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Functional applications of text analytics systems / / Steven Simske and Marie Vans, editors
| Functional applications of text analytics systems / / Steven Simske and Marie Vans, editors |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Denmark : , : River Publishers, , [2021] |
| Descrizione fisica | 1 online resource (292 pages) |
| Disciplina | 006.312 |
| Collana | River Publishers Series in Document Engineering |
| Soggetto topico | Text data mining |
| ISBN |
1-00-333822-4
1-003-33822-4 1-000-79358-3 87-7022-342-4 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- Half Title -- Series Page -- Title Page -- Copyright Page -- Table of Contents -- Preface -- Acknowledgement -- List of Figures -- List of Tables -- List of Abbreviations -- 1: Linguistics and NLP -- 1.1 Introduction -- 1.2 General Considerations -- 1.3 Machine Learning Aspects -- 1.3.1 Machine Learning Features -- 1.3.2 Other Machine Learning Approaches -- 1.4 Design/System Considerations -- 1.4.1 Sensitivity Analysis -- 1.4.2 Iterative Tradeoff in Approach -- 1.4.3 Competition - Cooperation Algorithms -- 1.4.4 Top-Down and Bottom-Up Designs -- 1.4.5 Agent-Based Models and Other Simulations -- 1.5 Applications/Examples -- 1.6 Test and Configuration -- 1.7 Summary -- 2: Summarization -- 2.1 Introduction -- 2.2 General Considerations -- 2.2.1 Summarization Approaches - An Overview -- 2.2.2 Weighting Factors in Extractive Summarization -- 2.2.3 Other Considerations in Extractive Summarization -- 2.2.4 Meta-Algorithmics and Extractive Summarization -- 2.3 Machine Learning Aspects -- 2.4 Design/System Considerations -- 2.5 Applications/Examples -- 2.6 Test and Configuration -- 2.7 Summary -- 3: Clustering, Classification, and Categorization -- 3.1 Introduction -- 3.1.1 Clustering -- 3.1.2 Regularization - An Introduction -- 3.1.3 Regularization and Clustering -- 3.2 General Considerations -- 3.3 Machine Learning Aspects -- 3.3.1 Machine Learning and Clustering -- 3.3.2 Machine Learning and Classification -- 3.3.3 Machine Learning and Categorization -- 3.4 Design/System Considerations -- 3.5 Applications/Examples -- 3.5.1 Query-Synonym Expansion -- 3.5.2 ANOVA, Cross-Correlation, and Image Classification -- 3.6 Test and Configuration -- 3.7 Summary -- 4: Translation -- 4.1 Introduction -- 4.2 General Considerations -- 4.2.1 Review of Relevant Prior Research -- 4.2.2 Summarization as a Means to Functionally Grade the Accuracy of Translation.
4.3 Machine Learning Aspects -- 4.3.1 Summarization and Translation -- 4.3.2 Document Reading Order -- 4.3.3 Other Machine Learning Considerations -- 4.4 Design/System Considerations -- 4.5 Applications/Examples -- 4.6 Test and Configuration -- 4.7 Summary -- 5: Optimization -- 5.1 Introduction -- 5.2 General Considerations -- 5.3 Machine Learning Aspects -- 5.4 Design/System Considerations -- 5.5 Applications/Examples -- 5.5.1 Document Clustering -- 5.5.2 Document Classification -- 5.5.3 Web Mining -- 5.5.4 Information and Content Extraction -- 5.5.5 Natural Language Processing -- 5.5.6 Sentiment Analysis -- 5.5.7 Native vs. Non-Native Speakers -- 5.5.8 Virtual Reality and Augmented Reality -- 5.6 Test and Configuration -- 5.7 Summary -- 6: Learning -- 6.1 Introduction -- 6.1.1 Reading Order -- 6.1.2 Repurposing of Text -- 6.1.3 Philosophies of Learning -- 6.2 General Considerations -- 6.2.1 Metadata -- 6.2.2 Pathways