Publication statistics

Pub. period:1991-2012
Pub. count:35
Number of co-authors:63



Co-authors

Number of publications with 3 favourite co-authors:

Katherine M. Everitt:
Brian Ngo:
Tanya Bragin:

 

 

Productive colleagues

James Fogarty's 3 most productive colleagues in number of publications:

John M. Carroll:209
Mary Beth Rosson:142
Scott E. Hudson:113
 
 
 

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James Fogarty

Has also published under the name of:
"James W. Fogarty"

Personal Homepage:
homes.cs.washington.edu/~jfogarty/

 

Publications by James Fogarty (bibliography)

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2012
 
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Roesner, Franziska, Fogarty, James and Kohno, Tadayoshi (2012): User interface toolkit mechanisms for securing interface elements. In: Proceedings of the 2012 ACM Symposium on User Interface Software and Technology 2012. pp. 239-250. Available online

User interface toolkit research has traditionally assumed that developers have full control of an interface. This assumption is challenged by the mashup nature of many modern interfaces, in which different portions of a single interface are implemented by multiple, potentially mutually distrusting developers (e.g., an Android application embedding a third-party advertisement). We propose considering security as a primary goal for user interface toolkits. We motivate the need for security at this level by examining today's mashup scenarios, in which security and interface flexibility are not simultaneously achieved. We describe a security-aware user interface toolkit architecture that secures interface elements while providing developers with the flexibility and expressivity traditionally desired in a user interface toolkit. By challenging trust assumptions inherent in existing approaches, this architecture effectively addresses important interface-level security concerns.

© All rights reserved Roesner et al. and/or ACM Press

2011
 
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Dixon, Morgan, Leventhal, Daniel and Fogarty, James (2011): Content and hierarchy in pixel-based methods for reverse engineering interface structure. In: Proceedings of ACM CHI 2011 Conference on Human Factors in Computing Systems 2011. pp. 969-978. Available online

The rigidity and fragmentation of GUI toolkits are fundamentally limiting the progress and impact of interaction research. Pixel-based methods offer unique potential for addressing these challenges independent of the implementation of any particular interface or toolkit. This work builds upon Prefab, which enables the modification of existing interfaces. We present new methods for hierarchical models of complex widgets, real-time interpretation of interface content, and real-time interpretation of content and hierarchy throughout an entire interface. We validate our new methods through implementations of four applications: stencil-based tutorials, ephemeral adaptation, interface translation, and end-user interface customization. We demonstrate these enhancements in complex existing applications created from different user interface toolkits running on different operating systems.

© All rights reserved Dixon et al. and/or their publisher

2010
 
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Amershi, Saleema, Fogarty, James, Kapoor, Ashish and Tan, Desney (2010): Examining multiple potential models in end-user interactive concept learning. In: Proceedings of ACM CHI 2010 Conference on Human Factors in Computing Systems 2010. pp. 1357-1360. Available online

End-user interactive concept learning is a technique for interacting with large unstructured datasets, requiring insights from both human-computer interaction and machine learning. This note re-examines an assumption implicit in prior interactive machine learning research, that interaction should focus on the question "what class is this object?". We broaden interaction to include examination of multiple potential models while training a machine learning system. We evaluate this approach and find that people naturally adopt revision in the interactive machine learning process and that this improves the quality of their resulting models for difficult concepts.

© All rights reserved Amershi et al. and/or their publisher

 
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Dixon, Morgan and Fogarty, James (2010): Prefab: implementing advanced behaviors using pixel-based reverse engineering of interface structure. In: Proceedings of ACM CHI 2010 Conference on Human Factors in Computing Systems 2010. pp. 1525-1534. Available online

Current chasms between applications implemented with different user interface toolkits make it difficult to implement and explore potentially important interaction techniques in new and existing applications, limiting the progress and impact of human-computer interaction research. We examine an approach based in the single most common characteristic of all graphical user interface toolkits, that they ultimately paint pixels to a display. We present Prefab, a system for implementing advanced behaviors through the reverse engineering of the pixels in graphical interfaces. Informed by how user interface toolkits paint interfaces, Prefab features a separation of the modeling of widget layout from the recognition of widget appearance. We validate Prefab in implementations of three applications: target-aware pointing techniques, Phosphor transitions, and Side Views parameter spectrums. Working only from pixels, we demonstrate a single implementation of these enhancements in complex existing applications created in different user interface toolkits running on different windowing systems.

© All rights reserved Dixon and Fogarty and/or their publisher

 
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Patel, Kayur, Bancroft, Naomi, Drucker, Steven M., Fogarty, James, Ko, Andrew J. and Landay, James A. (2010): Gestalt: integrated support for implementation and analysis in machine learning. In: Proceedings of the 2010 ACM Symposium on User Interface Software and Technology 2010. pp. 37-46. Available online

We present Gestalt, a development environment designed to support the process of applying machine learning. While traditional programming environments focus on source code, we explicitly support both code and data. Gestalt allows developers to implement a classification pipeline, analyze data as it moves through that pipeline, and easily transition between implementation and analysis. An experiment shows this significantly improves the ability of developers to find and fix bugs in machine learning systems. Our discussion of Gestalt and our experimental observations provide new insight into general-purpose support for the machine learning process.

© All rights reserved Patel et al. and/or their publisher

2009
 
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Everitt, Katherine M., Bragin, Tanya, Fogarty, James and Kohno, Tadayoshi (2009): A comprehensive study of frequency, interference, and training of multiple graphical passwords. In: Proceedings of ACM CHI 2009 Conference on Human Factors in Computing Systems 2009. pp. 889-898. Available online

Graphical password systems have received significant attention as one potential solution to the need for more usable authentication, but nearly all prior work makes the unrealistic assumption of studying a single password. This paper presents the first study of multiple graphical passwords to systematically examine frequency of access to a graphical password, interference resulting from interleaving access to multiple graphical passwords, and patterns of access while training multiple graphical passwords. We find that all of these factors significantly impact the ease of authenticating using multiple facial graphical passwords. For example, participants who accessed four different graphical passwords per week were ten times more likely to completely fail to authenticate than participants who accessed a single password once per week. Our results underscore the need for more realistic evaluations of the use of multiple graphical passwords, have a number of implications for the adoption of graphical password systems, and provide a new basis for comparing proposed graphical password systems.

© All rights reserved Everitt et al. and/or ACM Press

 
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Wobbrock, Jacob O., Fogarty, James, Liu, Shih-Yen (Sean), Kimuro, Shunichi and Harada, Susumu (2009): The angle mouse: target-agnostic dynamic gain adjustment based on angular deviation. In: Proceedings of ACM CHI 2009 Conference on Human Factors in Computing Systems 2009. pp. 1401-1410. Available online

We present a novel method of dynamic C-D gain adaptation that improves target acquisition for users with motor impairments. Our method, called the Angle Mouse, adjusts the mouse C-D gain based on the deviation of angles sampled during movement. When angular deviation is low, the gain is kept high. When angular deviation is high, the gain is dropped, making the target bigger in motor-space. A key feature of the Angle Mouse is that, unlike most pointing facilitation techniques, it is target-agnostic, requiring no knowledge of target locations or dimensions. This means that the problem of distractor targets is avoided because adaptation is based solely on the user's behavior. In a study of 16 people, 8 of which had motor impairments, we found that the Angle Mouse improved motor-impaired pointing throughput by 10.3% over the Windows default mouse and 11.0% over sticky icons. For able-bodied users, there was no significant difference among the three techniques, as Angle Mouse throughput was within 1.2% of the default. Thus, the Angle Mouse improved pointing performance for users with motor impairments while remaining unobtrusive for able-bodied users.

© All rights reserved Wobbrock et al. and/or ACM Press

 
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Hoffmann, Raphael, Amershi, Saleema, Patel, Kayur, Wu, Fei, Fogarty, James and Weld, Daniel S. (2009): Amplifying community content creation with mixed initiative information extraction. In: Proceedings of ACM CHI 2009 Conference on Human Factors in Computing Systems 2009. pp. 1849-1858. Available online

Although existing work has explored both information extraction and community content creation, most research has focused on them in isolation. In contrast, we see the greatest leverage in the synergistic pairing of these methods as two interlocking feedback cycles. This paper explores the potential synergy promised if these cycles can be made to accelerate each other by exploiting the same edits to advance both community content creation and learning-based information extraction. We examine our proposed synergy in the context of Wikipedia infoboxes and the Kylin information extraction system. After developing and refining a set of interfaces to present the verification of Kylin extractions as a non primary task in the context of Wikipedia articles, we develop an innovative use of Web search advertising services to study people engaged in some other primary task. We demonstrate our proposed synergy by analyzing our deployment from two complementary perspectives: (1) we show we accelerate community content creation by using Kylin's information extraction to significantly increase the likelihood that a person visiting a Wikipedia article as a part of some other primary task will spontaneously choose to help improve the article's infobox, and (2) we show we accelerate information extraction by using contributions collected from people interacting with our designs to significantly improve Kylin's extraction performance.

