Open AccessSearching Big Data via cyclic groups
Author(s) -
Tımur Karacay
Publication year - 2017
Publication title -
global journal of computer sciences
Language(s) - English
Resource type - Journals
ISSN - 2301-2587
DOI - 10.18844/gjcs.v6i2.1475
Subject(s) - big data , partition (number theory) , task (project management) , computer science , dual (grammatical number) , group (periodic table) , mathematics , combinatorics , data mining , chemistry , engineering , art , literature , systems engineering , organic chemistry
We look up for a certain information in big data. To achieve this task we first endow the big data with a group structure and partition it to it’s cyclic subgroups. We devise a method to search the whole big data starting from the smallest subroup through the largest one. Our method eventually exhausts the whole big data.
Keywords: BigData, topological groups, dual groups, linear search.