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Theory And Applications For Advanced Text Mining

Theory And Applications For Advanced Text Mining

          
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About the Book

Due to the growth of computer technologies and web technologies, we can
easily collect and store large amounts of text data. We can believe that the data
include useful knowledge. Text mining, also referred to as text data mining,
roughly equivalent to text analytics, refers to the process of deriving high-quality
information from text. High-quality information is typically derived through the
devising of patterns and trends through means such as statistical pattern learning.
The purpose of Text Mining is to process unstructured information, extract
meaningful numeric indices from the text, and, thus, make the information
contained in the text accessible to the various data mining algorithms. Information
can be extracted to derive summaries for the words contained in the documents
or to compute summaries for the documents based on the words
contained in them. Hence, you can analyze words, clusters of words used in
documents, etc., or you could analyze documents and determine similarities
between them or how they are related to other variables of interest in the data
mining project. Text mining can help an organization derive potentially valuable
business insights from text-based content such as word documents, email and
postings on social media streams like Facebook, Twitter and LinkedIn. Mining
unstructured data with natural language processing (NLP), statistical modeling
and machine learning techniques can be challenging, however, because natural
language text is often inconsistent. It contains ambiguities caused by inconsistent
syntax and semantics, including slang, language speci c to vertical industries
and age groups, double entendres and sarcasm. Unstructured text is very
common, and in fact may represent the majority of information available to a
particular research or data mining project. Even if many important techniques
have been developed, the text mining research eld continues to expand for the
needs arising from various application elds. Text mining techniques have been
studied aggressively in order to extract the knowledge from the data since late
1990s. This book highlights the theory and applications of advanced text mining
techniques..


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Product Details
  • ISBN-13: 9781681173047
  • Publisher: Scitus Academics LLC
  • Binding: Hardback
  • No of Pages: 300
  • Width: 152.4 mm
  • ISBN-10: 1681173042
  • Publisher Date: 2016
  • Height: 229 mm
  • Weight: 0 gr

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