Paper Reading #24 - The Why UI: Using Goal Networks to Improve User Interfaces

Comments:


Reference:
The Why UI: Using Goal Networks to Improve User Interfaces
Dustin A. Smith, Henry Lieberman
IUI '10

Summary:
This paper examines a new method of modeling user goals through voice commands.  The method the authors describe processes a natural language plan corpus, constructed by many people.  Goals can be inferred by a system or explicitly stated by a user.  However, each goal can have a multitude of sub-goals, and it is useful to predict specifically what the user is interested in.  As it is, people usually fall short in stating explicit goals. 

The authors downloaded a corpus from 43things.com which contains a multitude of goal statements ("buy a house," "travel to New York," etc.)  These goal statements did not have explicit relations, so the authors attempted to infer relations by matching the context of plan statements with goal statements.  After correcting spelling mistakes and in general tidying up the text, they built a directed weighted goal graph.  They found that while most of the goals in the corpus were unique, there were a few that were far more prevelant than others.  They then transfer the results to a mobile app which can help the user achieve those goals.  For example, a user wanting to buy a house would have a map come up suggesting subgoals, such as locations and details for realtors in the area.

Discussion:
This is another interesting example of how technology may be used to assist us in everyday life.  This application doesn't do anything that people with the time and motivation couldn't figure out by themselves, but it certainly makes the potentially desired information easier to access.  I can especially see it being useful for someone trying something for the first time.  It will be interesting to see where this technology will go from here.

Book Reading #51 - Living With Complexity

Reference:
Living With Complexity
Donald A. Norman
2011 The MIT Press

Summary:
Ch. 1 - Complexity is all around us, though much of it is of our own design.  Many of us have our own organized chaos, where something incomprehensible to another person makes perfect sense to us.  However, sometimes in products unnecessary complexity is used that makes a device or feature difficult to use.  At other times, complexity is used for aesthetic reasons.  Intreestingly, we are much more at home with complex things that we grow up with (swimming, reading, learning an instrument) than we are with taking an hour or two to learn a new technology.

Ch. 2 - Conceptual models are one method to hide the underlying complexity of a system.  In a computer file system, for example, what we thing of as files and folders are simply blocks of data scattered across the storage space.  Sometimes, we use conceptual models that simplify a complex system while still getting the main interactions across.  There are some tools that are simple in design, but incredibly complex in their application and usage.  While the design of things can be simple or complex, sometimes the simple thing is confusing (an array of unlabeled light switches) while a complex thing is easilly unserstood (a crowded marketplace).

Discussion:
Ch. 1 - It is interesting how we will defend complexity that we know for all of our lives.  While I know that the digital clock face is more efficient overall, I still prefer the analog method and always wear a watch.  I am often shocked when I run into peers that don't know how to read the analog face, but from a usability standpoint it makes sense.

Ch. 2 - The computer file system is a good analogy to use here.  We have a fairly simple conceptual model that it works like a physical file cabinet, yet the underlying system is so complex and confusing that it makes your head spin.  Still, everyone is able to use it because it is presented in a way we can understand.

Why We Make Mistakes - Full Blog

Book Reading #50 - Why We Make Mistakes

Paper Reading #23 - Automatic Generation of Research Trails in Web History

Comments:

Reference:

Automatic Generation of Research Trails in Web History

Elin Pedersen, Karl Gyllstrom, Shengyin Gu, Peter Jin Hong

IUI '10

Summary:

After conducting an ethnographic study, the authors of this paper determined that while people are using the internet to conduct extensive research, they are not following traditional scolarly and investigative methods.  The research conducted usually falls into one of the following categories: personal consumption, fragmented process, topic sliding, or premature structure.  The authors believe that tools designed to track research sessions and provide context to the researcher upon subsequent research would be beneficial.  Research trails may be used to do just that by grouping events that the user perceives belong in the same category and listing them as temporally ordered lists of segments.

Research trails helps the researcher by showing them where they are in the current activity.  This will help answer possible questions like "what did I leave unfinished?" and "where did I leave of last time I worked on this?"  It also extracts activity-based and semantic information from user activity.  Enough ambiguity is allowed to allow users to switch between topics based on timely affinity.  Events are temporally grouped into specific periods of activity called segments.  A segment is bounded when more than five minutes pass between two consecutive events.  Each event is provided with a topic vector, a list of its coverage of automatically determined set of topics.  These vectors allow for semantic analysis of the events.  In their preliminary assessment, the authors found that their segment definition naturally captured the concept of a work session.  They also found that segments typically were related and coherent locally, though there were occasionally both unrelated segments in trails and related segments excluded from trails.  In the future, they plan to capture a richer set of activity data, such as user activity on a visited page.

Discussion: This concept certainly seems like it would be a boon to researchers.  Aside from tracking the sites visited while doing research, it provides context and relations between the visited resources.  The automated aspect is somewhat of a double-edged sword, for while it makes things easier for the researcher overall, in doing so it removes the responsibilities of the researcher to keep track of their work and increases their overall expectations that everything should be done for them by default.  Still, this seems like a valuable tool that I wouldn't mind using myself.

Book Reading #49 - Why We Make Mistakes

Reference:
Why We Make Mistakes
Joeseph T. Hallinan
Broadway Books 2009

Summary:
Ch. 10 - People have a tendency to think that they are above average.  We overestimate our skills and how much we would use a product.  Busnisses understand this, and use it to prey on unwitting people.  An exception to this rule is present in the least confident, who seem to have a nearly perfect grasp on their abilities.  It is possible, however, to become more realistic in our assessments when we have strong, instant feedback.

Ch. 11 - We often tend to make a snap decision when faced with a challenge instead of reflecting on it. 

Discussion:
Ch. 10 -

Ch. 11 -

Book Reading #48 - Media Equation

References:
Machines and Mindlessness: Social Response to Computers
Clifford Nass, Youngme Moon
Journal of Social Issues, Vol. 56, No. 1, 2000, pp. 81-103

Computers are Social Actors
Clifford Nass, Jonathan Steuer, Ellen R. Tauber
CHI '94

Can Computer Personalities be Human Personalities?
Clifford Nass, Youngme Moon, BJ Fogg, Byron Reeves, Chris Dryer
CHI '95

Summary:
Machines and Mindlessness:

Computers are Social Actors:

Can Computer Personalities be Human Personalities:

Discussion:
Machines and Mindlessness:

Computers are Social Actors:

Can Computer Personalities be Human Personalities: