文章基本信息

标题：Big Data Retrieval: Taxonomy, Techniques and Feature Analysis
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作者：Israr Haneef ; Ehsan Ullah Munir ; Ghazia Qaiser 等
期刊名称：International Journal of Computer Science and Network Security
印刷版ISSN：1738-7906
出版年度：2018
卷号：18
期号：11
页码：55-59
出版社：International Journal of Computer Science and Network Security
摘要：In recent years, Information retrieval in big data has become more popular research field. Big data is collection of heterogeneous structured and unstructured data. The heterogeneity, volume and the speed in which data is generating makes it problematic to process and analyze big data. The traditional databases system, warehouses and analyses tools are failed to process this type of data. Big data in IR system is an emerging approach not just because of the volume of data but also unstructured type of nature. The data that is related to the user query must be retrieved in IR system. Big data includes all type data like images, audio and video and from all resources like database, social media posts, and web blogs. In this paper, authors tried to provide and broad overview on different revival techniques in big data with the help of categorization of different techniques from existing literature.
关键词：Big data; information retrieval; Feature analysis; retrieval techniques.