Stock Market Recommendation System

The information system chosen for the project was a stock investment management website providing live prices, historical data, news articles, etc and also basic analysis and recommendations using data mining techniques. 1. Crawling and parsing Yahoo-Finance, Reuters and Twitter data (Java, twitter4j). 2. Web Interface using J2EE and Struts-2 framework. jQuery (highstocks lib) for showing technical charts. 3. Database integration, data cleaning, feature selection on the collected data and applying linear regression and classification algorithms : SVM, Naive Bayes to produce detailed analysis and recommendations.