of Learning -- 6.3 Machine Learning Aspects -- 6.3.1 Learning About Machine Learning -- 6.3.2 Machine Learning Constraints -- 6.4 Design/System Considerations -- 6.4.1 Do Not Use Machine Learning for the Sake of Using Machine Learning -- 6.4.2 Learning to Learn -- 6.4.3 Prediction Time -- 6.5 Applications/Examples -- 6.5.1 Curriculum Development -- 6.5.2 Customized Education Planning -- 6.5.3 Personalized Rehearsing -- 6.6 Test and Configuration -- 6.7 Summary -- 7: Testing and Configuration -- 7.1 Introduction -- 7.2 General Considerations -- 7.2.1 Data-Ops -- 7.2.2 Text Analytics and Immunological Data -- 7.2.3 Text Analytics and Cybersecurity -- 7.2.4 Data-Ops and Testing -- 7.3 Machine Learning Aspects -- 7.4 Design/System Considerations -- 7.5 Applications/Examples -- 7.6 Test and Configuration -- 7.7 Summary -- Index -- About the Author. |
| Record Nr. | UNINA-9910794691603321 |
| Denmark : , : River Publishers, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Functional applications of text analytics systems / / Steven Simske and Marie Vans, editors
| Functional applications of text analytics systems / / Steven Simske and Marie Vans, editors |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Denmark : , : River Publishers, , [2021] |
| Descrizione fisica | 1 online resource (292 pages) |
| Disciplina | 006.312 |
| Collana | River Publishers Series in Document Engineering |
| Soggetto topico | Text data mining |
| ISBN |
1-00-333822-4
1-003-33822-4 1-000-79358-3 87-7022-342-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- Half Title -- Series Page -- Title Page -- Copyright Page -- Table of Contents -- Preface -- Acknowledgement -- List of Figures -- List of Tables -- List of Abbreviations -- 1: Linguistics and NLP -- 1.1 Introduction -- 1.2 General Considerations -- 1.3 Machine Learning Aspects -- 1.3.1 Machine Learning Features -- 1.3.2 Other Machine Learning Approaches -- 1.4 Design/System Considerations -- 1.4.1 Sensitivity Analysis -- 1.4.2 Iterative Tradeoff in Approach -- 1.4.3 Competition - Cooperation Algorithms -- 1.4.4 Top-Down and Bottom-Up Designs -- 1.4.5 Agent-Based Models and Other Simulations -- 1.5 Applications/Examples -- 1.6 Test and Configuration -- 1.7 Summary -- 2: Summarization -- 2.1 Introduction -- 2.2 General Considerations -- 2.2.1 Summarization Approaches - An Overview -- 2.2.2 Weighting Factors in Extractive Summarization -- 2.2.3 Other Considerations in Extractive Summarization -- 2.2.4 Meta-Algorithmics and Extractive Summarization -- 2.3 Machine Learning Aspects -- 2.4 Design/System Considerations -- 2.5 Applications/Examples -- 2.6 Test and Configuration -- 2.7 Summary -- 3: Clustering, Classification, and Categorization -- 3.1 Introduction -- 3.1.1 Clustering -- 3.1.2 Regularization - An Introduction -- 3.1.3 Regularization and Clustering -- 3.2 General Considerations -- 3.3 Machine Learning Aspects -- 3.3.1 Machine Learning and Clustering -- 3.3.2 Machine Learning and Classification -- 3.3.3 Machine Learning and Categorization -- 3.4 Design/System Considerations -- 3.5 Applications/Examples -- 3.5.1 Query-Synonym Expansion -- 3.5.2 ANOVA, Cross-Correlation, and Image Classification -- 3.6 Test and Configuration -- 3.7 Summary -- 4: Translation -- 4.1 Introduction -- 4.2 General Considerations -- 4.2.1 Review of Relevant Prior Research -- 4.2.2 Summarization as a Means to Functionally Grade the Accuracy of Translation.