© All rights reserved Hoffmann et al. and/or ACM Press

 
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Amershi, Saleema, Fogarty, James, Kapoor, Ashish and Tan, Desney (2009): Overview based example selection in end user interactive concept learning. In: Proceedings of the ACM Symposium on User Interface Software and Technology 2009. pp. 247-256. Available online

Interaction with large unstructured datasets is difficult because existing approaches, such as keyword search, are not always suited to describing concepts corresponding to the distinctions people want to make within datasets. One possible solution is to allow end users to train machine learning systems to identify desired concepts, a strategy known as interactive concept learning. A fundamental challenge is to design systems that preserve end user flexibility and control while also guiding them to provide examples that allow the machine learning system to effectively learn the desired concept. This paper presents our design and evaluation of four new overview based approaches to guiding example selection. We situate our explorations within CueFlik, a system examining end user interactive concept learning in Web image search. Our evaluation shows our approaches not only guide end users to select better training examples than the best performing previous design for this application, but also reduce the impact of not knowing when to stop training the system. We discuss challenges for end user interactive concept learning systems and identify opportunities for future research on the effective design of such systems.

© All rights reserved Amershi et al. and/or their publisher

2008
 
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Fogarty, James, Tan, Desney S., Kapoor, Ashish and Winder, Simon (2008): CueFlik: interactive concept learning in image search. In: Proceedings of ACM CHI 2008 Conference on Human Factors in Computing Systems April 5-10, 2008. pp. 29-38. Available online

Web image search is difficult in part because a handful of keywords are generally insufficient for characterizing the visual properties of an image. Popular engines have begun to provide tags based on simple characteristics of images (such as tags for black and white images or images that contain a face), but such approaches are limited by the fact that it is unclear what tags end users want to be able to use in examining Web image search results. This paper presents CueFlik, a Web image search application that allows end users to quickly create their own rules for re ranking images based on their visual characteristics. End users can then re rank any future Web image search results according to their rule. In an experiment we present in this paper, end users quickly create effective rules for such concepts as "product photos", "portraits of people", and "clipart". When asked to conceive of and create their own rules, participants create such rules as "sports action shot" with images from queries for "basketball" and "football". CueFlik represents both a promising new approach to Web image search and an important study in end user interactive machine learning.

© All rights reserved Fogarty et al. and/or ACM Press

 
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Toomim, Michael, Zhang, Xianhang, Fogarty, James and Landay, James A. (2008): Access control by testing for shared knowledge. In: Proceedings of ACM CHI 2008 Conference on Human Factors in Computing Systems April 5-10, 2008. pp. 193-196. Available online

Controlling the privacy of online content is difficult and often confusing. We present a social access control where users devise simple questions testing shared knowledge instead of constructing authenticated accounts and explicit access control rules. We implemented a prototype and conducted studies to explore the context of photo sharing security, gauge the difficulty of creating shared knowledge questions, measure their resilience to adversarial attack, and evaluate user ability to understand and predict this resilience.

© All rights reserved Toomim et al. and/or ACM Press

 
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Patel, Kayur, Fogarty, James, Landay, James A. and Harrison, Beverly L. (2008): Investigating statistical machine learning as a tool for software development. In: Proceedings of ACM CHI 2008 Conference on Human Factors in Computing Systems April 5-10, 2008. pp. 667-676. Available online

As statistical machine learning algorithms and techniques continue to mature, many researchers and developers see statistical machine learning not only as a topic of expert study, but also as a tool for software development. Extensive prior work has studied software development, but little prior work has studied software developers applying statistical machine learning. This paper presents interviews of eleven researchers experienced in applying statistical machine learning algorithms and techniques to human-computer interaction problems, as well as a study of ten participants working during a five-hour study to apply statistical machine learning algorithms and techniques to a realistic problem. We distill three related categories of difficulties that arise in applying statistical machine learning as a tool for software development: (1) difficulty pursuing statistical machine learning as an iterative and exploratory process, (2) difficulty understanding relationships between data and the behavior of statistical machine learning algorithms, and (3) difficulty evaluating the performance of statistical machine learning algorithms and techniques in the context of applications. This paper provides important new insight into these difficulties and the need for development tools that better support the application of statistical machine learning.

