Call For Paper Volume:4 Issue:8 Aug'2017 |

Text Analytics for Big Data

Publication Date : 31/03/2015



Author(s) :

Dr Sharvari Tamane.


Volume/Issue :
Volume 2
,
Issue 3
(03 - 2015)



Abstract :

Most of the data used in various application areas like government, business and research is available in the form of text and therefore it is the requirement of these applications that it should derive high quality information by converting text into data for analysis purpose. The process of deriving high-quality information from the text is known as text analytics. Text analytics techniques represent knowledge, facts, business rules and relationships which are otherwise available in textual form incomprehensible for automatic processing. This paper mainly explores on how the different types of unstructured data are analyzed to get real meaning from data and which different text analytics tools are available for big data infrastructure. Routinely statistical and natural language processing techniques are used in text analytics to retrieve information from unstructured data. The idea behind this type of analytics is to determine who did what to whom, when, where, how and why. This information is then combined with structured information available in the data warehouse using various tools to gather further insight. At the end an overview of some of the players of this market is provided.


No. of Downloads :

47


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Text Analytics for Big Data

March 10, 2015