4.3 Machine Learning Aspects -- 4.3.1 Summarization and Translation -- 4.3.2 Document Reading Order -- 4.3.3 Other Machine Learning Considerations -- 4.4 Design/System Considerations -- 4.5 Applications/Examples -- 4.6 Test and Configuration -- 4.7 Summary -- 5: Optimization -- 5.1 Introduction -- 5.2 General Considerations -- 5.3 Machine Learning Aspects -- 5.4 Design/System Considerations -- 5.5 Applications/Examples -- 5.5.1 Document Clustering -- 5.5.2 Document Classification -- 5.5.3 Web Mining -- 5.5.4 Information and Content Extraction -- 5.5.5 Natural Language Processing -- 5.5.6 Sentiment Analysis -- 5.5.7 Native vs. Non-Native Speakers -- 5.5.8 Virtual Reality and Augmented Reality -- 5.6 Test and Configuration -- 5.7 Summary -- 6: Learning -- 6.1 Introduction -- 6.1.1 Reading Order -- 6.1.2 Repurposing of Text -- 6.1.3 Philosophies of Learning -- 6.2 General Considerations -- 6.2.1 Metadata -- 6.2.2 Pathways of Learning -- 6.3 Machine Learning Aspects -- 6.3.1 Learning About Machine Learning -- 6.3.2 Machine Learning Constraints -- 6.4 Design/System Considerations -- 6.4.1 Do Not Use Machine Learning for the Sake of Using Machine Learning -- 6.4.2 Learning to Learn -- 6.4.3 Prediction Time -- 6.5 Applications/Examples -- 6.5.1 Curriculum Development -- 6.5.2 Customized Education Planning -- 6.5.3 Personalized Rehearsing -- 6.6 Test and Configuration -- 6.7 Summary -- 7: Testing and Configuration -- 7.1 Introduction -- 7.2 General Considerations -- 7.2.1 Data-Ops -- 7.2.2 Text Analytics and Immunological Data -- 7.2.3 Text Analytics and Cybersecurity -- 7.2.4 Data-Ops and Testing -- 7.3 Machine Learning Aspects -- 7.4 Design/System Considerations -- 7.5 Applications/Examples -- 7.6 Test and Configuration -- 7.7 Summary -- Index -- About the Author. |
| Record Nr. | UNINA-9910811011803321 |
| Denmark : , : River Publishers, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Low resource social media text mining / / Shriphani Palakodety, Ashiqur R. KhudaBukhsh, Guha Jayachandran
| Low resource social media text mining / / Shriphani Palakodety, Ashiqur R. KhudaBukhsh, Guha Jayachandran |
| Autore | Palakodety Shriphani |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (67 pages) |
| Disciplina | 006.312 |
| Collana | SpringerBriefs in Computer Science |
| Soggetto topico |
Text data mining
Natural language processing (Computer science) |
| ISBN | 981-16-5625-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910502650503321 |
Palakodety Shriphani
|
||
| Singapore : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Low resource social media text mining / / Shriphani Palakodety, Ashiqur R. KhudaBukhsh, Guha Jayachandran
| Low resource social media text mining / / Shriphani Palakodety, Ashiqur R. KhudaBukhsh, Guha Jayachandran |
| Autore | Palakodety Shriphani |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (67 pages) |
| Disciplina | 006.312 |
| Collana | SpringerBriefs in Computer Science |
| Soggetto topico |
Text data mining
Natural language processing (Computer science) |
| ISBN | 981-16-5625-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996464533103316 |
|
Palakodety Shriphani
|
||
| Singapore : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Practical text mining with Perl [[electronic resource] /] / Roger Bilisoly
| Practical text mining with Perl [[electronic resource] /] / Roger Bilisoly |
| Autore | Bilisoly Roger <1963-> |
| Pubbl/distr/stampa | Hoboken, N.J., : Wiley, c2008 |
| Descrizione fisica | 1 online resource (322 p.) |
| Disciplina | 005.74 |
| Collana | Wiley series on methods and applications in data mining |
| Soggetto topico |
Text data mining
Perl (Computer program language) |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-118-21050-6
