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Artech House USA
Human-Centered Information Fusion

Human-Centered Information Fusion

By (author)s: David L. Hall, John Jordan
Copyright: 2010
Pages: 316
ISBN: 9781596934351

Information fusion refers to the merging of information from disparate sources with differing conceptual, contextual and typographical representations. Rather than focusing on traditional data fusion applications which have been mainly concerned with physical military targets, this unique resource explores new human-centered trends, such as locations, identity, and interactions of individuals and groups (social networks). Moreover, the book discusses two new major sources of information: human observations and web-based information. This cutting-edge volume presents a new view of multi-sensor data fusion that seeks to address these new developments, explicitly considering the active role of a human user/analyst. Professionals become knowledgeable about the key inputs into this innovative information fusion process, including traditional sensing resources (S-space), dynamic communities of human observers (H-space), and resources such as archived sensor data, blogs, and dynamic news reports from citizen reporters via the Internet (I-space).
Introduction: The Changing Role of Humans in Information Fusion -Introduction. Traditional Views of Data Fusion. New Roles for Humans in Data Fusion. Summary.; Sensing the Human Landscape: Issues and Opportunities -Introduction. Contrasts. Elements of the Human Landscape. Issues in Representing the Human Landscape. Information Overload Versus Other Complications of Human Landscapes: The Case of the STASI. Information Fusion and the Human Landscape. Conclusion.; H-Space: Humans as Observers -Introduction. Source Characterization Challenges. A Framework for Characterizing Observers. Summary.; Global Neighborhood Watch: The Emerging Community of Observers - Emerging Trends in Ad Hoc Global Observations. Humans as Sensors and Sensor Platforms. Reporting Mechanisms. Challenges and Biases in Group Observations. Tasking the Community. Information Management. Crowds as Fusion. Conclusion.; What Does It Mean to Live in a Searchable World? -Introduction. Context. Domains of Change. Looking Ahead. Search and Human-Centered Fusion. ; Data Visualization and Understanding -Introduction. Understanding Visualizations. Success Stories. Commercial Tools. Visualizing Physical Data. Visualizing Nonspatial Data. Lessons and Opportunities.; Beyond Visualization: Sonification -Introduction. Sound as Information. Monitoring Versus Analysis. Acoustic Dimensions of Sound. Psychoacoustics: Dimensions of Human Sound Perception. Auditory Gestalts. Sonification: Design Considerations. Example Sonifications. Application to Cybersecurity. Sonification Software. Conclusions.; Adapting IPB for Human Terrain Understanding: Informational Preparation of the Engagement Space -Introduction. The Traditional (Surface-Centric) IPB Process. IPB Is Continuous. Adapting IPB to JIPOE for the Human Terrain. Summary.; Information Fusion for Civilians: The Prospects of Mega-Collaboration -Introduction. The Role of ICT in Disaster Recovery. Information Fusion Through Mega-Collaborative Processes and Tools. Implications for Design and Development. Conclusions.; Virtual World Technologies - Introduction. Overview of Virtual Worlds. Types of Virtual Worlds. Virtual Worlds and Learning. The Wikipedia Phenomenon. Virtual World Collaboration Tools and Platforms. Lessons from Online, Multiplayer Gaming Communities. Summary.; Information Markets and Related Forms of Collective Processing - Crowdsourcing of Analysis. The Wisdom of Crowds. How Do Crowds Express Wisdom?. What Kinds of Questions Best Lend Themselves to Group Wisdom?. Where Is Error Introduced?. Varieties of Market Experience. Future Directions. FutureMAP: A Brief Case Study. Summary. ; Hybrid Cognition and Situation Awareness: Perspectives for the Future of Human-Centered Fusion -Introduction. Requirements Pull for HCF and SA. Technology Push: Enablers for HCF. The Business Case for Human-Centered Fusion. Prospects for Implementation. Conclusion.; References. About the Authors. Index.;
  • David L. Hall David L. Hall is a professor in the College of Information Sciences and Technology(IST) at The Pennsylvania State University. He is also the author of Mathematical Techniques in Multisensor Data Fusion, Second Edition (Artech House, 2004). Dr. Hall has been named an IEEE fellow for his contributions to data fusion and he is a past recipient of the DoD Joe Mignona National Data Fusion Award. He earned his Ph.D. in Astronomy at The Pennsylvania State University.
  • John Jordan
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