Text Analytics 24 Success Secrets - 24 Most Asked Questions On Text Analytics - What You Need To Know

Business & Finance
Cover of the book Text Analytics 24 Success Secrets - 24 Most Asked Questions On Text Analytics - What You Need To Know by Benjamin Rosales, Emereo Publishing
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Author: Benjamin Rosales ISBN: 9781488535383
Publisher: Emereo Publishing Publication: February 3, 2014
Imprint: Emereo Publishing Language: English
Author: Benjamin Rosales
ISBN: 9781488535383
Publisher: Emereo Publishing
Publication: February 3, 2014
Imprint: Emereo Publishing
Language: English
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Text mining', as well referenced to like written material information mining, approximately equal to '#Text excavating and written material analytics|text analytics', alludes to the procedure of deriving high-quality data as of Plain text. High-quality data is characteristically obtained via the conceiving of models and tendencies via intents such like design recognition|statistical design educating. Text excavating normally includes the procedure of arranging the input written material (usually parsing, alongside with the extension of a few obtained lexical attributes and the deletion of other ones, and following introduction in to a database), deriving models inside the organized information, and eventually assessment and explanation of the yield. 'high quality' in written material excavating normally alludes to a few amalgamation of relevancy (information retrieval)|relevance, freshness (patent)|novelty, and interestingness.

There has never been a Text Analytics Guide like this.

It contains 24 answers, much more than you can imagine; comprehensive answers and extensive details and references, with insights that have never before been offered in print. Get the information you need--fast! This all-embracing guide offers a thorough view of key knowledge and detailed insight. This Guide introduces what you want to know about Text Analytics.

A quick look inside of some of the subjects covered: Intelligent text analysis - Commercial, Analytics - Analytics vs. analysis, Data mining Commercial data-mining software and applications, Text mining - Commercial, Text mining - History, Semantic analytics, Data analysis, Angoss - Services, Sentiment analysis, Unstructured information - Dealing with unstructured data, SPSS Modeler, Intelligent text analysis - Text mining and text analytics, Customer intelligence Example sources of data for CI, Data extraction, Predictive analytics Technology and big data influences, and much more...

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Text mining', as well referenced to like written material information mining, approximately equal to '#Text excavating and written material analytics|text analytics', alludes to the procedure of deriving high-quality data as of Plain text. High-quality data is characteristically obtained via the conceiving of models and tendencies via intents such like design recognition|statistical design educating. Text excavating normally includes the procedure of arranging the input written material (usually parsing, alongside with the extension of a few obtained lexical attributes and the deletion of other ones, and following introduction in to a database), deriving models inside the organized information, and eventually assessment and explanation of the yield. 'high quality' in written material excavating normally alludes to a few amalgamation of relevancy (information retrieval)|relevance, freshness (patent)|novelty, and interestingness.

There has never been a Text Analytics Guide like this.

It contains 24 answers, much more than you can imagine; comprehensive answers and extensive details and references, with insights that have never before been offered in print. Get the information you need--fast! This all-embracing guide offers a thorough view of key knowledge and detailed insight. This Guide introduces what you want to know about Text Analytics.

A quick look inside of some of the subjects covered: Intelligent text analysis - Commercial, Analytics - Analytics vs. analysis, Data mining Commercial data-mining software and applications, Text mining - Commercial, Text mining - History, Semantic analytics, Data analysis, Angoss - Services, Sentiment analysis, Unstructured information - Dealing with unstructured data, SPSS Modeler, Intelligent text analysis - Text mining and text analytics, Customer intelligence Example sources of data for CI, Data extraction, Predictive analytics Technology and big data influences, and much more...

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