Number of co-authors:40
Number of publications with 3 favourite co-authors:Allen Cypher:Mira Dontcheva:Jeffrey P. Bigham:
Tessa Lau's 3 most productive colleagues in number of publications:Steve Whittaker:67Michael J. Muller:65John Riedl:61
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Publications by Tessa Lau (bibliography)
Pedemonte, Pablo, Mahmud, Jalal and Lau, Tessa (2012): Towards automatic functional test execution. In: Proceedings of the 2012 International Conference on Intelligent User Interfaces 2012. pp. 227-236. http://dx.doi.org/10.1145/2166966.2167005
As applications are developed, functional tests ensure they continue to function as expected. Nowadays, functional testing is mostly done manually, with human testers verifying a system's functionality themselves, following hand-written instructions. While there exist tools supporting functional test automation, in practice they are hard to use, require programming skills, and do not provide good support for test maintenance. In this paper, we take an alternative approach: we semi-automatically convert hand-written instructions into automated tests. Our approach consists of two stages: first, employing machine learning and natural language processing to compute an intermediate representation from test steps; and second, interactively disambiguating that representation to create a fully automated test. These two stages comprise a complete system for converting hand-written functional tests into automated tests. We also present a quantitative study analyzing the effectiveness of our approach. Our results show that 70% of manual test steps can be automatically converted to automated test steps with no user intervention.
© All rights reserved Pedemonte et al. and/or ACM Press
Lasecki, Walter, Lau, Tessa, He, Grant and Bigham, Jeffrey (2012): Crowd-based recognition of web interaction patterns. In: Adjunct Proceedings of the 2012 ACM Symposium on User Interface Software and Technology 2012. pp. 99-100. http://dx.doi.org/10.1145/2380296.2380341
Web automation often involves users describing complex tasks to a system, with directives generally limited to low-level constituent actions like "click the search button." This level of description is unnatural and makes it difficult to generalize the task across websites. In this paper, we propose a system for automatically recognizing higher-level interaction patterns from user's completion of tasks, such as "searching for cat videos" or "replying to a post". We present PatFinder, a system that identifies these patterns using the input of crowd workers. We validate the system by generating data for 10 tasks, having 62 crowd workers label them, and automatically extracting 14 interaction patterns. Our results show that the number of patterns grows sublinearly with the number of tasks, suggesting that a small finite set of patterns may suffice to describe the vast majority of tasks on the web.
© All rights reserved Lasecki et al. and/or ACM Press
Mahmud, Jalal, Matthews, Tara, Whittaker, Steve, Moran, Tom and Lau, Tessa (2011): Topika: integrating collaborative sharing with email. In: Proceedings of ACM CHI 2011 Conference on Human Factors in Computing Systems 2011. pp. 3161-3164. http://dx.doi.org/10.1145/1978942.1979410
New enterprise tools (wikis, team spaces, social tags) offer potential benefits for enterprise collaboration, providing shared resources to organize work. However, a vast amount of collaboration still takes place by email. But email is problematic for collaboration because information may be distributed across multiple messages in an overloaded inbox. Email also increases workload as each individual has to manage their own versions of collaborative materials. We present a novel system, Topika that integrates email with collaboration tools. It allows users to continue to use email while also enjoying the benefits of these dedicated tools. When a user composes an email Topika analyzes the message and suggests relevant shared spaces (e.g., wiki pages) within the user's collaboration tools. This allows her to post the email to those spaces. An evaluation of Topika's suggestion algorithm shows that it performs well at accurately suggesting shared spaces.
© All rights reserved Mahmud et al. and/or their publisher
Li, Ian, Nichols, Jeffrey, Lau, Tessa, Drews, Clemens and Cypher, Allen (2010): Here's what i did: sharing and reusing web activity with ActionShot. In: Proceedings of ACM CHI 2010 Conference on Human Factors in Computing Systems 2010. pp. 723-732. http://doi.acm.org/10.1145/1753326.1753432
ActionShot is an integrated web browser tool that creates a fine-grained history of users' browsing activities by continually recording their browsing actions at the level of interactions, such as button clicks and entries into form fields. ActionShot provides interfaces to facilitate browsing and searching through this history, sharing portions of the history through established social networking tools such as Facebook, and creating scripts that can be used to repeat previous interactions at a later time. ActionShot can also create short textual summaries for sequences of interactions. In this paper, we describe the ActionShot and our initial explorations of the tool through field deployments within our organization and a lab study. Overall, we found that ActionShot's history features provide value beyond typical browser history interfaces.
