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• Acknowledgments Introduction Fundamentals Spatializations for Sensemaking Using Visual Analytics Semantic Interaction Applications that Integrate Semantic Interaction Evaluating Semantic Interaction Discussion and Open Challenges Conclusion References Author's Biography.
• (source: Nielsen Book Data)

This book discusses semantic interaction, a user interaction methodology for visual analytic applications that more closely couples the visual reasoning processes of people with the computation. This methodology affords user interaction on visual data representations that are native to the domain of the data. User interaction in visual analytics systems is critical to enabling visual data exploration. Interaction transforms people from mere viewers to active participants in the process of analyzing and understanding data. This discourse between people and data enables people to understand aspects of their data, such as structure, patterns, trends, outliers, and other properties that ultimately result in insight. Through interacting with visualizations, users engage in sensemaking, a process of developing and understanding relationships within datasets through foraging and synthesis. The book provides a description of the principles of semantic interaction, providing design guidelines for the integration of semantic interaction into visual analytics, examples of existing technologies that leverage semantic interaction, and a discussion of how to evaluate these technologies. Semantic interaction has the potential to increase the effectiveness of visual analytic technologies and opens possibilities for a fundamentally new design space for user interaction in visual analytics systems.
(source: Nielsen Book Data)

• Acknowledgments Introduction Fundamentals Spatializations for Sensemaking Using Visual Analytics Semantic Interaction Applications that Integrate Semantic Interaction Evaluating Semantic Interaction Discussion and Open Challenges Conclusion References Author's Biography.
• (source: Nielsen Book Data)

This book discusses semantic interaction, a user interaction methodology for visual analytic applications that more closely couples the visual reasoning processes of people with the computation. This methodology affords user interaction on visual data representations that are native to the domain of the data. User interaction in visual analytics systems is critical to enabling visual data exploration. Interaction transforms people from mere viewers to active participants in the process of analyzing and understanding data. This discourse between people and data enables people to understand aspects of their data, such as structure, patterns, trends, outliers, and other properties that ultimately result in insight. Through interacting with visualizations, users engage in sensemaking, a process of developing and understanding relationships within datasets through foraging and synthesis. The book provides a description of the principles of semantic interaction, providing design guidelines for the integration of semantic interaction into visual analytics, examples of existing technologies that leverage semantic interaction, and a discussion of how to evaluate these technologies. Semantic interaction has the potential to increase the effectiveness of visual analytic technologies and opens possibilities for a fundamentally new design space for user interaction in visual analytics systems.
(source: Nielsen Book Data)

• Introduction The Query Process and Barriers to Finding Information Online Online Search: An Evolution Search and Discovery Technologies: An Overview Information Access: A Spectrum of Needs and Uses Future Tense: The Next Era in Information Access and Discovery Answer Machines.
• (source: Nielsen Book Data)

The Answer Machine is a practical, non-technical guide to the technologies behind information seeking and analysis. It introduces search and content analytics to software buyers, knowledge managers, and searchers who want to understand and design effective online environments. The book describes how search evolved from an expert-only to an end user tool. It provides an overview of search engines, categorization and clustering, natural language processing, content analytics, and visualization technologies. Detailed profiles for Web search, eCommerce search, eDiscovery, and enterprise search contrast the types of users, uses, tasks, technologies, and interaction designs for each. These variables shape each application, although the underlying technologies are the same. Types of information tasks and the trade-offs between precision and recall, time, volume and precision, and privacy vs. personalization are discussed within this context. The book examines trends toward convenient, context-aware computing, big data and analytics technologies, conversational systems, and answer machines. The Answer Machine explores IBM Watson's DeepQA technology and describes how it is used to answer health care and Jeopardy questions. The book concludes by discussing the implications of these advances: how they will change the way we run our businesses, practice medicine, govern, or conduct our lives in the digital age.
(source: Nielsen Book Data)

• Introduction The Query Process and Barriers to Finding Information Online Online Search: An Evolution Search and Discovery Technologies: An Overview Information Access: A Spectrum of Needs and Uses Future Tense: The Next Era in Information Access and Discovery Answer Machines.
• (source: Nielsen Book Data)

The Answer Machine is a practical, non-technical guide to the technologies behind information seeking and analysis. It introduces search and content analytics to software buyers, knowledge managers, and searchers who want to understand and design effective online environments. The book describes how search evolved from an expert-only to an end user tool. It provides an overview of search engines, categorization and clustering, natural language processing, content analytics, and visualization technologies. Detailed profiles for Web search, eCommerce search, eDiscovery, and enterprise search contrast the types of users, uses, tasks, technologies, and interaction designs for each. These variables shape each application, although the underlying technologies are the same. Types of information tasks and the trade-offs between precision and recall, time, volume and precision, and privacy vs. personalization are discussed within this context. The book examines trends toward convenient, context-aware computing, big data and analytics technologies, conversational systems, and answer machines. The Answer Machine explores IBM Watson's DeepQA technology and describes how it is used to answer health care and Jeopardy questions. The book concludes by discussing the implications of these advances: how they will change the way we run our businesses, practice medicine, govern, or conduct our lives in the digital age.
(source: Nielsen Book Data)

• Human-Computer Interaction and Knowledge Discovery. Hypothesis Generation by Interactive Visual Exploration of Heterogeneous Medical Data / Cagatay Turkay [and others]
• Combining HCI, Natural Language Processing, and Knowledge Discovery -- Potential of IBM Content Analytics as an Assistive Technology in the Biomedical Field / Andreas Holzinger [and others]
• Designing Computer-Based Clinical Guidelines Decision Support by a Clinician / Ljiljana Trtica-Majnarić, Aleksandar Včev
• Opinion Mining on the Web 2.0 -- Characteristics of User Generated Content and Their Impacts / Gerald Petz [and others]
• Evaluation of SHAPD2 Algorithm Efficiency Supported by a Semantic Compression Mechanism in Plagiarism Detection Tasks / Dariusz Adam Ceglarek
• Using Hasse Diagrams for Competence-Oriented Learning Analytics / Michael D. Kickmeier-Rust, Dietrich Albert.

• Towards the Detection of Deception in Interactive Multimedia Environments / Hugo Plácido da Silva [and others]
• Predictive Sentiment Analysis of Tweets: A Stock Market Application / Jasmina Smailović [and others]
• A UI Prototype for Emotion-Based Event Detection in the Live Web / George Valkanas, Dimitrios Gunopulos
• Challenges from Cross-Disciplinary Learning Relevant for KDD Methods in Intercultural HCI Design / Rüdiger Heimgärtner
• Intent Recognition Using Neural Networks and Kalman Filters / Pradipta Biswas [and others]
• HCI Empowered Literature Mining for Cross-Domain Knowledge Discovery / Matjaž Juršič [and others]
• An Interactive Course Analyzer for Improving Learning Styles Support Level / Moushir M. El-Bishouty [and others]
• A Framework for Automatic Identification and Visualization of Mobile Device Functionalities and Usage / Renan H.P. Lima, Moushir M. El-Bishouty, Sabine Graf.

• Crowdsourcing Fact Extraction from Scientific Literature / Christin Seifert [and others]
• Digital Archives: Semantic Search and Retrieval / Dimitris Spiliotopoulos [and others]
• Inconsistency Knowledge Discovery for Longitudinal Data Management: A Model-Based Approach / Roberto Boselli [and others]
• On Knowledge Discovery in Open Medical Data on the Example of the FDA Drug Adverse Event Reporting System for Alendronate (Fosamax) / Pinar Yildirim, Ilyas Ozgur Ekmekci, Andreas Holzinger
• Random Forests for Feature Selection in Non-invasive Brain-Computer Interfacing / David Steyrl, Reinhold Scherer, Gernot R. Müller-Putz
• Knowledge Discovery and Smart Homes. End Users Programming Smart Homes -- A Case Study on Scenario Programming / Gerhard Leitner, Anton J. Fercher, Christian Lassen
• Understanding the Limitations of Eco-feedback: A One-Year Long-Term Study / Lucas Pereira [and others].

• " ... Language in Their Very Gesture" First Steps towards Calm Smart Home Input / John N.A. Brown [and others]
• "Oh, I Say, Jeeves!" A Calm Approach to Smart Home Input / John N.A. Brown [and others]
• Smart Learning Environments. Optimizing Classroom Environment to Support Technology Enhanced Learning / Junfeng Yang, Ronghuai Huang, Yanyan Li
• A Smart Problem Solving Environment / Nguyen-Thinh Le, Niels Pinkwart
• Collaboration Is Smart: Smart Learning Communities / Gabriele Frankl, Sofie Bitter
• Smart Open-Ended Learning Environments That Support Learners Cognitive and Metacognitive Processes / Gautam Biswas, James R. Segedy, John S. Kinnebrew
• Curriculum Optimization by Correlation Analysis and Its Validation / Kohei Takada [and others]
• The Concept of eTextbooks in K-12 Classes from the Perspective of Its Stakeholders / Guang Chen [and others].

