A Text Information Retrieval Technique for Big Data Using Map Reduce
Big data is a heterogeneous collection of both structured and unstructured data of larger volumes. The volume and the heterogeneity of data and the speed at which it is generated, makes it difficult for the present computing infrastructure to manage Big Data .The traditional data management, warehousing and analysis systems fall short of tools for analyzing enormous data. The proposed methodology is the information retrieval mechanism to improve text information retrieval using map reduce technique. This reorganization produces significant gains in performance by reducing the number of accesses made to the data file. It is examined the impact of other factors on text retrieval is also experiment in this work namely Heterogeneity, Scale, Data Representation and Complexity. A major motivation for reorganizing the structured data retrieval is to allow the application of iteration aware perfecting.
Keywords: Big Data Analysis, Big Data Management, Text Retrieval, Map Reduce, HDFS.
Volume: 6 | Issue: Special Issue on Advances in Computer Science and Engineering and Workshop on Big Data Analytics Editors: Dr.S.B. Kulkarni, Dr.U.P. Kulkarni, Dr.S.M. Joshi and J.V. Vadavi
Issue Date: October , 2016