© All rights reserved Li et al. and/or their publisher
Mahmud, Jalal and Lau, Tessa (2010): Lowering the barriers to website testing with CoTester. In: Proceedings of the 2010 International Conference on Intelligent User Interfaces 2010. pp. 169-178. http://doi.acm.org/10.1145/1719970.1719994
In this paper, we present CoTester, a system designed to decrease the difficulty of testing web applications. CoTester allows testers to create test scripts that are represented in an easy-to-understand scripting language rather than a complex programming language, which allows tests to be created rapidly and by non-developers. CoTester improves the management of test scripts by grouping sequences of lowlevel actions into subroutines, such as "log in" or "check out shopping cart", which help testers visualize test structure and make bulk modifications. A key innovation in CoTester is its ability to automatically identify these subroutines using a machine learning algorithm. Our algorithm is able to achieve 91% accuracy at recognizing a set of 7 representative subroutines commonly found in test scripts.
© All rights reserved Mahmud and Lau and/or their publisher
Lau, Tessa, Cerruti, Julian, Manzato, Guillermo, Bengualid, Mateo, Bigham, Jeffrey P. and Nichols, Jeffrey (2010): A conversational interface to web automation. In: Proceedings of the 2010 ACM Symposium on User Interface Software and Technology 2010. pp. 229-238. http://doi.acm.org/10.1145/1866029.1866067
This paper presents CoCo, a system that automates web tasks on a user's behalf through an interactive conversational interface. Given a short command such as "get road conditions for highway 88," CoCo synthesizes a plan to accomplish the task, executes it on the web, extracts an informative response, and returns the result to the user as a snippet of text. A novel aspect of our approach is that we leverage a repository of previously recorded web scripts and the user's personal web browsing history to determine how to complete each requested task. This paper describes the design and implementation of our system, along with the results of a brief user study that evaluates how likely users are to understand what CoCo does for them.
© All rights reserved Lau et al. and/or their publisher
Cypher, Allen, Lau, Tessa, Nichols, Jeffrey and Dontcheva, Mira (2009): Workshop on end user programming for the web. In: Proceedings of ACM CHI 2009 Conference on Human Factors in Computing Systems 2009. pp. 4779-4782. http://doi.acm.org/10.1145/1520340.1520739
In the past several years, there has been a resurgence in research activity in end user programming (EUP), all focused on the web. This work is spread across a variety of institutions and has been published in a variety of conference venues, including CHI, UIST, IUI, and WWW. This workshop will bring these researchers together for a common discussion, with the following goals: establish a sense of community amongst researchers in this area; discuss common problems and lessons learned about doing research in EUP for the web; define a standard corpus of tasks that can be used to evaluate current and future EUP systems; and plan the publication of an edited book on the topic of end user programming for the web.
© All rights reserved Cypher et al. and/or ACM Press
Bigham, Jeffrey P., Lau, Tessa and Nichols, Jeffrey (2009): Trailblazer: enabling blind users to blaze trails through the web. In: Proceedings of the 2009 International Conference on Intelligent User Interfaces 2009. pp. 177-186. http://doi.acm.org/10.1145/1502650.1502677
For blind web users, completing tasks on the web can be frustrating. Each step can require a time-consuming linear search of the current web page to find the needed interactive element or piece of information. Existing interactive help systems and the playback components of some programming-by-demonstration tools identify the needed elements of a page as they guide the user through predefined tasks, obviating the need for a linear search on each step. We introduce TrailBlazer, a system that provides an accessible, non-visual interface to guide blind users through existing how-to knowledge. A formative study indicated that participants saw the value of TrailBlazer but wanted to use it for tasks and web sites for which no existing script was available. To address this, TrailBlazer offers suggestion-based help created on-the-fly from a short, user-provided task description and an existing repository of how-to knowledge. In an evaluation on 15 tasks, the correct prediction was contained within the top 5 suggestions 75.9% of the time.
