Publication statistics

Pub. period:2005-2012
Pub. count:15
Number of co-authors:23



Co-authors

Number of publications with 3 favourite co-authors:

Ryen W. White:4
Gifford Cheung:2
Efthimis N. Efthimiadis:2

 

 

Productive colleagues

Jeff Huang's 3 most productive colleagues in number of publications:

Susan Dumais:74
Ryen W. White:59
Michael Twidale:23
 
 
 
Jul 10

Visual appearance is one of the most effective variables for quickly differentiating one application from another

-- Bob Baxley, 2003

 
 

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by Mads Soegaard and Rikke Friis Dam

 
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Jeff Huang

Personal Homepage:
http://jeffhuang.com

Current place of employment:
University of Washington

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Publications by Jeff Huang (bibliography)

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2012
 
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Cheung, Gifford and Huang, Jeff (2012): Remix and play: lessons from rule variants in Texas Hold'em and Halo 2. In: Proceedings of ACM CSCW12 Conference on Computer-Supported Cooperative Work 2012. pp. 559-568.

Players can change the rules of a multi-person game to experience a different gameplay mechanic, add thematic color, or fine-tune its balance. To better understand game variants, we use a grounded approach to analyze 62 variants for Texas Hold'em, a popular card game, and a follow-up case-study of 91 variants of Halo 2, a popular video game. We study their development and examine whether lessons from Texas Hold'em apply to a constrained system such as Halo 2. We discover video gamers' reliance on 'honor rules', rules dependent on the cooperative spirit of its players. We develop a theory of 'necessity' in rule adoption, showing players' sensitivity to the impact of one change on the whole game. In solving game-design problems, adjustments drawn from a set of 'canned' rule changes address common problems with familiar solutions. We find a complex interplay between who can play and what rules are chosen. Our findings have implications for game designers and for variants in non-game contexts.

© All rights reserved Cheung and Huang and/or ACM Press

 
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Diriye, Abdigani, Kumaran, Giridhar and Huang, Jeff (2012): Interactive search support for difficult web queries. In: Proceedings of the 2012 BCS-IRSG European Conference on Information Retrieval 2012. pp. 37-49.

Short and common web queries are aptly supported by state-of-the-art search engines but performance and user experience are degraded when web queries are longer and less common. Extending previous solutions that automatically shorten queries, we introduce searchAssist: a novel search interface that provides interactive support for difficult web queries. The query logs and questionnaires from a naturalistic study of 90 web users' search behaviors show

© All rights reserved Diriye et al. and/or Springer

 
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Huang, Jeff, White, Ryen W., Buscher, Georg and Wang, Kuansan (2012): Improving searcher models using mouse cursor activity. In: Proceedings of the 35th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2012. pp. 195-204.

Web search components such as ranking and query suggestions analyze the user data provided in query and click logs. While this data is easy to collect and provides information about user behavior, it omits user interactions with the search engine that do not hit the server; these logs omit search data such as users' cursor movements. Just as clicks provide signals for relevance in search results, cursor hovering and scrolling can be additional implicit signals. In this work, we demonstrate a technique to extend models of the user's search result examination state to infer document relevance. We start by exploring recorded user interactions with the search results, both qualitatively and quantitatively. We find that cursor hovering and scrolling are signals telling us which search results were examined, and we use these interactions to reveal latent variables in searcher models to more accurately compute document attractiveness and satisfaction. Accuracy is evaluated by computing how well our model using these parameters can predict future clicks for a particular query. We are able to improve the click predictions compared to a basic searcher model for higher ranked search results using the additional log data.

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

 
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Huang, Jeff, Etzioni, Oren, Zettlemoyer, Luke, Clark, Kevin and Lee, Christian (2012): RevMiner: an extractive interface for navigating reviews on a smartphone. In: Proceedings of the 2012 ACM Symposium on User Interface Software and Technology 2012. pp. 3-12.

Smartphones are convenient, but their small screens make searching, clicking, and reading awkward. Thus, perusing product reviews on a smartphone is difficult. In response, we introduce RevMiner -- a novel smartphone interface that utilizes Natural Language Processing techniques to analyze and navigate reviews. RevMiner was run over 300K Yelp restaurant reviews extracting attribute-value pairs, where attributes represent restaurant attributes such as sushi and service, and values represent opinions about the attributes such as fresh or fast. These pairs were aggregated and used to: 1) answer queries such as "cheap Indian food", 2) concisely present information about each restaurant, and 3) identify similar restaurants. Our user studies demonstrate that on a smartphone, participants preferred RevMiner's interface to tag clouds and color bars, and that they preferred RevMiner's results to Yelp's, particularly for conjunctive queries (e.g., "great food and huge portions"). Demonstrations of RevMiner are available at revminer.com.

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

2011
 
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Cheung, Gifford and Huang, Jeff (2011): Starcraft from the stands: understanding the game spectator. In: Proceedings of ACM CHI 2011 Conference on Human Factors in Computing Systems 2011. pp. 763-772.

