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Collaborative Filtering Recommender System for Financial Market

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Author(s): F.R.Sayyed, | R.V.Argiddi | S.S.Apte

Journal: International Journal of Engineering and Advanced Technology
ISSN 2249-8958

Volume: 2;
Issue: 6;
Start page: 389;
Date: 2013;
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Keywords: Collaborative Filtering | Financial Markets | Recommender System | Stocks Predictions.

ABSTRACT
Recommender systems suggest items to users by utilizing the techniques of Collaborative filtering based on historical records of items that users have purchased. Recommender systems make use of data mining techniques to determine the similarity among a huge collection of data items, by analyzing historical user data and then extracting hidden useful information or patterns. Collaborative filtering aims at finding the relationships among the new individuals and the existing data items in order to further determine the similarity and provide recommendations. In this paper, a Collaborative Filtering Recommender System is proposed which can be used for financial markets such as stock exchanges for future predictions.
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