© All rights reserved Patel et al. and/or ACM Press

 
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L, Hao and Fogarty, James (2008): Cascaded Treemaps: Examining the Visibility and Stability of Structure in Treemaps. In: Proceedings of the 2008 Conference on Graphics Interface May 28-30, 2008, Windsor, Ontario, Canada. pp. 259-266.

Treemaps are an important and commonly-used approach to hierarchy visualization, but an important limitation of treemaps is the difficulty of discerning the structure of a hierarchy. This paper presents cascaded treemaps, a new approach to treemap presentation that is based in cascaded rectangles instead of the traditional nested rectangles. Cascading uses less space to present the same containment relationship, and the space savings enable a depth effect and natural padding between siblings in complex hierarchies. In addition, we discuss two general limitations of existing treemap layout algorithms: disparities between node weight and relative node size that are introduced by layout algorithms ignoring the space dedicated to presenting internal nodes, and a lack of stability when generating views of different levels of treemaps as a part of supporting interactive zooming. We finally present a two-stage layout process that addresses both concerns, computing a stable structure for the treemap and then using that structure to consider the presentation of internal nodes when arranging the treemap. All of this work is presented in the context of two large real-world hierarchies, the Java package hierarchy and the eBay auction hierarchy.

© All rights reserved L and Fogarty and/or their publisher

 
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Campbell, Taj, Ngo, Brian and Fogarty, James (2008): Game design principles in everyday fitness applications. In: Proceedings of ACM CSCW08 Conference on Computer-Supported Cooperative Work 2008. pp. 249-252. Available online

The global obesity epidemic has prompted our community to explore the potential for technology to play a stronger role in promoting healthier lifestyles. Although there are several examples of successful games based on focused physical interaction, persuasive applications that integrate into everyday life have had more mixed results. This underscores a need for designs that encourage physical activity while addressing fun, sustainability, and behavioral change. This note suggests a new perspective, inspired in part by the social nature of many everyday fitness applications and by the successful encouragement of long term play in massively multiplayer online games. We first examine the game design literature to distill a set of principles for discussing and comparing applications. We then use these principles to analyze an existing application. Finally, we present Kukini, a design for an everyday fitness game.

© All rights reserved Campbell et al. and/or ACM Press

 
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Harada, Susumu, Lester, Jonathan, Patel, Kayur, Saponas, T. Scott, Fogarty, James, Landay, James A. and Wobbrock, Jacob O. (2008): VoiceLabel: using speech to label mobile sensor data. In: Digalakis, Vassilios, Potamianos, Alexandros, Turk, Matthew, Pieraccini, Roberto and Ivanov, Yuri (eds.) Proceedings of the 10th International Conference on Multimodal Interfaces - ICMI 2008 October 20-22, 2008, Chania, Crete, Greece. pp. 69-76. Available online

 
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Adar, Eytan, Dontcheva, Mira, Fogarty, James and Weld, Daniel S. (2008): Zoetrope: interacting with the ephemeral web. In: Cousins, Steve B. and Beaudouin-Lafon, Michel (eds.) Proceedings of the 21st Annual ACM Symposium on User Interface Software and Technology October 19-22, 2008, Monterey, CA, USA. pp. 239-248. Available online

 
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Harada, Susumu, Lester, Jonathan, Patel, Kayur, Saponas, T. Scott, Fogarty, James, Landay, James A. and Wobbrock, Jacob O. (2008): VoiceLabel: using speech to label mobile sensor data. In: Proceedings of the 2008 International Conference on Multimodal Interfaces 2008. pp. 69-76. Available online

Many mobile machine learning applications require collecting and labeling data, and a traditional GUI on a mobile device may not be an appropriate or viable method for this task. This paper presents an alternative approach to mobile labeling of sensor data called VoiceLabel. VoiceLabel consists of two components: (1) a speech-based data collection tool for mobile devices, and (2) a desktop tool for offline segmentation of recorded data and recognition of spoken labels. The desktop tool automatically analyzes the audio stream to find and recognize spoken labels, and then presents a multimodal interface for reviewing and correcting data labels using a combination of the audio stream, the system's analysis of that audio, and the corresponding mobile sensor data. A study with ten participants showed that VoiceLabel is a viable method for labeling mobile sensor data. VoiceLabel also illustrates several key features that inform the design of other data labeling tools.