1-281-78799-X 9786611787998 0-470-38286-4 0-470-38285-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Practical Text Mining With Perl; Contents; List of Figures; List of Tables; Preface; Acknowledgments; 1 Introduction; 2 Text Patterns; 3 Quantitative Text Summaries; 4 Probability and Text Sampling; 5 Applying Information Retrieval to Text Mining; 6 Concordance Lines and Corpus Linguistics; 7 Multivariate Techniques with Text; 8 Text Clustering; 9 A Sample of Additional Topics; Appendix A: Overview of Perl for Text Mining; Appendix B: Summary of R used in this Book; References; Index |
| Record Nr. | UNINA-9910143987203321 |
|
Bilisoly Roger <1963->
|
||
| Hoboken, N.J., : Wiley, c2008 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Practical text mining with Perl [[electronic resource] /] / Roger Bilisoly
| Practical text mining with Perl [[electronic resource] /] / Roger Bilisoly |
| Autore | Bilisoly Roger <1963-> |
| Pubbl/distr/stampa | Hoboken, N.J., : Wiley, c2008 |
| Descrizione fisica | 1 online resource (322 p.) |
| Disciplina | 005.74 |
| Collana | Wiley series on methods and applications in data mining |
| Soggetto topico |
Text data mining
Perl (Computer program language) |
| ISBN |
1-118-21050-6
1-281-78799-X 9786611787998 0-470-38286-4 0-470-38285-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Practical Text Mining With Perl; Contents; List of Figures; List of Tables; Preface; Acknowledgments; 1 Introduction; 2 Text Patterns; 3 Quantitative Text Summaries; 4 Probability and Text Sampling; 5 Applying Information Retrieval to Text Mining; 6 Concordance Lines and Corpus Linguistics; 7 Multivariate Techniques with Text; 8 Text Clustering; 9 A Sample of Additional Topics; Appendix A: Overview of Perl for Text Mining; Appendix B: Summary of R used in this Book; References; Index |
| Record Nr. | UNINA-9910829995403321 |
|
Bilisoly Roger <1963->
|
||
| Hoboken, N.J., : Wiley, c2008 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Revista Humanidades Digitales (RHD) = : Journal of Digital Humanities
| Revista Humanidades Digitales (RHD) = : Journal of Digital Humanities |
| Pubbl/distr/stampa | Spain, : Universidad Nacional de Educación a Distancia (UNED), 2017-9999 |
| Soggetto topico |
Electronic journals
Humanities - Periodicals Digital libraries Text data mining Sentiment analysis Corpora (Linguistics) Natural language processing (Computer science) Digital preservation |
| Soggetto non controllato |
digital archives
digital media digitization |
| ISSN | 2531-1786 |
| Formato | Materiale a stampa |
| Livello bibliografico | Periodico |
| Lingua di pubblicazione | spa |
| Record Nr. | UNISA-996321023603316 |
| Spain, : Universidad Nacional de Educación a Distancia (UNED), 2017-9999 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Revista Humanidades Digitales (RHD) = : Journal of Digital Humanities
| Revista Humanidades Digitales (RHD) = : Journal of Digital Humanities |
| Pubbl/distr/stampa | Spain, : Universidad Nacional de Educación a Distancia (UNED), 2017-9999 |
| Soggetto topico |
Electronic journals
Humanities - Periodicals Digital libraries Text data mining Sentiment analysis Corpora (Linguistics) Natural language processing (Computer science) Digital preservation |
| Soggetto non controllato |
digital archives
digital media digitization |
| ISSN | 2531-1786 |
| Formato | Materiale a stampa |
| Livello bibliografico | Periodico |
| Lingua di pubblicazione | spa |
| Record Nr. | UNINA-9910330728103321 |
| Spain, : Universidad Nacional de Educación a Distancia (UNED), 2017-9999 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Text as data : computational methods of understanding written expression using SAS / / Barry deVille, Gurpreet Singh Bawa
| Text as data : computational methods of understanding written expression using SAS / / Barry deVille, Gurpreet Singh Bawa |
| Autore | De Ville Barry |
| Pubbl/distr/stampa | Hoboken, NJ : , : John Wiley & Sons, Inc., , [2022] |
| Descrizione fisica | 1 online resource (235 pages) |
| Disciplina | 006.312 |
| Collana | Wiley and SAS business series |
| Soggetto topico | Text data mining |
