An Association Rule Mining Based Stock Market Recommender System

Paranjape-Voditel, Preeti; Deshpande, Umesh

doi:10.1109/eait.2011.90

Cited by 8 publications

(1 citation statement)

References 2 publications

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“…It can be characterized as an indication of capital interest of a man or an undertaking in an organization or a restricted risk organization [4]. Stock costs rely on upon different components, the imperative ones being the market sentiment, performance of the industry, earning results and projected earnings, takeover or merger, introduction of a new product or introduction of an existing product into new markets, share buy-back, announcements of dividends or bonuses, addition or removal from the index [5]. Stock market prediction has been a region of extraordinary enthusiasm because of the capability of getting an exceptional yield on the put cash in a brief timeframe [6].…”

Section: Introductionmentioning

confidence: 99%

Performance Evaluation of Association Rule Mining with Enhanced Apriori Algorithm Incorporated with Artificial Bee Colony Optimization Algorithm

Selvanambi¹,

Jaisankar²

2017

IJIES

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Abstract:In data mining, association rules are produced in view of solid relations and regularities existing among the variables in extensive exchanges. These association rules go for extricating connections, frequent patterns and associations among the item sets in exchanges. Association rules are connected for use in different zones, for example, media transmission, hazard administration and so forth. One such territory where the association rules are vital is the stock market. In stock marketing, picking the right stock relies on upon the genuine stock quality and the capacity to pick the stock is urgent as it impacts the profit of investors. In this work, the proposed technique develops a novel and effective way to deal with producing optimal stock rules to help in the stock market prediction by utilizing Enhanced Apriori algorithm and Artificial Bee Colony Optimization (ABC) algorithm. In the result profit of PP, EMA, ROC and RSI for min-support 3, 4, 5 and 6 individually in rule mining for HCL stock market dataset is appeared with correlation of GA-Apriori algorithm, AGA-Enhanced Apriori algorithm and ABC-Enhanced Apriori algorithm. From this Artificial Bee Colony (ABC) optimization algorithm is performed when contrasting and different strategies and grant that strong association rules to be produced.

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Section: Introductionmentioning

confidence: 99%