© All rights reserved Bigham et al. and/or their publisher
Leshed, Gilly, Haber, Eben M., Matthews, Tara and Lau, Tessa (2008): CoScripter: automating & sharing how-to knowledge in the enterprise. In: Proceedings of ACM CHI 2008 Conference on Human Factors in Computing Systems April 5-10, 2008. pp. 1719-1728. http://doi.acm.org/10.1145/1357054.1357323
Modern enterprises are replete with numerous online processes. Many must be performed frequently and are tedious, while others are done less frequently yet are complex or hard to remember. We present interviews with knowledge workers that reveal a need for mechanisms to automate the execution of and to share knowledge about these processes. In response, we have developed the CoScripter system (formerly Koala ), a collaborative scripting environment for recording, automating, and sharing web-based processes. We have deployed CoScripter within a large corporation for more than 10 months. Through usage log analysis and interviews with users, we show that CoScripter has addressed many user automation and sharing needs, to the extent that more than 50 employees have voluntarily incorporated it into their work practice. We also present ways people have used CoScripter and general issues for tools that support automation and sharing of how-to knowledge.
© All rights reserved Leshed et al. and/or ACM Press
Nichols, Jeffrey and Lau, Tessa (2008): Mobilization by demonstration: using traces to re-author existing web sites. In: Proceedings of the 2008 International Conference on Intelligent User Interfaces 2008. pp. 149-158. http://doi.acm.org/10.1145/1378773.1378793
Today's web pages provide many useful features, but unfortunately nearly all are designed first and foremost for the desktop form factor. At the same time, the number of mobile devices with different form factors and unique input and output facilities is growing substantially. The Highlight re-authoring environment addresses these problems by allowing users to start with existing sites they already use and create mobile versions that are customized to their tasks and mobile devices. This "re-authoring" is performed through a combination of demonstrating desired interactions with an existing web site and directly specifying content to be included on mobile pages. The system has been tested successfully with a variety of existing sites. A study showed that novice users were able to use the system to create useful mobile applications for sites of their own choosing.
© All rights reserved Nichols and Lau and/or ACM Press
Tang, John C., Drews, Clemens, Smith, Mark, Wu, Fei, Sue, Alison and Lau, Tessa (2007): Exploring patterns of social commonality among file directories at work. In: Proceedings of ACM CHI 2007 Conference on Human Factors in Computing Systems 2007. pp. 951-960. http://doi.acm.org/10.1145/1240624.1240769
We studied files stored by members of a work organization for patterns of social commonality. Discovering identical or similar documents, applications, developer libraries, or other files may suggest shared interests or experience among users. Examining actual file data revealed a number of individual and aggregate practices around file storage. For example, pairs of users typically have many (over 13,000) files in common. A prototype called LiveWire exploits this commonality to make file backup and restore more efficient for a work organization. We removed commonly shared files and focused on specific filetypes that represent user activity to find more meaningful files in common. The Consolidarity project explores how patterns of file commonality could encourage social networking in an organizational context. Mechanisms for addressing the privacy concerns raised by this approach are discussed.
© All rights reserved Tang et al. and/or ACM Press
Farrell, Stephen, Lau, Tessa, Nusser, Stefan, Wilcox, Eric and Muller, Michael J. (2007): Socially augmenting employee profiles with people-tagging. In: Proceedings of the ACM Symposium on User Interface Software and Technology October 7-10, 2007, Newport, Rhode Island, USA. pp. 91-100. http://doi.acm.org/10.1145/1294211.1294228
Employee directories play a valuable role in helping people find others to collaborate with, solve a problem, or provide needed expertise. Serving this role successfully requires accurate and up-to-date user profiles, yet few users take the time to maintain them. In this paper, we present a system that enables users to tag other users with key words that are displayed on their profiles. We discuss how people-tagging is a form of social bookmarking that enables people to organize their contacts into groups, annotate them with terms supporting future recall, and search for people by topic area. In addition, we show that people-tagging has a valuable side benefit: it enables the community to collectively maintain each others' interest and expertise profiles. Our user studies suggest that people tag other people as a form of contact management and that the tags they have been given are accurate descriptions of their interests and expertise. Moreover, none of the people interviewed reported offensive or inappropriate tags. Based on our results, we believe that peopletagging will become an important tool for relationship management in an organization.
