Generating Recommendations for Stock Market Using Collaborative Filtering

Recommendation systems apply different data mining techniques on data and try to find the similarity among a huge collection of data items. These systems work on the technique of collaborative filtering, which makes use of the past users’ data and gives recommendations to new users. Collaborative filtering technique can be applied to various application areas where there is similarity between the past users’ behaviour pattern and the current new users. The recommendation system for stock markets described in this paper works using the technique of collaborative filtering and makes use of Apache Mahout to generate recommendations for new users.