| Soggetto genere / forma | Electronic books. |
| ISBN |
9781119487142
1-119-48714-5 1-119-48715-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- Title Page -- Copyright Page -- Contents -- Preface -- Acknowledgments -- About the Authors -- Introduction -- Chapter 1 Text Mining and Text Analytics -- Background and Terminology -- Text Analytics: What Is It? -- Brief History of Text -- Writing Systems of the World -- Meaning and Ambiguity -- Notes -- Chapter 2 Text Analytics Process Overview -- Text Analytics Processing -- Process Building Blocks -- Preparation -- Utilization -- Process Description -- Text Mining Data Sources -- Capture -- Linguistic Processing -- Parsing and Parse Products -- Internal Representation and Text Products -- Representation -- Notes -- Chapter 3 Text Data Source Capture -- Text Mining Data Source Assembly -- Use Case: Accessing Text from SAS Conference Proceedings -- Text Data Capture Process -- Consuming Linguistics Text Products -- Notes -- Chapter 4 Document Content and Characterization -- Authorship Analytics: Early Text Indicators and Measures -- Function Words as Indicators -- Beyond Function Words -- Words and Word Forms as Psychological Artifacts -- A Case Study in Gender Detection -- Data Product Example -- Analysis Results -- Summarization and Discourse Analysis -- Elementary Operations as Building Blocks to Results -- Fact Extraction -- Sentiment Extraction -- Conditional Inference -- Deployment -- Summarization -- Conclusion -- Notes -- Chapter 5 Textual Abstraction: Latent Structure, Dimension Reduction -- Text Mining Data Source Assembly -- Latent Structure and Dimensional Reduction -- Singular Value Decomposition as Dimension Reduction -- Latent Semantic Analysis -- Clustering Approach to Document Classification -- SVD Approach to Document Indexing -- Rough Meaning - Approximation for Singular Value Dimensions -- Semantic Indexing: Assigning Category Based on Singular Value Dimensional Scores -- Identifying Topics Using Latent Structure.
Latent Structure: Tracking Topic Term Variability Across Semantic Fields -- Conclusion -- Notes -- Chapter 6 Classification and Prediction -- Use Case Scenario -- Composite Document Construction -- Model Development -- Ensemble or Multiagent Models -- Identifying Drivers of Textual Consumer Feedback Using Distance-Based Clustering and Matrix Factorization -- Use Case Scenario: Retailer Reliability Ecommerce -- Discussion -- Notes -- Chapter 7 Boolean Methods of Classification and Prediction -- Rule-Based Text Classification and Prediction -- Method Description -- Characteristics of Boolean Rule Methods -- Example of Boolean Rules Applied to Text Mining Vaccine Data -- An Example Analysis -- Summary -- Notes -- Chapter 8 Speech to Text -- Introduction -- Processing Audio Feedback -- Business Problem -- Process Components -- Further Analysis: Sentiment and Latent Topics -- Conclusion -- Notes -- Appendix A Mood State Identification in Text -- Origins of Mood State Identification -- An Approach to Mood State Developed at SAS -- Background and Discussion -- An Example Mood State Process Flow -- Notes -- Appendix B A Design Approach to Characterizing Users Based on AudioInteractions on a Conversational AI Platform -- Audio-Based User Interaction Inference -- Recommendation Perspective vs. Conventional -- Sole Dependency on Text-Based Bots -- Implementation Scenario: Voice-Based Conversational AI Platform -- Component Process Flow -- Constructed Interaction -- Note -- Appendix C SAS Patents in Text Analytics -- Glossary -- Index -- EULA. |
| Record Nr. | UNINA-9910555092303321 |
|
De Ville Barry
|
||
| Hoboken, NJ : , : John Wiley & Sons, Inc., , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Text as data : computational methods of understanding written expression using SAS / / Barry deVille, Gurpreet Singh Bawa
| Text as data : computational methods of understanding written expression using SAS / / Barry deVille, Gurpreet Singh Bawa |
