Theory and Applications for Advanced Text Mining (Shigeaki Sakurai)

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Theory and Applications for Advanced Text Mining (Shigeaki Sakurai)

The development of computer and online technologies has made it simple for us to gather and store vast amounts of text data. We can assume that the data include knowledge that is beneficial. Since the late 1990s, text mining techniques have been actively researched in an effort to extract knowledge from the data.

Despite the fact that many significant techniques have been created, the area of text mining research is still expanding to meet the demands of diverse application fields.

Text mining is a technique used to process unstructured data, extract useful numerical indices from the text, and then make the data accessible to other data mining algorithms. Information can be gathered to create summaries based on the terms found in the texts or to compute summaries based only on those words.

As a result, you can examine terms, word groups found in documents, etc., or you can examine documents to see if there are any similarities between them or how they relate to other variables that the data mining project is interested in.

Nine chapters in this book introduce sophisticated text mining techniques. They include a range of methods, including relation extraction and language with few resources. This book, in my opinion, will contribute fresh knowledge to the field of text mining and assist many readers in establishing new research areas.

Text-based content, such as word documents, emails, and postings on social media channels like Facebook, Twitter, and LinkedIn, can be mined for potentially useful business insights.

However, because natural language text is frequently inconsistent, mining unstructured data with natural language processing (NLP), statistical modeling, and machine learning approaches can be difficult. It includes slang, terminology particular to certain industries and age groups, double entendres, and sarcasm, as well as misunderstandings brought on by inconsistent syntax and semantics.

Unstructured text is quite prevalent and may even make up the majority of the data that a research or data mining project has access to. Despite the fact that many significant techniques have been created, the area of text mining research is still expanding to meet the demands of diverse application fields.

Ebook Details

Published Date / Year
(November 21, 2012)
Attribution 3.0 Unported (CC BY 3.0)
218 pages
eBook Format
PDF files

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