© All rights reserved Harada et al. and/or their publisher

2007
 
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Tullio, Joe, Dey, Anind K., Chalecki, Jason and Fogarty, James (2007): How it works: a field study of non-technical users interacting with an intelligent system. In: Proceedings of ACM CHI 2007 Conference on Human Factors in Computing Systems 2007. pp. 31-40. Available online

In order to develop intelligent systems that attain the trust of their users, it is important to understand how users perceive such systems and develop those perceptions over time. We present an investigation into how users come to understand an intelligent system as they use it in their daily work. During a six-week field study, we interviewed eight office workers regarding the operation of a system that predicted their managers' interruptibility, comparing their mental models to the actual system model. Our results show that by the end of the study, participants were able to discount some of their initial misconceptions about what information the system used for reasoning about interruptibility. However, the overarching structures of their mental models stayed relatively stable over the course of the study. Lastly, we found that participants were able to give lay descriptions attributing simple machine learning concepts to the system despite their lack of technical knowledge. Our findings suggest an appropriate level of feedback for user interfaces of intelligent systems, provide a baseline level of complexity for user understanding, and highlight the challenges of making users aware of sensed inputs for such systems.

© All rights reserved Tullio et al. and/or ACM Press

 
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Avrahami, Daniel, Fogarty, James and Hudson, Scott E. (2007): Biases in human estimation of interruptibility: effects and implications for practice. In: Proceedings of ACM CHI 2007 Conference on Human Factors in Computing Systems 2007. pp. 51-60. Available online

People have developed a variety of conventions for negotiating face to face interruptions. The physical distribution of teams, however, together with the use of computer mediated communication and awareness systems, fundamentally alters what information is available to a person considering an interruption of a remote collaborator. This paper presents a detailed comparison between self-reports of interruptibility, collected from participants over extended periods in their actual work environment, and estimates of this interruptibility, provided by a second set of participants based on audio and video recordings. Our results identify activities and environmental cues that affect participants' ability to correctly estimate interruptibility. We show, for example, that a closed office door had a significant effect on observers' estimation of interruptibility, but did not have an effect on participants' reports of their own interruptibility. We discuss our findings and their importance for successful design of computer-mediated communication and awareness systems.

© All rights reserved Avrahami et al. and/or ACM Press

 
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Fogarty, James and Hudson, Scott E. (2007): Toolkit support for developing and deploying sensor-based statistical models of human situations. In: Proceedings of ACM CHI 2007 Conference on Human Factors in Computing Systems 2007. pp. 135-144. Available online

Sensor based statistical models promise to support a variety of advances in human computer interaction, but building applications that use them is currently difficult and potential advances go unexplored. We present Subtle, a toolkit that removes some of the obstacles to developing and deploying applications using sensor based statistical models of human situations. Subtle provides an appropriate and extensible sensing library, continuous learning of personalized models, fully automated high level feature generation, and support for using learned models in deployed applications. By removing obstacles to developing and deploying sensor based statistical models, Subtle makes it easier to explore the design space surrounding sensor based statistical models of human situations. Subtle thus helps to move the focus of human computer interaction research onto applications and datasets, instead of the difficulties of developing and deploying sensor based statistical models.

© All rights reserved Fogarty and Hudson and/or ACM Press

 
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Hoffmann, Raphael, Fogarty, James and Weld, Daniel S. (2007): Assieme: finding and leveraging implicit references in a web search interface for programmers. In: Proceedings of the ACM Symposium on User Interface Software and Technology October 7-10, 2007, Newport, Rhode Island, USA. pp. 13-22. Available online

Programmers regularly use search as part of the development process, attempting to identify an appropriate API for a problem, seeking more information about an API, and seeking samples that show how to use an API. However, neither general-purpose search engines nor existing code search engines currently fit their needs, in large part because the information programmers need is distributed across many pages. We present Assieme, a Web search interface that effectively supports common programming search tasks by combining information from Web-accessible Java Archive (JAR) files, API documentation, and pages that include explanatory text and sample code. Assieme uses a novel approach to finding and resolving implicit references to Java packages, types, and members within sample code on the Web. In a study of programmers performing searches related to common programming tasks, we show that programmers obtain better solutions, using fewer queries, in the same amount of time spent using a general Web search interface.

