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1. |
Record Nr. |
UNINA990002286190403321 |
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Titolo |
Termodinamica degli equilibri di complessi in solventi inerti. Roma, 1961, p. 517-535 |
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Altri autori (Persone) |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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2. |
Record Nr. |
UNISA990000590880203316 |
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Autore |
FLORIDIA, Antonio |
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Titolo |
Regolazione sociale ed economie locali / attori, strategie, risorse : il caso dei distretti conciari / di Antonio Floridia, Leonardo Parri, Floriana Quaglia |
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Pubbl/distr/stampa |
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ISBN |
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Descrizione fisica |
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Collana |
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Irpet/Istituto regionale per la programmazione economica della Toscana ; 20 |
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Altri autori (Persone) |
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PARRI, Leonardo |
QUAGLIA, Floriana |
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Disciplina |
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Soggetti |
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Concia - Industria - Arzignano - 1980-1990 |
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Collocazione |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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In testa al front.: Irpet, Istituto regionale per la programmazione economica della Toscana |
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3. |
Record Nr. |
UNINA9910794555103321 |
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Autore |
Fortino Andres G. |
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Titolo |
Text analytics for business decisions : a case study approach / / Andres G. Fortino |
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Pubbl/distr/stampa |
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Dulles : , : Mercury Learning & Information, , [2021] |
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©2021 |
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ISBN |
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1-68392-664-1 |
1-68392-665-X |
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Descrizione fisica |
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1 online resource (332 pages) |
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Disciplina |
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Soggetti |
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Business - Decision making - Computer programs |
Text processing (Computer science) |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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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 -- 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 -- 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 -- |
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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? -- 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 -- 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 -- Exercise 8.3 - Case Study Using Dataset C: Product Reviews -- Exercise 8.4 - Case Study Using Dataset E: Large Text Files -- References -- Chapter 9 : Coding Text Data -- What is a Code? -- What are the Common Approaches to Coding Text Data? -- What is Inductive Coding? -- Exercise 9.1 - Case Study Using Dataset A: Training -- Exercise 9.2 - Case Study Using Dataset J: Remote Learning -- Exercise 9.3 - Case Study Using Dataset E: Large Text Files -- Affinity Diagram Coding -- Exercise 9.4 - Case Study Using Dataset M: Onboarding Brainstorming -- References -- Chapter 10 : Named Entity Recognition -- Named Entity Recognition -- What is a Named Entity? -- Common Approaches to Extracting Named Entities -- Classifiers - The Core NER Process -- What Does This Mean for Business? -- Exercise 10.1 - Using the Stanford NER -- Exercise 10.2 - Example Cases. |
Exercise 10.2 - Case Study Using Dataset H: Corporate Financial Reports -- Additional Exercise 10.3 - Case Study Using Dataset L: Corporate Financial Reports -- Exercise 10.4 - Case Study Using Dataset E: Large Text Files -- Additional Exercise 10.5 - Case Study Using Dataset E: Large Text Files -- References -- Chapter 11 : Topic Recognition in Documents -- Information Retrieval -- Document Characterization -- Topic Recognition -- Exercises -- Exercise 11.1 - Case Study Using Dataset G: University Curricula -- Exercise 11.2 - Case Study Using Dataset E: Large Text Files -- Exercise 11.3 - Case Study Using Dataset E: Large Text Files -- Exercise 11.4 - Case Study Using Dataset E: Large Text Files -- Exercise 11.5 - Case Study Using Dataset E: Large Text Files -- Additional Exercise 11.6 - Case Study Using Dataset P: Patents -- Additional Exercise 11.7 - Case Study Using Dataset F: Federalist Papers -- Additional Exercise 11.8 - Case Study Using Dataset E: Large Text Files -- Additional Exercise 11.9- Case Study Using Dataset N: Sonnets -- References -- Chapter 12 : Text Similarity Scoring -- What is Text Similarity Scoring? -- Text Similarity Scoring Exercises -- Exercise 12.1 - Case Study Using Dataset D: Occupation Description -- Analysis using R -- Exercise 12.2 - Case D: Resume and Job Description -- Reference -- Chapter 13 : Analysis of Large Datasets by Sampling -- Using Sampling to Work with Large Data Files -- Exercise 13.1 - Big Data Analysis -- Additional Case Study Using Dataset E: BankComplaints Big Data File -- Chapter 14 : |
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Installing R and RStudio -- Installing R -- Install R Software for a Mac System -- Installing RStudio -- Reference -- Chapter 15 : Installing the Entity Extraction Tool -- Downloading and Installing the Tool -- The NER Graphical User Interface -- Reference -- Chapter 16 : Installing the Topic Modeling Tool. |
Installing and Using the Topic Modeling Tool -- Install the tool -- For Macs -- For Windows PCs -- UTF-8 caveat -- Setting up the workspace -- Workspace Directory -- Using the Tool -- Select metadata file -- Selecting the number of topics -- Analyzing the Output -- Multiple Passes for Optimization -- The Output Files -- Chapter 17 : Installing the Voyant Text Analysis Tool -- Install or Update Java -- Installation of Voyant Server -- The Voyant Server -- Downloading VoyantServer -- Running Voyant Server -- Controlling the Voyant Server -- Testing the Installation -- Reference -- INDEX. |
