文章基本信息

标题：Text Analytics to Data Warehousing
本地全文：下载
作者：Kalli Srinivasa Nageswara Prasad ; S. Ramakrishna
期刊名称：International Journal on Computer Science and Engineering
印刷版ISSN：2229-5631
电子版ISSN：0975-3397
出版年度：2010
卷号：2
期号：6
页码：2201-2207
出版社：Engg Journals Publications
摘要：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.
关键词：Information Extraction (IE); Entity; Semantics; Natural Language Processing (NLP); Parsing.