© All rights reserved Hoffmann et al. and/or ACM Press

 
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Andrew, Adrienne H., Borriello, Gaetano and Fogarty, James (2007): Toward a Systematic Understanding of Suggestion Tactics in Persuasive Technologies. In: Kort, Yvonne de, IJsselsteijn, Wijnand, Midden, Cees J. H., Eggen, Berry and Fogg, B. J. (eds.) PERSUASIVE 2007 - Persuasive Technology, Second International Conference on Persuasive Technology April 26-27, 2007, Palo Alto, CA, USA. pp. 259-270. Available online

2006
 
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Tang, Karen P., Keyani, Pedram, Fogarty, James and Hong, Jason I. (2006): Putting people in their place: an anonymous and privacy-sensitive approach to collecting sensed data in location-based applications. In: Proceedings of ACM CHI 2006 Conference on Human Factors in Computing Systems 2006. pp. 93-102. Available online

The emergence of location-based computing promises new and compelling applications, but raises very real privacy risks. Existing approaches to privacy generally treat people as the entity of interest, often using a fidelity tradeoff to manage the costs and benefits of revealing a person's location. However, these approaches cannot be applied in some applications, as a reduction in precision can render location information useless. This is true of a category of applications that use location data collected from multiple people to infer such information as whether there is a traffic jam on a bridge, whether there are seats available in a nearby coffee shop, when the next bus will arrive, or if a particular conference room is currently empty. We present hitchhiking, a new approach that treats locations as the primary entity of interest. Hitchhiking removes the fidelity tradeoff by preserving the anonymity of reports without reducing the precision of location disclosures. We can therefore support the full functionality of an interesting class of location-based applications without introducing the privacy concerns that would otherwise arise.

© All rights reserved Tang et al. and/or ACM Press

 
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Fogarty, James, Au, Carolyn and Hudson, Scott E. (2006): Sensing from the basement: a feasibility study of unobtrusive and low-cost home activity recognition. In: Proceedings of the ACM Symposium on User Interface Software and Technology 2006. pp. 91-100. Available online

The home deployment of sensor-based systems offers many opportunities, particularly in the area of using sensor-based systems to support aging in place by monitoring an elder's activities of daily living. But existing approaches to home activity recognition are typically expensive, difficult to install, or intrude into the living space. This paper considers the feasibility of a new approach that "reaches into the home" via the existing infrastructure. Specifically, we deploy a small number of low-cost sensors at critical locations in a home's water distribution infrastructure. Based on water usage patterns, we can then infer activities in the home. To examine the feasibility of this approach, we deployed real sensors into a real home for six weeks. Among other findings, we show that a model built on microphone-based sensors that are placed away from systematic noise sources can identify 100% of clothes washer usage, 95% of dishwasher usage, 94% of showers, 88% of toilet flushes, 73% of bathroom sink activity lasting ten seconds or longer, and 81% of kitchen sink activity lasting ten seconds or longer. While there are clear limits to what activities can be detected when analyzing water usage, our new approach represents a sweet spot in the tradeoff between what information is collected at what cost.

© All rights reserved Fogarty et al. and/or ACM Press

2005
 
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Fogarty, James, Baker, Ryan S. and Hudson, Scott E. (2005): Case studies in the use of ROC curve analysis for sensor-based estimates in human computer interaction. In: Graphics Interface 2005 May 9-11, 2005, Victoria, British Columbia, Canada. pp. 129-136. Available online

Applications that use sensor-based estimates face a fundamental tradeoff between true positives and false positives when examining the reliability of these estimates, one that is inadequately described by the straightforward notion of accuracy. To address this tradeoff, this paper examines the use of Receiver Operating Characteristic (ROC) curve analysis, a method that has a long history but is under-appreciated in the human computer interaction research community. We present the fundamentals of ROC analysis, the use of the A' statistic to compute the area under an ROC curve, and the equivalence of A' to the Wilcoxon statistic. We then present several case studies, framed in the context of our work on human interruptibility, demonstrating how ROC analysis can yield better results than analyses based on accuracy. These case studies compare sensor-based estimates with human performance, optimize a feature selection process for the area under the ROC curve, and examine end-user selection of a desirable tradeoff.

