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• Preface Acknowledgments
• Part 1: Setting the Stage Introduction
• Part 2: Getting Ready The Data-Driven Persona Revolution Getting Your Organization Data-Driven Persona Ready
• Part 3: Developing Data-Driven Personas Getting Meaningful Data Creating Data-Driven Personas Data-Driven Personas as Interfaces for Persona Analytics System
• Part 4: Using Data-Driven Personas Challenges of Applying Data-Driven Persona Development Use Cases for Data-Driven Personas Using Data-Driven Personas Alongside Other Human-Computer Interaction (HCI) Techniques
• Part 5: Evaluating Data-Driven Personas and the Road Ahead Evaluating Data-Driven Personas Selecting the Appropriate Persona Creation Method
• Part 6: Data-Driven Personas and the Future Conclusion: Dispelling Myths ad Laying Out the Grand Challenges of Data-Driven Personas Appendix A: Persona Perception Scale Items Appendix B: User Interview Questions for Persona Data Collection Appendix C: Persona Profile Attribute Comparison Glossary Afterword Authors' Biographies.
• (source: Nielsen Book Data)

Data-driven personas are a significant advancement in the fields of human-centered informatics and human-computer interaction. Data-driven personas enhance user understanding by combining the empathy inherent with personas with the rationality inherent in analytics using computational methods. Via the employment of these computational methods, the data-driven persona method permits the use of large-scale user data, which is a novel advancement in persona creation. A common approach for increasing stakeholder engagement about audiences, customers, or users, persona creation remained relatively unchanged for several decades. However, the availability of digital user data, data science algorithms, and easy access to analytics platforms provide avenues and opportunities to enhance personas from often sketchy representations of user segments to precise, actionable, interactive decision-making tools-data-driven personas! Using the data-driven approach, the persona profile can serve as an interface to a fully functional analytics system that can present user representation at various levels of information granularity for more task-aligned user insights. We trace the techniques that have enabled the development of data-driven personas and then conceptually frame how one can leverage data-driven personas as tools for both empathizing with and understanding of users. Presenting a conceptual framework consisting of (a) persona benefits, (b) analytics benefits, and (c) decision-making outcomes, we illustrate applying this framework via practical use cases in areas of system design, digital marketing, and content creation to demonstrate the application of data-driven personas in practical applied situations. We then present an overview of a fully functional data-driven persona system as an example of multi-level information aggregation needed for decision making about users. We demonstrate that data-driven personas systems can provide critical, empathetic, and user understanding functionalities for anyone needing such insights.
(source: Nielsen Book Data)

• Preface Acknowledgments
• Part 1: Setting the Stage Introduction
• Part 2: Getting Ready The Data-Driven Persona Revolution Getting Your Organization Data-Driven Persona Ready
• Part 3: Developing Data-Driven Personas Getting Meaningful Data Creating Data-Driven Personas Data-Driven Personas as Interfaces for Persona Analytics System
• Part 4: Using Data-Driven Personas Challenges of Applying Data-Driven Persona Development Use Cases for Data-Driven Personas Using Data-Driven Personas Alongside Other Human-Computer Interaction (HCI) Techniques
• Part 5: Evaluating Data-Driven Personas and the Road Ahead Evaluating Data-Driven Personas Selecting the Appropriate Persona Creation Method
• Part 6: Data-Driven Personas and the Future Conclusion: Dispelling Myths ad Laying Out the Grand Challenges of Data-Driven Personas Appendix A: Persona Perception Scale Items Appendix B: User Interview Questions for Persona Data Collection Appendix C: Persona Profile Attribute Comparison Glossary Afterword Authors' Biographies.
• (source: Nielsen Book Data)

Data-driven personas are a significant advancement in the fields of human-centered informatics and human-computer interaction. Data-driven personas enhance user understanding by combining the empathy inherent with personas with the rationality inherent in analytics using computational methods. Via the employment of these computational methods, the data-driven persona method permits the use of large-scale user data, which is a novel advancement in persona creation. A common approach for increasing stakeholder engagement about audiences, customers, or users, persona creation remained relatively unchanged for several decades. However, the availability of digital user data, data science algorithms, and easy access to analytics platforms provide avenues and opportunities to enhance personas from often sketchy representations of user segments to precise, actionable, interactive decision-making tools-data-driven personas! Using the data-driven approach, the persona profile can serve as an interface to a fully functional analytics system that can present user representation at various levels of information granularity for more task-aligned user insights. We trace the techniques that have enabled the development of data-driven personas and then conceptually frame how one can leverage data-driven personas as tools for both empathizing with and understanding of users. Presenting a conceptual framework consisting of (a) persona benefits, (b) analytics benefits, and (c) decision-making outcomes, we illustrate applying this framework via practical use cases in areas of system design, digital marketing, and content creation to demonstrate the application of data-driven personas in practical applied situations. We then present an overview of a fully functional data-driven persona system as an example of multi-level information aggregation needed for decision making about users. We demonstrate that data-driven personas systems can provide critical, empathetic, and user understanding functionalities for anyone needing such insights.
(source: Nielsen Book Data)

