الفهرس | Only 14 pages are availabe for public view |
Abstract This Thesis aims to improve analysis big data using mapreduce (hadoop) which use two main functions: map function and reduce function. Mapreduce can handle and do processes on big data such as storing, capturing, manipulating and many processes which traditional data base tools cannot. Mapreduce hadoop is open source software framework for sorting, processing and analysis which distributed, fault tolerance, availability and reliability. Using hadoop in many fields such as text mining and marketing (association rules). We are representing mapreduce algorithm with association rule algorithms finally optimizing result using genetic algorithm. A major challenge for analysis and extracting strong association rules from large databases (big data) using mapreduce for implementing proposed system: combination of three algorithms (mapreduce algorithm then association rule algorithms finally genetic algorithm) for generating new strong association rules which help in making decisions. |