© All rights reserved Fogarty et al. and/or their publisher

 
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Fogarty, James, Ko, Andrew J., Aung, Htet Htet, Golden, Elspeth, Tang, Karen P. and Hudson, Scott E. (2005): Examining task engagement in sensor-based statistical models of human interruptibility. In: Proceedings of ACM CHI 2005 Conference on Human Factors in Computing Systems 2005. pp. 331-340. Available online

The computer and communication systems that office workers currently use tend to interrupt at inappropriate times or unduly demand attention because they have no way to determine when an interruption is appropriate. Sensor?based statistical models of human interruptibility offer a potential solution to this problem. Prior work to examine such models has primarily reported results related to social engagement, but it seems that task engagement is also important. Using an approach developed in our prior work on sensor?based statistical models of human interruptibility, we examine task engagement by studying programmers working on a realistic programming task. After examining many potential sensors, we implement a system to log low?level input events in a development environment. We then automatically extract features from these low?level event logs and build a statistical model of interruptibility. By correctly identifying situations in which programmers are non?interruptible and minimizing cases where the model incorrectly estimates that a programmer is non?interruptible, we can support a reduction in costly interruptions while still allowing systems to convey notifications in a timely manner.

© All rights reserved Fogarty et al. and/or ACM Press

2004
 
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Fogarty, James, Hudson, Scott E. and Lai, Jennifer (2004): Examining the robustness of sensor-based statistical models of human interruptibility. In: Dykstra-Erickson, Elizabeth and Tscheligi, Manfred (eds.) Proceedings of ACM CHI 2004 Conference on Human Factors in Computing Systems April 24-29, 2004, Vienna, Austria. pp. 207-214. Available online

Current systems often create socially awkward interruptions or unduly demand attention because they have no way of knowing if a person is busy and should not be interrupted. Previous work has examined the feasibility of using sensors and statistical models to estimate human interruptibility in an office environment, but left open some questions about the robustness of such an approach. This paper examines several dimensions of robustness in sensor-based statistical models of human interruptibility. We show that real sensors can be constructed with sufficient accuracy to drive the predictive models. We also create statistical models for a much broader group of people than was studied in prior work. Finally, we examine the effects of training data quantity on the accuracy of these models and consider tradeoffs associated with different combinations of sensors. As a whole, our analyses demonstrate that sensor-based statistical models of human interruptibility can provide robust estimates for a variety of office workers in a range of circumstances, and can do so with accuracy as good as or better than people. Integrating these models into systems could support a variety of advances in human computer interaction and computer-mediated communication.

© All rights reserved Fogarty et al. and/or ACM Press

 
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Fogarty, James, Lai, Jennifer and Christensen, Jim (2004): Presence versus availability: the design and evaluation of a context-aware communication client. In International Journal of Human-Computer Studies, 61 (3) pp. 299-317. Available online

Although electronic communication plays an important role in the modern workplace, the interruptions created by poorly-timed attempts to communicate are disruptive. Prior work suggests that sharing an indication that a person is currently busy might help to prevent such interruptions, because people could wait for a person to become available before attempting to initiate communication. We present a context-aware communication client that uses the built-in microphones of laptop computers to sense nearby speech. Combining this speech detection sensor data with location, computer, and calendar information, our system models availability for communication, a concept that is distinct from the notion of presence found in widely-used systems. In a 4 week study of the system with 26 people, we examined the use of this additional context. To our knowledge, this is the first-field study to quantitatively examine how people use automatically sensed context and availability information to make decisions about when and how to communicate with colleagues. Participants appear to have used the provided context to as an indication of presence, rather than considering availability. Our results raise the interesting question of whether sharing an indication that a person is currently unavailable will actually reduce inappropriate interruptions.

© All rights reserved Fogarty et al. and/or Academic Press

2003
 
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Hudson, Scott E., Fogarty, James, Atkeson, Christopher, Avrahami, Daniel, Forlizzi, Jodi, Kiesler, Sara, Lee, Johnny and Yang, Jie (2003): Predicting human interruptibility with sensors: a Wizard of Oz feasibility study. In: Cockton, Gilbert and Korhonen, Panu (eds.) Proceedings of the ACM CHI 2003 Human Factors in Computing Systems Conference April 5-10, 2003, Ft. Lauderdale, Florida, USA. pp. 257-264.