© All rights reserved Farrell et al. and/or ACM Press
Dredze, Mark, Lau, Tessa and Kushmerick, Nicholas (2006): Automatically classifying emails into activities. In: Proceedings of the 2006 International Conference on Intelligent User Interfaces 2006. pp. 70-77. http://doi.acm.org/10.1145/1111449.1111471
Email-based activity management systems promise to give users better tools for managing increasing volumes of email, by organizing email according to a user's activities. Current activity management systems do not automatically classify incoming messages by the activity to which they belong, instead relying on simple heuristics (such as message threads), or asking the user to manually classify incoming messages as belonging to an activity. This paper presents several algorithms for automatically recognizing emails as part of an ongoing activity. Our baseline methods are the use of message reply-to threads to determine activity membership and a naive Bayes classifier. Our SimSubset and SimOverlap algorithms compare the people involved in an activity against the recipients of each incoming message. Our SimContent algorithm uses IRR (a variant of latent semantic indexing) to classify emails into activities using similarity based on message contents. An empirical evaluation shows that each of these methods provide a significant improvement to the baseline methods. In addition, we show that a combined approach that votes the predictions of the individual methods performs better than each individual method alone.
© All rights reserved Dredze et al. and/or ACM Press
Bergman, Lawrence, Castelli, Vittorio, Lau, Tessa and Oblinger, Daniel (2005): DocWizards: a system for authoring follow-me documentation wizards. In: Proceedings of the 2005 ACM Symposium on User Interface Software and Technology 2005. pp. 191-200. http://doi.acm.org/10.1145/1095034.1095067
Traditional documentation for computer-based procedures is difficult to use: readers have trouble navigating long complex instructions, have trouble mapping from the text to display widgets, and waste time performing repetitive procedures. We propose a new class of improved documentation that we call follow-me documentation wizards. Follow-me documentation wizards step a user through a script representation of a procedure by highlighting portions of the text, as well application UI elements. This paper presents algorithms for automatically capturing follow-me documentation wizards by demonstration, through observing experts performing the procedure. We also present our DocWizards implementation on the Eclipse platform. We evaluate our system with an initial user study that showing that most users have a marked preference for this form of guidance over traditional documentation.
© All rights reserved Bergman et al. and/or ACM Press
Danis, Catalina, Kellogg, Wendy A., Lau, Tessa, Dredze, Mark, Stylos, Jeffrey and Kushmerick, Nicholas (2005): Managers' email: beyond tasks and to-dos. In: Proceedings of ACM CHI 2005 Conference on Human Factors in Computing Systems 2005. pp. 1324-1327. http://doi.acm.org/10.1145/1056808.1056907
In this paper, we describe preliminary findings that indicate that managers and non-mangers think about their email differently. We asked three research managers and three research non-managers to sort about 250 of their own email messages into categories that "would help them to manage their work." Our analyses indicate that managers create more categories and a more differentiated category structure than non-managers. Our data also suggest that managers create "relationship-oriented" categories more often than non-managers. These results are relevant to research on "email overload" that has highlighted the use of email for activities beyond communication. In particular, our findings suggest that too strong a focus on task management may be incomplete, and that a user's organizational role has an impact on their conceptualization and likely use of email.
© All rights reserved Danis et al. and/or ACM Press
Riedl, John, Jameson, Anthony, Billsus, Daniel and Lau, Tessa (eds.) Proceedings of the 10th international conference on Intelligent user interfaces January 10-13, 2005, San Diego, California, USA.