Video games are primarily designed for the players. However, video game spectating is also a popular activity, boosted by the rise of online video sites and major gaming tournaments. In this paper, we focus on the spectator, who is emerging as an important stakeholder in video games. Our study focuses on Starcraft, a popular real-time strategy game with millions of spectators and high level tournament play. We have collected over a hundred stories of the Starcraft spectator from online sources, aiming for as diverse a group as possible. We make three contributions using this data: i) we find nine personas in the data that tell us who the spectators are and why they spectate; ii) we strive to understand how different stakeholders, like commentators, players, crowds, and game designers, affect the spectator experience; and iii) we infer from the spectators' expressions what makes the game entertaining to watch, forming a theory of distinct types of information asymmetry that create suspense for the spectator. One design implication derived from these findings is that, rather than presenting as much information to the spectator as possible, it is more important for the stakeholders to be able to decide how and when they uncover that information.

© All rights reserved Cheung and Huang and/or their publisher

 
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Huang, Jeff, White, Ryen W. and Dumais, Susan (2011): No clicks, no problem: using cursor movements to understand and improve search. In: Proceedings of ACM CHI 2011 Conference on Human Factors in Computing Systems 2011. pp. 1225-1234.

Understanding how people interact with search engines is important in improving search quality. Web search engines typically analyze queries and clicked results, but these actions provide limited signals regarding search interaction. Laboratory studies often use richer methods such as gaze tracking, but this is impractical at Web scale. In this paper, we examine mouse cursor behavior on search engine results pages (SERPs), including not only clicks but also cursor movements and hovers over different page regions. We: (i) report an eye-tracking study showing that cursor position is closely related to eye gaze, especially on SERPs; (ii) present a scalable approach to capture cursor movements, and an analysis of search result examination behavior evident in these large-scale cursor data; and (iii) describe two applications (estimating search result relevance and distinguishing good from bad abandonment) that demonstrate the value of capturing cursor data. Our findings help us better understand how searchers use cursors on SERPs and can help design more effective search systems. Our scalable cursor tracking method may also be useful in non-search settings.

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

2010
 
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Huang, Jeff and White, Ryen W. (2010): Parallel browsing behavior on the web. In: Proceedings of the 21st ACM Conference on Hypertext and Hypermedia 2010. pp. 13-18.

Parallel browsing describes a behavior where users visit Web pages in multiple concurrent threads. Web browsers explicitly support this by providing tabs. Although parallel browsing is more prevalent than linear browsing online, little is known about how users perform this activity. We study the use of parallel browsing through a log-based study of millions of Web users and present findings on their behavior. We identify a power law distribution in browser metrics comprising "outclicks" and tab switches, which signify the degree of parallel browsing. We find that users switch tabs at least 57.4% of the time, but user activity, measured in pageviews, is split among tabs rather than increasing overall activity. Finally, analysis of a subset of the logs focused on Web search shows that while the majority of users do not branch from search engine result pages, the degree of branching is higher for non-navigational queries. Our findings have design implications for Web sites and browsers, search interfaces, and log analysis.

© All rights reserved Huang and White and/or their publisher

 
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Huang, Jeff, Thornton, Katherine M. and Efthimiadis, Efthimis N. (2010): Conversational tagging in twitter. In: Proceedings of the 21st ACM Conference on Hypertext and Hypermedia 2010. pp. 173-178.

Users on Twitter, a microblogging service, started the phenomenon of adding tags to their messages sometime around February 2008. These tags are distinct from those in other Web 2.0 systems because users are less likely to index messages for later retrieval. We compare tagging patterns in Twitter with those in Delicious to show that tagging behavior in Twitter is different because of its conversational, rather than organizational nature. We use a mixed method of statistical analysis and an interpretive approach to study the phenomenon. We find that tagging in Twitter is more about filtering and directing content so that it appears in certain streams. The most illustrative example of how tagging in Twitter differs is the phenomenon of the Twitter micro-meme: emergent topics for which a tag is created, used widely for a few days, then disappears. We describe the micro-meme phenomenon and discuss the importance of this new tagging practice for the larger real-time search context.

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

 
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Singla, Adish, White, Ryen and Huang, Jeff (2010): Studying trailfinding algorithms for enhanced web search. In: Proceedings of the 33rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2010. pp. 443-450.

Search engines return ranked lists of Web pages in response to queries. These pages are starting points for post-query navigation, but may be insufficient for search tasks involving multiple steps. Search trails mined from toolbar logs start with a query and contain pages visited by one user during post-query navigation. Implicit endorsements from many trails can enhance result ranking. Rather than using trails solely to improve ranking, it may also be worth providing trail information directly to users. In this paper, we quantify the benefit that users currently obtain from trail-following and compare different methods for finding the best trail for a given query and each top-ranked result. We compare the relevance, topic coverage, topic diversity, and utility of trails selected using different methods, and break out findings by factors such as query type and origin relevance. Our findings demonstrate value in trails, highlight interesting differences in the performance of trailfinding algorithms, and show we can find best-trails for a query that outperform the trails most users follow. Findings have implications for enhancing Web information seeking using trails.