 
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Fogarty, James and Hudson, Scott E. (2003): GADGET: a toolkit for optimization-based approaches to interface and display generation. In: Proceedings of the 16th annural ACM Symposium on User Interface Software and Technology November, 2-5, 2003, Vancouver, Canada. pp. 125-134. Available online

Recent work is beginning to reveal the potential of numerical optimization as an approach to generating interfaces and displays. Optimization-based approaches can often allow a mix of independent goals and constraints to be blended in ways that would be difficult to describe algorithmically. While optimization-based techniques appear to offer several potential advantages, further research in this area is hampered by the lack of appropriate tools. This paper presents GADGET, an experimental toolkit to support optimization for interface and display generation. GADGET provides convenient abstractions of many optimization concepts. GADGET also provides mechanisms to help programmers quickly create optimizations, including an efficient lazy evaluation framework, a powerful and configurable optimization structure, and a library of reusable components. Together these facilities provide an appropriate tool to enable exploration of a new class of interface and display generation techniques.

© All rights reserved Fogarty and Hudson and/or ACM Press

 
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Fogarty, James, Forlizzi, Jodi and Hudson, Scott E. (2003): Portrait: Generating Personal Presentations. In: Graphics Interface 2003 June 11-13, 2003, Halifax, Nova Scotia, Canada. pp. 209-216.

2002
 
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Fogarty, James, Forlizzi, Jodi and Hudson, Scott E. (2002): Specifying behavior and semantic meaning in an unmodified layered drawing package. In: Beaudouin-Lafon, Michel (ed.) Proceedings of the 15th annual ACM symposium on User interface software and technology October 27-30, 2002, Paris, France. pp. 61-70. Available online

In order to create and use rich custom appearances, designers are often forced to introduce an unnatural gap into the design process. For example, a designer creating a skin for a music player must separately specify the appearance of the elements in the music player skin and the mapping between these visual elements and the functionality provided by the music player. This gap between appearance and semantic meaning creates a number of problems. We present a set of techniques that allows designers to use their preferred drawing tool to specify both appearance and semantic meaning. We demonstrate our techniques in an unmodified version of Adobe Photoshop, but our techniques are general and adaptable to nearly any layered drawing package.

© All rights reserved Fogarty et al. and/or ACM Press

2001
 
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Carroll, John M., Rosson, Mary Beth, Isenhour, Philip, Ganoe, Craig, Dunlap, Dan, Fogarty, James, Schafer, Wendy and Metre, Christina Van (2001): Designing Our Town: MOOsburg. In International Journal of Human-Computer Studies, 54 (5) pp. 725-751.

MOOsburg is a community-oriented multi-user domain. It was created to enrich the Blacksburg Electronic Village (BEV) by providing real-time, situated interaction and a place-based model for community information. Three versions of MOOsburg have been developed: a classic text-based MOO, a MOO extended to drive a Web-browser, and a Java-based system. The most recent version of MOOsburg is fundamentally different from classic MOOs, supporting distributed system development and management and a direct manipulation approach to navigation. We are currently developing a variety of community-oriented applications, including a virtual science fair and a dispersed natural history museum.

© All rights reserved Carroll et al. and/or Academic Press

 
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Fogarty, James, Forlizzi, Jodi and Hudson, Scott E. (2001): Aesthetic information collages: generating decorative displays that contain information. In: Marks, Joe and Mynatt, Elizabeth D. (eds.) Proceedings of the 14th annual ACM symposium on User interface software and technology November 11 - 14, 2001, Orlando, Florida. pp. 141-150. Available online

Normally, the primary purpose of an information display is to convey information. If information displays can be aesthetically interesting, that might be an added bonus. This paper considers an experiment in reversing this imperative. It describes the Kandinsky system which is designed to create displays which are first aesthetically interesting, and then as an added bonus, able to convey information. The Kandinsky system works on the basis of aesthetic properties specified by an artist (in a visual form). It then explores a space of collages composed from information bearing images, using an optimization technique to find compositions which best maintain the properties of the artist's aesthetic expression.

© All rights reserved Fogarty et al. and/or ACM Press

1991
 
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Granda, Thomas M., McClure, Donald H. and Fogarty, James (1991): The Development of an Altitude Awareness Program: An Integrated Approach. In: Proceedings of the Human Factors Society 35th Annual Meeting 1991. pp. 47-51.

N/R

© All rights reserved Granda et al. and/or Human Factors Society

 
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