Number of co-authors:20
Number of publications with 3 favourite co-authors:Tessa Lau:5Vittorio Castelli:5Jie Lu:3
Lawrence Bergman's 3 most productive colleagues in number of publications:Tessa Lau:21Jie Lu:20Bamshad Mobasher:18
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Publications by Lawrence Bergman (bibliography)
Sharmin, Moushumi, Bergman, Lawrence, Lu, Jie and Konuru, Ravi (2012): On slide-based contextual cues for presentation reuse. In: Proceedings of the 2012 International Conference on Intelligent User Interfaces 2012. pp. 129-138.
Reuse of existing presentation materials is prevalent among knowledge workers. However, finding the most appropriate material for reuse is challenging. Existing information management and search tools provide inadequate support for reuse due to their dependence on users' ability to effectively categorize, recall, and recognize existing materials. Based on our findings from an online survey and contextual interviews, we designed and implemented a slide-based contextual recommender, ConReP, for supporting reuse of presentation materials. ConReP utilizes a user-selected slide as a search-key, recommends materials based on similarity to the selected slide, and provides a local-context-based visual representation of the recommendations. Users input provides new insight into presentation reuse and reveals that slide-based search is more effective than keyword-based search, local-context-based visual representation helps in better recall and recognition, and shows the promise of this general approach of exploiting individual slides and local-context for better presentation reuse.
© All rights reserved Sharmin et al. and/or ACM Press
Mejova, Yelena, Schepper, Klaar De, Bergman, Lawrence and Lu, Jie (2011): Reuse in the wild: an empirical and ethnographic study of organizational content reuse. In: Proceedings of ACM CHI 2011 Conference on Human Factors in Computing Systems 2011. pp. 2877-2886.
We present a large-scale study of content reuse networks in a large and highly hierarchical organization. In our study, we combine analysis of a collection of presentations produced by employees with interviews conducted throughout the organization and a survey to study presentation content reuse. Study results show a variety of information needs and behaviors related to content reuse as well as a need for a personalized and socially-integrated networking tool for enabling easy access to previously generated presentation material. In this paper we describe our findings and outline a set of requirements for an effective content reuse facility.
© All rights reserved Mejova et al. and/or their publisher
Bergman, Lawrence, Lu, Jie, Konuru, Ravi, MacNaught, Julie and Yeh, Danny (2010): Outline wizard: presentation composition and search. In: Proceedings of the 2010 International Conference on Intelligent User Interfaces 2010. pp. 209-218.
Presentation material is a commonly-performed task. Yet current tools provide inadequate support -- search tools are unable to return individual slides, and the linear model employed by presentation creation tools lacks structure and context. We propose a novel method for presentation creation, implemented in a tool called Outline Wizard, which enables outline-based composition and search. An Outline Wizard user enters a hierarchically-structured outline of a presentation; using that structure, the tool extracts user requests to formulate contextual queries, matches them against presentations within a repository, taking into account both content and structures of the presentations, and presents the user with sets of slides that are appropriate for each outline topic. At the heart of Outline Wizard is an outline-based search technique, which conducts content search within the context derived from the hierarchical structures of both user requests and presentations. We present a heuristic outline-extraction technique, which is used to reverse engineer the structures of presentations, thereby making the structures available for our search engine. Evaluations show that the outline extraction technique and outline-based search both perform well, and that users report a satisfying experience when using Outline Wizard to compose presentations from libraries of existing material.
© All rights reserved Bergman et al. and/or their publisher
Bao, Xinlong, Bergman, Lawrence and Thompson, Rich (2009): Stacking recommendation engines with additional meta-features. In: Proceedings of the 2009 ACM Conference on Recommender Systems 2009. pp. 109-116.