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

 
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White, Ryen W. and Huang, Jeff (2010): Assessing the scenic route: measuring the value of search trails in web logs. In: Proceedings of the 33rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2010. pp. 587-594.

Search trails mined from browser or toolbar logs comprise queries and the post-query pages that users visit. Implicit endorsements from many trails can be useful for search result ranking, where the presence of a page on a trail increases its query relevance. Following a search trail requires user effort, yet little is known about the benefit that users obtain from this activity versus, say, sticking with the clicked search result or jumping directly to the destination page at the end of the trail. In this paper, we present a log-based study estimating the user value of trail following. We compare the relevance, topic coverage, topic diversity, novelty, and utility of full trails over that provided by sub-trails, trail origins (landing pages), and trail destinations (pages where trails end). Our findings demonstrate significant value to users in following trails, especially for certain query types. The findings have implications for the design of search systems, including trail recommendation systems that display trails on search result pages.

© All rights reserved White and Huang and/or their publisher

 
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Huang, Jeff and Kazeykina, Anna (2010): Optimal Strategies for Reviewing Search Results. In: Proceedings of AAAI 2010. .

2009
 
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Huang, Jeff and Efthimiadis, Efthimis N. (2009): Analyzing and Evaluating Query Reformulation Strategies in Web Search Logs. In: Proceedings of CIKM 2009. p. 10.

2007
 
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Huang, Jeff and Twidale, Michael (2007): Graphstract: minimal graphical help for computers. In: Proceedings of the ACM Symposium on User Interface Software and Technology October 7-10, 2007, Newport, Rhode Island, USA. pp. 203-212.

We explore the use of abstracted screenshots as part of a new help interface. Graphstract, an implementation of a graphical help system, extends the ideas of textually oriented Minimal Manuals to the use of screenshots, allowing multiple small graphical elements to be shown in a limited space. This allows a user to get an overview of a complex sequential task as a whole. The ideas have been developed by three iterations of prototyping and evaluation. A user study shows that Graphstract helps users perform tasks faster on some but not all tasks. Due to their graphical nature, it is possible to construct Graphstracts automatically from pre-recorded interactions. A second study shows that automated capture and replay is a low-cost method for authoring Graphstracts, and the resultant help is as understandable as manually constructed help.

© All rights reserved Huang and Twidale and/or ACM Press

2006
 
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Chen, Irene Y. L., Su, Addison, Huang, Jeff, Lan, Blue and Shen, Yen-Shih (2006): Ubiquitous Collaborative Learning in Knowledge-Aware Virtual Communities. In: SUTC 2006 - IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing 5-7 June, 2006, Taichung, Taiwan. pp. 84-89.

2005
 
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Huang, Jeff, Lu, Bo and Twidale, Michael B. (2005): Graphical abstract help. In: Proceedings of CHINZ05, the ACM SIGCHI New Zealand Chapters International Conference on Computer-Human Interaction 2005. pp. 83-89.

We explore the use of abstracted versions of screenshots as part of an interface to support giving help to the user. Graphstract, the software implementation of this graphical help system, extends the ideas of textually oriented Minimal Manuals to the use of screenshots, enabling multiple small graphical elements to be shown in a small space. This enables the user to get an overview of a complex sequential task as a whole. Graphical hints, such as jagged edges, red dots, and icons are also explored. The idea has been developed by iterative prototyping. In cases where the minimalist help is insufficient, ways of providing more detailed information on demand are investigated.

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

 
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Changes to this page (author)

23 Nov 2012: Modified
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Page maintainer: The Editorial Team
URL: http://www.interaction-design.org/references/authors/jeff_huang.html

Publication statistics

Pub. period:2005-2012
Pub. count:15
Number of co-authors:23



Co-authors

Number of publications with 3 favourite co-authors:

Ryen W. White:4
Gifford Cheung:2
Efthimis N. Efthimiadis:2

 

 

Productive colleagues

Jeff Huang's 3 most productive colleagues in number of publications:

Susan Dumais:74
Ryen W. White:59
Michael Twidale:23
 
 
 
Jul 10

Visual appearance is one of the most effective variables for quickly differentiating one application from another

-- Bob Baxley, 2003

 
 

Featured chapter

Marc Hassenzahl explains the fascinating concept of User Experience and Experience Design. Commentaries by Don Norman, Eric Reiss, Mark Blythe, and Whitney Hess

User Experience and Experience Design !

 
 

Our Latest Books

Kumar and Herger 2013: Gamification at Work: Designing Engaging Business Software...
by Janaki Mythily Kumar and Mario Herger

 
Start reading

Whitworth and Ahmad 2013: The Social Design of Technical Systems: Building technologies for communities...
by Brian Whitworth and Adnan Ahmad

 
Start reading

Soegaard and Dam 2013: The Encyclopedia of Human-Computer Interaction, 2nd Ed....
by Mads Soegaard and Rikke Friis Dam

 
Start reading
 
 

Help us help you!