Lau, Tessa, Bergman, Lawrence, Castelli, Vittorio and Oblinger, Daniel (2004): Sheepdog: learning procedures for technical support. In: Nunes, Nuno Jardim and Rich, Charles (eds.) International Conference on Intelligent User Interfaces 2004 January 13-16, 2004, Funchal, Madeira, Portugal. pp. 109-116. http://doi.acm.org/10.1145/964442.964464
Technical support procedures are typically very complex. Users often have trouble following printed instructions describing how to perform these procedures, and these instructions are difficult for support personnel to author clearly. Our goal is to learn these procedures by demonstration, watching multiple experts performing the same procedure across different operating conditions, and produce an executable procedure that runs interactively on the user's desktop. Most previous programming by demonstration systems have focused on simple programs with regular structure, such as loops with fixed-length bodies. In contrast, our system induces complex procedure structure by aligning multiple execution traces covering different paths through the procedure. This paper presents a solution to this alignment problem using Input/Output Hidden Markov Models. We describe the results of a user study that examines how users follow printed directions. We present Sheepdog, an implemented system for capturing, learning, and playing back technical support procedures on the Windows desktop. Finally, we empirically evalute our system using traces gathered from the user study and show that we are able to achieve 73% accuracy on a network configuration task using a procedure trained by non-experts.
© All rights reserved Lau et al. and/or ACM Press
Bergman, Lawrence and Lau, Tessa (2004): Workshop on behavior-based user interface customization. In: Nunes, Nuno Jardim and Rich, Charles (eds.) International Conference on Intelligent User Interfaces 2004 January 13-16, 2004, Funchal, Madeira, Portugal. pp. 372-373. http://doi.acm.org/10.1145/964442.964540
Gaeremynck, Yves, Bergman, Lawrence and Lau, Tessa (2003): MORE for less: model recovery from visual interfaces for multi-device application design. In: Johnson, Lewis and Andre, Elisabeth (eds.) International Conference on Intelligent User Interfaces 2003 January 12-15, 2003, Miami, Florida, USA. pp. 69-76. http://doi.acm.org/10.1145/604045.604060
An emerging approach to multi-device application development requires developers to build an abstract semantic model that is translated into specific implementations for web browsers, PDAs, voice systems and other user interfaces. Specifying abstract semantics can be difficult for designers accustomed to working with concrete screen-oriented layout. We present an approach to model recovery: inferring semantic models from existing applications, enabling developers to use familiar tools but still reap the benefits of multi-device deployment. We describe MORE, a system that converts the visual layout of HTML forms into a semantic model with explicit captions and logical grouping. We evaluate MOREs performance on forms from existing Web applications, and demonstrate that in most cases the difference between the recovered model and a hand-authored model is under 5%.
© All rights reserved Gaeremynck et al. and/or ACM Press
Bergman, Lawrence, Gaeremynck, Yves and Lau, Tessa (2003): MORE: model recovery from visual interfaces for multi-device application design. In: Johnson, Lewis and Andre, Elisabeth (eds.) International Conference on Intelligent User Interfaces 2003 January 12-15, 2003, Miami, Florida, USA. p. 318. http://doi.acm.org/10.1145/604045.604111
Lau, Tessa and Weld, Daniel S. (1999): Programming by Demonstration: An Inductive Learning Formulation. In: Maybury, Mark T. (ed.) International Conference on Intelligent User Interfaces 1999 January 5-8, 1999, Redondo Beach, California, USA. pp. 145-152. http://www.acm.org/pubs/articles/proceedings/uist/291080/p145-lau/p145-lau.pdf
Although Programming by Demonstration (PBD) has the potential to improve the productivity of unsophisticated users, previous PBD systems have used brittle, heuristic, domain-specific approaches to execution-trace generalization. In this paper we define two application-independent methods for performing generalization that are based on well-understood machine learning technology. TGENVS uses version-space generalization, and TGENFOIL is based on the FOIL inductive logic programming algorithm. We analyze each method both theoretically and empirically, arguing that TGENVS has lower sample complexity, but TGENFOIL can learn a much more interesting class of programs.
© All rights reserved Lau and Weld and/or ACM Press
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