e-ISSN : 0975-3397
Print ISSN : 2229-5631
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ABSTRACT

Title : Text Analytics to Data Warehousing
Authors : Kalli Srinivasa Nageswara Prasad, S. Ramakrishna
Keywords : Information Extraction (IE); Entity; Semantics; Natural Language Processing (NLP); Parsing.
Issue Date : September 2010
Abstract :
Information hidden or stored in unstructured data can play a critical role in making decisions, understanding and conducting other business functions. Integrating data stored in both structured and unstructured formats can add significant value to an organization. With the extent of development happening in Text Mining and technologies to deal with unstructured and semi structured data like XML and MML(Mining Markup Language) to extract and analyze data, text analytics has evolved to handle unstructured data to helps unlock and predict business results via Business Intelligence and Data Warehousing. Text mining involves dealing with texts in documents and discovering hidden patterns, but Text Analytics enhances Information Retrieval in form of search and enabling clustering of results and more over Text Analytics is text mining and visualization. In this paper we would discuss on handling unstructured data that are in documents so that they fit into business applications like Data Warehouses for further analysis and it helps in the framework we have used for the solution.
Page(s) : 2201-2207
ISSN : 0975–3397
Source : Vol. 2, Issue.6

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