Text Analytics for Business Decisions A Case Study Approach.

This book helps for business analysts who wish to increase their skills in extracting answers for text data in order to support business decision making. --

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Fortino, Andres
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Bloomfield : Mercury Learning & Information, 2021.
Temas:
Data mining.
Text processing (Computer science)
Business > Decision making > Data processing.
Exploration de données (Informatique)
Traitement de texte.
Business > Decision making > Data processing
Data mining
Acceso en línea:Texto completo

MARC

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029 1 |a AU@  |b 000072106314 
035 |a (OCoLC)1259323033  |z (OCoLC)1257705396  |z (OCoLC)1258217017 
050 1 4 |a QA76.73.P98  |b .F67 2021 
082 0 4 |a 005.133  |2 23 
049 |a UAMI 
100 1 |a Fortino, Andres. 
245 1 0 |a Text Analytics for Business Decisions  |h [electronic resource] :  |b A Case Study Approach. 
260 |a Bloomfield :  |b Mercury Learning & Information,  |c 2021. 
300 |a 1 online resource (332 p.) 
500 |a Description based upon print version of record. 
505 0 |a Intro -- Contents -- Preface -- On the Companion Files -- Acknowledgements -- Chapter 1 : Framing Analytical Questions -- Data is the New Oil -- The World of the Business Data Analyst -- How Does Data Analysis Relate to Decision Making? -- How Do We Frame Analytical Questions? -- What are the Characteristics of Well-framed Analytical Questions? -- Exercise 1.1 -- Case Study Using Dataset K: Titanic Disaster -- What are Some Examples of Text-Based Analytical Questions? -- Additional Case Study Using Dataset J: Remote Learning Student Survey -- References -- Chapter 2 : Analytical Tool Sets 
505 8 |a Tool Sets for Text Analytics -- Excel -- Microsoft Word -- Adobe Acrobat -- SAS JMP -- R and RStudio -- Voyant -- Java -- Stanford Named Entity Recognizer (NER) -- Topic Modeling Tool -- References -- Chapter 3 : Text Data Sources and Formats -- Sources and Formats of Text Data -- Social Media Data -- Customer opinion data from commercial sites -- Email -- Documents -- Surveys -- Websites -- Chapter 4 : Preparing the Data File -- What is Data Shaping? -- The Flat File Format -- Shaping the Text Variable in a Table -- Bag-of-Words Representation -- Single Text Files 
505 8 |a Exercise 4.1 -- Case Study Using Dataset L: Resumes -- Exercise 4.2 -- Case Study Using Dataset D: Occupation Descriptions -- Additional Exercise 4.3 -- Case Study Using Dataset I: NAICS Codes -- Aggregating Across Rows and Columns -- Exercise 4.4 -- Case Study Using Dataset D: Occupation Descriptions -- Additional Advanced Exercise 4.5 -- Case Study Using Dataset E: Large Data Files -- Additional Advanced Exercise 4.6 -- Case Study Using Dataset F: The Federalist Papers -- References -- Chapter 5 : Word Frequency Analysis -- What is Word Frequency Analysis? 
505 8 |a How Does It Apply to Text Business Data Analysis? -- Exercise 5.1 -- Case Study Using Dataset A: Training Survey -- Exercise 5.2 -- Case Study Using Dataset D: Job Descriptions -- Exercise 5.3 -- Case Study Using Dataset C: Product Reviews -- Additional Exercise 5.4 -- Case Study Using Dataset B: Consumer Complaints -- Chapter 6 : Keyword Analysis -- Exercise 6.1 -- Case Study Using Dataset D: Resume and Job Description -- Exercise 6.2 -- Case Study Using Dataset G: University Curriculum -- Exercise 6.3 -- Case Study Using Dataset C: Product Reviews 
505 8 |a Additional Exercise 6.4 -- Case Study Using Dataset B: Customer Complaints -- Chapter 7 : Sentiment Analysis -- What is Sentiment Analysis? -- Exercise 7.1 -- Case Study Using Dataset C: Product Reviews -- Rubbermaid -- Exercise 7.2 -- Case Study Using Dataset C: Product Reviews-Windex -- Exercise 7.3 -- Case Study Using Dataset C: Product Reviews-Both Brands -- Chapter 8 : Visualizing Text Data -- What Is Data Visualization Used For? -- Exercise 8.1 -- Case Study Using Dataset A: Training Survey -- Exercise 8.2 -- Case Study Using Dataset B: Consumer Complaints 
505 8 |a Exercise 8.3 -- Case Study Using Dataset C: Product Reviews 
520 |a This book helps for business analysts who wish to increase their skills in extracting answers for text data in order to support business decision making. --  |c Edited summary from book. 
590 |a ProQuest Ebook Central  |b Ebook Central Academic Complete 
650 0 |a Data mining. 
650 0 |a Text processing (Computer science) 
650 0 |a Business--Decision making--Data processing. 
650 6 |a Exploration de données (Informatique) 
650 6 |a Traitement de texte. 
650 7 |a Business  |x Decision making  |x Data processing  |2 fast 
650 7 |a Data mining  |2 fast 
650 7 |a Text processing (Computer science)  |2 fast 
758 |i has work:  |a Text Analytics for Business Decisions (Text)  |1 https://id.oclc.org/worldcat/entity/E39PCXJYDmcwg7RvvyPDBgMkjC  |4 https://id.oclc.org/worldcat/ontology/hasWork 
776 0 8 |i Print version:  |a Fortino, Andres  |t Text Analytics for Business Decisions  |d Bloomfield : Mercury Learning & Information,c2021 
856 4 0 |u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=6647712  |z Texto completo 
938 |a Askews and Holts Library Services  |b ASKH  |n AH41156955 
938 |a ProQuest Ebook Central  |b EBLB  |n EBL6647712 
938 |a YBP Library Services  |b YANK  |n 302286822 
938 |a YBP Library Services  |b YANK  |n 17517173 
994 |a 92  |b IZTAP 

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