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Sommario/riassunto |
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With the rise in data science development, we now have many remarkable techniques and tools to extend data analysis from numeric and categorical data to textual data. Sifting through the open-ended responses from a survey, for example, was an arduous process when performed by hand. Using a case study approach, this book was written for business analysts who wish to increase their skills in extracting answers for text data in order to support business decision making. Most of the exercises use Excel, today’s most common analysis tool, and R, a popular analytic computer environment. The techniques covered range from the most basic text analytics, such as key word analysis, to more sophisticated techniques, such as topic extraction and text similarity scoring. Companion files with numerous datasets are included for use with case studies and exercises. FEATURES: Organized by tool or technique, with the basic techniques presented first and the more sophisticated techniques presented laterUses Excel and R for datasets in case studies and exercisesFeatures the CRISP-DM data mining standard with early chapters for conducting the preparatory steps in data miningCompanion files with numerous datasets and figures from the text.The companion files are available online by emailing the publisher with proof of purchase at info@merclearning.com. |
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4. |
Record Nr. |
UNINA9910973003903321 |
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Titolo |
Chinese society : change and transformation / / edited by Li Peilin |
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Pubbl/distr/stampa |
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London ; ; New York : , : Routledge, , 2012 |
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ISBN |
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1-136-30016-3 |
1-283-53312-X |
9786613845573 |
0-203-11673-9 |
1-136-30017-1 |
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Edizione |
[1st ed.] |
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Descrizione fisica |
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1 online resource (304 p.) |
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Altri autori (Persone) |
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Disciplina |
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Soggetti |
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Social change - China - History - 21st century |
Social change - China - History - 20th century |
China Social conditions 2000- |
China Social conditions 20th century |
China Social policy |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Front Cover; Chinese Society - Change and Transformation; Copyright Page; Contents; Notes on contributors; Introduction: Li Peilin; 1. Chinese society and the China Experience: Li Peilin; Basic characteristics of traditional Chinese society; Social changes in modern China; Social changes since reform and opening up; Reform and development of the 'China Experience'; Key points of the China Experience; 2. Marriage and family: Yang Shanhua; Background of institutional changes in China's urban and rural households; Characteristics and mechanisms of urban and rural family institutional changes |
Marriage in social transitionChanges in the family system and community reasoning; 3. Lineage and family: Zhang Xiaojun; An overview of family and lineage; The form of lineage and family; Country, land and revolution; Understanding lineages through five points of the China Experience; 4. Ethnicities and ethnic relations: Hao Shiyuan; From the 'five ethnicities' to the Chinese nation; Regional |
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ethnic autonomy and ethnic equality; Western development and ethnic affairs; 5. Social mentality and contemporary changes: Zhou Xiaohong |
Chinese people's traditional social mentality and modern evolutionLiberation: collapse of old traditions and consolidation of 'new tradition'; The evolutionary trajectory of Chinese social mentality since reform and opening up; Marginal man: modern Chinese group consciousness; The changing trend of Chinese social mentality; 6. Demographic transition and economic and social development: Cai Fang; China's unique demographic transition; Demographic dividend, source of growth and growth performance; Demographic position and growth sustainability; Demographic transition and social construction |
Fertility policy7. The political system and reform in China: Yang Dali; The institutional environment and evolution of personal power and status acquisition in China; The political system and development in China's social structural transformation; 8. Urbanization and urban-rural relations: Cai He; The process of urbanization; Characteristics of urbanization; Urban-rural relations; 9. Social stratification and institutional change: Li Qiang; The basic characteristics of China's social stratification structure; Changes in social hierarchical structure since reform and opening up |
The new trend of China's social stratification structural transformation10. Migrant workers and social mobility: Li Chunling; The distinguishing features of China's rural-urban immigration movements; Migrant workers' attainment of socio-economic status; Social mobility of the social transformation period; 11. Anti-poverty and social policies: Guan Xinping; Contemporary poverty issues and the characteristics of poverty in China; Poverty and anti-poverty action in rural China; Urban poverty and anti-poverty action in contemporary China; References and bibliography; Index |
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Sommario/riassunto |
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There is growing interest in social transformation in contemporary China, with much work published on the subject. This book is different from other books in that it presents an overview of the work of Chinese sociologists on how Chinese society is changing. It reports on a great deal of original research by leading, outstanding Chinese scholars, including extensive fieldwork and large-scale social change survey data, and covers comprehensively the full range of aspects of the subject. It assesses developments since the beginning of reform in China, and provides, overall, a comprehensive un |
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