In this paper, we apply stacking, an ensemble learning method, to the problem of building hybrid recommendation systems. We also introduce the novel idea of using runtime metrics which represent properties of the input users/items as additional meta-features, allowing us to combine component recommendation engines at runtime based on user/item characteristics. In our system, component engines are level-1 predictors, and a level-2 predictor is learned to generate the final prediction of the hybrid system. The input features of the level-2 predictor are predictions from component engines and the runtime metrics. Experimental results show that our system outperforms each single component engine as well as a static hybrid system. Our method has the additional advantage of removing restrictions on component engines that can be employed; any engine applicable to the target recommendation task can be easily plugged into the system.
© All rights reserved Bao et al. and/or ACM Press
Bergman, Lawrence, Kim, Jihie, Mobasher, Bamshad, Rueger, Stefan, Siersdorfer, Stefan, Sizov, Sergej and Stolze, Markus (2008): International workshop on recommendation and collaboration (ReColl 2008). In: Proceedings of the 2008 International Conference on Intelligent User Interfaces 2008. p. 439.
The International Workshop on Recommendation and Collaboration (ReColl 2008) aims to identify emerging trends in recommendation technology and collaborative environments in the context of intelligent user interfaces. We explore these two topics separately and the synergies between them.
© All rights reserved Bergman et al. and/or ACM Press
Castelli, Vittorio and Bergman, Lawrence (2007): Distributed augmentation-based learning: a learning algorithm for distributed collaborative programming-by-demonstration. In: Proceedings of the 2007 International Conference on Intelligent User Interfaces 2007. pp. 160-169.
The learning algorithms used in Programming-by-Demonstration (PBD) are either on-line and incremental or off-line and batch. Neither category is entirely suitable for capturing know-how from demonstrations in a distributed, collaborative environment, where multiple experts can independently provide examples to improve the model. In this paper we describe Distributed Augmentation-Based Learning (DABL), the first real-time PBD learning algorithm suited for distributed know-how acquisition. DABL is an incremental learning algorithm that uses a version-control-like paradigm to combine independently constructed procedure models. An expert can check out a procedure model from a repository and modify it by means of new demonstrations or by manually editing it. The expert then reconciles the changes with those concurrently made by other experts and checked into the repository. DABL automatically merges the two procedures, learns new decision points based on reconcilable differences, and identifies conflicts where there are multiple valid ways of combining the changes or where the combination produces an invalid model, that is, one that does not lie in the search space of the learning algorithm.
© All rights reserved Castelli and Bergman and/or ACM Press
Prabaker, Madhu, Bergman, Lawrence and Castelli, Vittorio (2006): An evaluation of using programming by demonstration and guided walkthrough techniques for authoring and utilizing documentation. In: Proceedings of ACM CHI 2006 Conference on Human Factors in Computing Systems 2006. pp. 241-250.
Much existing documentation is informal and serves to communicate "how-to" knowledge among restricted working groups. Using current practices, such documentation is both difficult to maintain and difficult to use properly. In this paper, we propose a documentation system, called DocWizards, that uses programming by demonstration to support low-cost authoring and guided walkthrough techniques to improve document usability. We report a comparative study between the use of DocWizards and traditional techniques for authoring and following documentation. The study participants showed significant gains in efficiency and reduction in error rates when using DocWizards. In addition, they expressed a clear preference for using the DocWizards tool, both for authoring and for following documentation.
© All rights reserved Prabaker et al. and/or ACM Press
Oblinger, Daniel, Castelli, Vittorio and Bergman, Lawrence (2006): Augmentation-based learning: combining observations and user edits for programming-by-demonstration. In: Proceedings of the 2006 International Conference on Intelligent User Interfaces 2006. pp. 202-209.
In this paper we introduce a new approach to Programming-by-Demonstration in which the user is allowed to explicitly edit the procedure model produced by the learning algorithm while demonstrating the task. We describe a new algorithm, Augmentation-Based Learning, that supports this approach by considering both demonstrations and edits as constraints on the hypothesis space, and resolving conflicts in favor of edits.
© All rights reserved Oblinger 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.
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
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.
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.
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.
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.
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