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A Map-Reduce based Approach for Mining Group Stock Portfolio

Published: 07 October 2015 Publication History

Abstract

In this paper, the map-reduce technique is utilized for speeding up the mining process and derived as similar results as our previous approach. The chromosome representation consists of four parts that are a mapper number, grouping part, stock part and portfolio part. According to mapper number, chromosomes in population are divided into subsets and sent to respective mappers. Fitness evaluation and genetic operations are the same with our previous approach, and executed on reducers. The evolution process is repeated until reaching the terminal conditions. Experiments are conducted on a real dataset to show the performance of proposed approach.

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cover image ACM Other conferences
ASE BD&SI '15: Proceedings of the ASE BigData & SocialInformatics 2015
October 2015
381 pages
ISBN:9781450337359
DOI:10.1145/2818869
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Published: 07 October 2015

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Author Tags

  1. group stock portfolio
  2. grouping genetic algorithms
  3. grouping problems
  4. map-reduce
  5. stock portfolio optimization

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ASE BD&SI '15
ASE BD&SI '15: ASE BigData & SocialInformatics 2015
October 7 - 9, 2015
Kaohsiung, Taiwan

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