetails.py
getAllMovieRatings.py		getAllMovieRatings.py
keyword_backup.sql		keyword_backup.sql
mostOccurringWords_filterStopWordsNLTK.py		mostOccurringWords_filterStopWordsNLTK.py
removeQuotes2.py		removeQuotes2.py

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