• A Multi-dimensional Personalization Approach to Developing Adaptive Learning Systems / Tzu-Chi Yang [and others]
• Extending the AAT Tool with a User-Friendly and Powerful Mechanism to Retrieve Complex Information from Educational Log Data / Stephen Kladich [and others]
• Automating the E-learning Personalization / Fathi Essalmi [and others]
• Teaching Computational Thinking Skills in C3STEM with Traffic Simulation / Anton Dukeman [and others]
• Learning Analytics to Support the Use of Virtual Worlds in the Classroom / Michael D. Kickmeier-Rust, Dietrich Albert
• Visualization and Data Analytics. Evaluation of Optimized Visualization of LiDAR Point Clouds, Based on Visual Perception / Sašo Pečnik, Domen Mongus, Borut Žalik
• Visualising the Attributes of Biological Cells, Based on Human Perception / Denis Horvat [and others]
• Interactive Visual Transformation for Symbolic Representation of Time-Oriented Data / Tim Lammarsch [and others]
• Organizing Documents to Support Activities / Anna Zacchi, Frank M. Shipman III.

• Human-computer interaction and knowledge discovery
• Knowledge discovery and smart homes
• Smart learning environments
• Visualization data analytics.

This book constitutes the refereed proceedings of the Third Workshop on Human-Computer Interaction and Knowledge Discovery, HCI-KDD 2013, held in Maribor, Slovenia, in July 2013, at SouthCHI 2013. The 20 revised papers presented were carefully reviewed and selected from 68 submissions. The papers are organized in topical sections on human-computer interaction and knowledge discovery, knowledge discovery and smart homes, smart learning environments, and visualization data analytics.

• Chapter 1: Mobile biometrics
• Chapter 2: Mobile biometric device design: history and challenges
• Chapter 3: Challenges in developing mass-market mobile biometric sensors
• Chapter 4: Deep neural networks for mobile person recognition with audio-visual signals
• Chapter 5: Active authentication using facial attributes
• Chapter 6: Fusion of shape and texture features for lip biometry in mobile devices
• Chapter 7: Mobile device usage data as behavioral biometrics
• Chapter 8: Continuous mobile authentication using user-phone interaction
• Chapter 9: Smartwatch-based gait biometrics
• Chapter 10: Toward practical mobile gait biometrics
• Chapter 11: 4F (TM)-ID: mobile four-fingers biometrics system
• Chapter 12: Palmprint recognition on mobile devices
• Chapter 13: Addressing the presentation attacks using periocular region for smartphone biometrics
• Chapter 14: Countermeasures to face photo spoofing attacks by exploiting structure and texture information from rotated face sequences
• Chapter 15: Biometric antispoofing on mobile devices
• Chapter 16: Biometric open protocol standard
• Chapter 17: Big data and cloud identity service for mobile authentication
• Chapter 18: Outlook for mobile biometrics.
• (source: Nielsen Book Data)

Mobile biometrics - the use of physical and/or behavioral characteristics of humans to allow their recognition by mobile/smart phones - aims to achieve conventional functionality and robustness while also supporting portability and mobility, bringing greater convenience and opportunity for its deployment in a wide range of operational environments from consumer applications to law enforcement. But achieving these aims brings new challenges such as issues with power consumption, algorithm complexity, device memory limitations, frequent changes in operational environment, security, durability, reliability, and connectivity. Mobile Biometrics provides a timely survey of the state of the art research and developments in this rapidly growing area. Topics covered in Mobile Biometrics include mobile biometric sensor design, deep neural network for mobile person recognition with audio-visual signals, active authentication using facial attributes, fusion of shape and texture features for lip biometry in mobile devices, mobile device usage data as behavioral biometrics, continuous mobile authentication using user phone interaction, smartwatch-based gait biometrics, mobile four-fingers biometrics system, palm print recognition on mobile devices, periocular region for smartphone biometrics, and face anti-spoofing on mobile devices.
(source: Nielsen Book Data)

• 1. Building an effective UI
• 2. Building the case for better UX
• 3. Effective planning and requirements
• 4. Bringing together a team
• 5. Getting the business perspective
• 6. Getting to know the user
• 7. Initial product architecture
• 8. iterative development process
• 9. Release and post-release.

Many companies recognize that people expect effortless, engaging interaction with desktop and web applications, but producing software that generates enjoyable user experiences is much harder than they anticipate. With "Effective UI", you'll learn proven user-experience strategies that will satisfy your clients and customers, drive business value, and increase brand strength. This book shows you how to capture the collaborative and cooperative spirit among designers, engineers, and management required for building engaging software.
(source: Nielsen Book Data)