• 1. A context for sponsored search
• 2. Modeling the process of sponsored search
• 3. Understanding the potential customers' intent for keyword selection
• 4. Sending signals to the potential customer with ads
• 5. Understanding consumer behavior for sponsored search
• 6. BAM: branding advertising and marketing for sponsored search
• 7. Sponsored search analytics
• 8. The serious game of bidding on keywords
• 9. Bringing it all together in a framework of sponsored search
• 10. The future of sponsored search.
• (source: Nielsen Book Data)

This book addresses the underlying foundational elements, both theoretical and methodological, of sponsored search. As such, the contents are less affected by the ever-changing implementation aspects of technology. Rather than focusing on the how, this book examines what causes the how. Why do certain keywords work, while others do not? Why does that ad work well, when others that are similar do not? Why does a key phrase cost a given amount? Why do we measure what we do in keyword advertising? This book speaks to that curiosity to understand why we do what we do in sponsored search. The content flows through the major components of any sponsored search effort, regardless of the underlying technology or client or product. The book addresses keywords, ads, consumers, pricing, competitors, analytics, branding, marketing and advertising, integrating these separate components into an incorporated whole. The focus is on the critical elements, with ample illustrations and with enough detail to lead the interested reader to further inquiry.
(source: Nielsen Book Data)

• 1. A context for sponsored search
• 2. Modeling the process of sponsored search
• 3. Understanding the potential customers' intent for keyword selection
• 4. Sending signals to the potential customer with ads
• 5. Understanding consumer behavior for sponsored search
• 6. BAM: branding advertising and marketing for sponsored search
• 7. Sponsored search analytics
• 8. The serious game of bidding on keywords
• 9. Bringing it all together in a framework of sponsored search
• 10. The future of sponsored search.
• (source: Nielsen Book Data)

This book addresses the underlying foundational elements, both theoretical and methodological, of sponsored search. As such, the contents are less affected by the ever-changing implementation aspects of technology. Rather than focusing on the how, this book examines what causes the how. Why do certain keywords work, while others do not? Why does that ad work well, when others that are similar do not? Why does a key phrase cost a given amount? Why do we measure what we do in keyword advertising? This book speaks to that curiosity to understand why we do what we do in sponsored search. The content flows through the major components of any sponsored search effort, regardless of the underlying technology or client or product. The book addresses keywords, ads, consumers, pricing, competitors, analytics, branding, marketing and advertising, integrating these separate components into an incorporated whole. The focus is on the critical elements, with ample illustrations and with enough detail to lead the interested reader to further inquiry.
(source: Nielsen Book Data)

• Understanding Web Analytics The Foundations of Web Analytics: Theory and Methods The History of Web Analytics Data Collection for Web Analytics Web Analytics Fundamentals Web Analytics Strategy Web Analytics as Competitive Intelligence Supplementary Methods for Augmenting Web Analytics Search Log Analytics Conclusion Key Terms Blogs for Further Reading References.
• (source: Nielsen Book Data)

This lecture presents an overview of the Web analytics process, with a focus on providing insight and actionable outcomes from collecting and analyzing Internet data. The lecture first provides an overview of Web analytics, providing in essence, a condensed version of the entire lecture. The lecture then outlines the theoretical and methodological foundations of Web analytics in order to make obvious the strengths and shortcomings of Web analytics as an approach. These foundational elements include the psychological basis in behaviorism and methodological underpinning of trace data as an empirical method. These foundational elements are illuminated further through a brief history of Web analytics from the original transaction log studies in the 1960s through the information science investigations of library systems to the focus on Websites, systems, and applications. Following a discussion of on-going interaction data within the clickstream created using log files and page tagging for analytics of Website and search logs, the lecture then presents a Web analytic process to convert these basic data to meaningful key performance indicators in order to measure likely converts that are tailored to the organizational goals or potential opportunities. Supplementary data collection techniques are addressed, including surveys and laboratory studies. The overall goal of this lecture is to provide implementable information and a methodology for understanding Web analytics in order to improve Web systems, increase customer satisfaction, and target revenue through effective analysis of user-Website interactions.
(source: Nielsen Book Data)

• Understanding Web Analytics The Foundations of Web Analytics: Theory and Methods The History of Web Analytics Data Collection for Web Analytics Web Analytics Fundamentals Web Analytics Strategy Web Analytics as Competitive Intelligence Supplementary Methods for Augmenting Web Analytics Search Log Analytics Conclusion Key Terms Blogs for Further Reading References.
• (source: Nielsen Book Data)