| Autore | De Ville Barry |
| Pubbl/distr/stampa | Hoboken, NJ : , : John Wiley & Sons, Inc., , [2022] |
| Descrizione fisica | 1 online resource (235 pages) |
| Disciplina | 006.312 |
| Collana | Wiley and SAS business series |
| Soggetto topico | Text data mining |
| ISBN |
1-119-48714-5
1-119-48715-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- Title Page -- Copyright Page -- Contents -- Preface -- Acknowledgments -- About the Authors -- Introduction -- Chapter 1 Text Mining and Text Analytics -- Background and Terminology -- Text Analytics: What Is It? -- Brief History of Text -- Writing Systems of the World -- Meaning and Ambiguity -- Notes -- Chapter 2 Text Analytics Process Overview -- Text Analytics Processing -- Process Building Blocks -- Preparation -- Utilization -- Process Description -- Text Mining Data Sources -- Capture -- Linguistic Processing -- Parsing and Parse Products -- Internal Representation and Text Products -- Representation -- Notes -- Chapter 3 Text Data Source Capture -- Text Mining Data Source Assembly -- Use Case: Accessing Text from SAS Conference Proceedings -- Text Data Capture Process -- Consuming Linguistics Text Products -- Notes -- Chapter 4 Document Content and Characterization -- Authorship Analytics: Early Text Indicators and Measures -- Function Words as Indicators -- Beyond Function Words -- Words and Word Forms as Psychological Artifacts -- A Case Study in Gender Detection -- Data Product Example -- Analysis Results -- Summarization and Discourse Analysis -- Elementary Operations as Building Blocks to Results -- Fact Extraction -- Sentiment Extraction -- Conditional Inference -- Deployment -- Summarization -- Conclusion -- Notes -- Chapter 5 Textual Abstraction: Latent Structure, Dimension Reduction -- Text Mining Data Source Assembly -- Latent Structure and Dimensional Reduction -- Singular Value Decomposition as Dimension Reduction -- Latent Semantic Analysis -- Clustering Approach to Document Classification -- SVD Approach to Document Indexing -- Rough Meaning - Approximation for Singular Value Dimensions -- Semantic Indexing: Assigning Category Based on Singular Value Dimensional Scores -- Identifying Topics Using Latent Structure.
Latent Structure: Tracking Topic Term Variability Across Semantic Fields -- Conclusion -- Notes -- Chapter 6 Classification and Prediction -- Use Case Scenario -- Composite Document Construction -- Model Development -- Ensemble or Multiagent Models -- Identifying Drivers of Textual Consumer Feedback Using Distance-Based Clustering and Matrix Factorization -- Use Case Scenario: Retailer Reliability Ecommerce -- Discussion -- Notes -- Chapter 7 Boolean Methods of Classification and Prediction -- Rule-Based Text Classification and Prediction -- Method Description -- Characteristics of Boolean Rule Methods -- Example of Boolean Rules Applied to Text Mining Vaccine Data -- An Example Analysis -- Summary -- Notes -- Chapter 8 Speech to Text -- Introduction -- Processing Audio Feedback -- Business Problem -- Process Components -- Further Analysis: Sentiment and Latent Topics -- Conclusion -- Notes -- Appendix A Mood State Identification in Text -- Origins of Mood State Identification -- An Approach to Mood State Developed at SAS -- Background and Discussion -- An Example Mood State Process Flow -- Notes -- Appendix B A Design Approach to Characterizing Users Based on AudioInteractions on a Conversational AI Platform -- Audio-Based User Interaction Inference -- Recommendation Perspective vs. Conventional -- Sole Dependency on Text-Based Bots -- Implementation Scenario: Voice-Based Conversational AI Platform -- Component Process Flow -- Constructed Interaction -- Note -- Appendix C SAS Patents in Text Analytics -- Glossary -- Index -- EULA. |
| Record Nr. | UNINA-9910830069703321 |
|
De Ville Barry
|
||
| Hoboken, NJ : , : John Wiley & Sons, Inc., , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