This lecture presents an overview of the Web analytics process, with a focus on providing insight and actionable outcomes from collecting and analyzing Internet data. The lecture first provides an overview of Web analytics, providing in essence, a condensed version of the entire lecture. The lecture then outlines the theoretical and methodological foundations of Web analytics in order to make obvious the strengths and shortcomings of Web analytics as an approach. These foundational elements include the psychological basis in behaviorism and methodological underpinning of trace data as an empirical method. These foundational elements are illuminated further through a brief history of Web analytics from the original transaction log studies in the 1960s through the information science investigations of library systems to the focus on Websites, systems, and applications. Following a discussion of on-going interaction data within the clickstream created using log files and page tagging for analytics of Website and search logs, the lecture then presents a Web analytic process to convert these basic data to meaningful key performance indicators in order to measure likely converts that are tailored to the organizational goals or potential opportunities. Supplementary data collection techniques are addressed, including surveys and laboratory studies. The overall goal of this lecture is to provide implementable information and a methodology for understanding Web analytics in order to improve Web systems, increase customer satisfaction, and target revenue through effective analysis of user-Website interactions.
(source: Nielsen Book Data)

• Section I: The Context Of Web Search:Technological, Social and Organizational Context
• Human Information Behavior and Human Computer Interaction Context
• Research Design.- Section II: How People Search The Web: Search Terms
• Search Queries
• Search Sessions.- Section III: Subjects Of Web Search: E-Commerce Web Searching
• Medical and Health Web Searching
• Sexually-Related Web Searching
• Multimedia Searching.- Section IV: Conclusion: Key Findings, Trends, Further Research and Conclusions.- Subject Index.- Author Index.
• (source: Nielsen Book Data)

"Web Search: Public Searching of the Web", co-authored by Drs. Amanda Spink and Bernard J. Jansen, is one of the first manuscripts that address the human - system interaction of Web searching in a thorough and complete manner. The authors provide an examination of Web searching from multiple levels of analysis, from theoretical overview to detailed study of term usage, and integrate these different levels of analysis into a coherent picture of how people locate information on the Web using search engines. Drawing primarily on their own research and work in the field, the authors present the temporal changes in, the growth of, and the stability of how people interact with Web search engines. Drs. Spink and Jansen present results from an analysis of multiple search engine data sets over a six year period, giving a firsthand account of the emergence of Web searching. They also compare and contrast their findings to the results of other researchers in the field, providing a valuable bibliographic resource. This research is directly relevant to those interested in providing information or services on the Web, along with those who research and study the Web as an information resource. Graduate students, academic and corporate researchers, search engine designers, information architects, and search engine optimizers will find the book of particular benefit.
(source: Nielsen Book Data)

• Cognitive-inspired computing fundamentals
• Cognitive-inspired computing systems
• Cognitive-inspired computing with big data
• Cognitive-inspired intelligent interaction
• AI-assisted cognitive computing approaches
• Brain analysis for cognitive-inspired computing
• Internet of cognitive Things
• Cognitive environment, sensing and data
• Cognitive robots and agents
• Security issue in cognitive-inspired computing
• Test-bed, prototype implementation and applications.

This book contains papers presented at the 2nd International Conference on Cognitive based Information Processing and Applications (CIPA) in Changzhou, China, from September 22 to 23, 2022. The book is divided into a 2-volume series and the papers represent the various technological advancements in network information processing, graphics and image processing, medical care, machine learning, smart cities. It caters to postgraduate students, researchers, and practitioners specializing and working in the area of cognitive-inspired computing and information processing.

• Cognitive-inspired computing fundamentals
• Cognitive-inspired computing systems
• Cognitive-inspired computing with big data
• Cognitive-inspired intelligent interaction
• AI-assisted cognitive computing approaches
• Brain analysis for cognitive-inspired computing
• Internet of cognitive Things
• Cognitive environment, sensing and data
• Cognitive robots and agents
• Security issue in cognitive-inspired computing
• Test-bed, prototype implementation and applications.

This book contains papers presented at the 2nd International Conference on Cognitive based Information Processing and Applications (CIPA) in Changzhou, China, from September 22 to 23, 2022. The book is divided into a 2-volume series and the papers represent the various technological advancements in network information processing, graphics and image processing, medical care, machine learning, smart cities. It caters to postgraduate students, researchers, and practitioners specializing and working in the area of cognitive-inspired computing and information processing.

• Cognitive-inspired computing fundamentals.- Cognitive-inspired computing systems.- Cognitive-inspired computing with big data.- Cognitive-inspired intelligent interaction.- AI-assisted cognitive computing approaches.- Brain analysis for cognitive-inspired computing.- Internet of cognitive Things.- Cognitive environment, sensing and data.- Cognitive robots and agents.- Security issue in cognitive-inspired computing.- Test-bed, prototype implementation and applications.
• (source: Nielsen Book Data)

This book contains papers presented at the International Conference on Cognitive based Information Processing and Applications (CIPA) held during August 21, 2021, online conference (since COVID 19), which is divided into a 2-volume book. The papers in the second volume represent the various technological advancements in network information processing, graphics and image processing, medical care, machine learning, smart cities. It caters to postgraduate students, researchers, and practitioners specializing and working in the area of cognitive-inspired computing and information processing.
(source: Nielsen Book Data)

Reflects on the multifaceted themes of Web use and presents various approaches to log analysis.
(source: Nielsen Book Data)