Friday, May 6, 2011

Paper Reading #25 - Using language complexity to measure cognitive load for adaptive interaction design

Comment:

Reference Info:
M. Asif Khawaja, Fang Chen, and Nadine Marcus.
IUI '10 Proceedings of the 15th international conference on Intelligent user interfaces


Summary:
This paper discusses an adaptive interaction system to keep track of the users' cognition load and will change responses and interactive flow to improve the user's experience. A speech content analysis will measure the cognitive load.

Discussion:
The idea seems like it would be great but I feel the paper fails to describe in detail how this would be done. It focuses more on the requirements than the implementation and what it will do to reach these goals.

Paper Reading #24 - Mobia Modeler: easing the creation process of mobile applications for non-technical users

Comments:

Reference Info:
Florence  Balagtas-Fernandez, Max Tafelmayer, and Heinrich Hussman 
IUI '10 Proceedings of the 15th international conference on Intelligent user interfaces

Summary:
This tools makes it easy for people with no programming skills to build mobile applications. It has configurable parts for the users that are seen in common applications.
Discussion:
 My first reaction was unease at the thought of non programmers programming. Upon further reading and thinking, i was eased with the thought that their programs would not be as complex as ones made by programmers.

Paper Reading #23: Evaluating the design of inclusive interfaces by simulation

Comments:
 
Reference info:
Evaluating the design of inclusive interfaces by simulation
Pradipta Biswas, and Peter Robinson.
IUI '10 Proceedings of the 15th international conference on Intelligent user interfaces
 
Summary:
The paper discusses a simulator for assistive interfacing. It is capable of predicting interaction patterns when a user used an input device. The experiment was conducted with 7 users. It shows how users can click on wrong icons and give errors.
 
 
 
Discussion:
I didn't feel like this paper gave to much information about their overall goal and what they want to do. It seemed like a good idea but needs further development.

Paper Reading #22 - From Documents to Tasks: Deriving User Tasks from Document Usage Patterns

Comments:
Jaideep Balekar

Cindy Skach



Reference Info:
From Documents to Tasks: Deriving User Tasks from Document Usage Patterns
Oliver Brdiczka
IUI '10 Proceedings of the 15th international conference on Intelligent 
  
Summary:
A knowledge worker is typically involved with multiple tasks and must switch often between them on a daily basis. The frequency of the switches between tasks become time expensive because of the recovery between tasks. Systems to aid users in switching exist but require too much from the user for their proper use. The paper proposes a system in which i automatically estimates a user's tasks from interactions with documents. The system focuses more on the document indentifiers rather than information contained within the document. The system monitors desktop activity and logs documents with focus on the desktop. Depending on their dwell time and similarity with other documents, frequencies and switches are estimated. The documents are then clustered according to the tasks.



Discussion:
I think it would be interesting to use such a system. I would like to have my tasks automated and switched for me to make it easier on me and more productive. I wonder if it would also group together unproductive things, or documents that may not be related to the work.

Paper Reading #21: Raconteur: from intent to stories

Comments:
Jaideep Balekar
Joe Cabrera

Reference Info:
Raconteur: from intent to stories
Pei-Yu Chi, Henry Lieberman
IUI '10 Proceedings of the 15th international conference on Intelligent user interfaces


Summary:
When creating a story out of media such as pictures or video, it is often diffucult to fit in some of the media. Some may seem like it does not fit and the user does not know where to place it to keep the flow of the story. Raconteur allows users to put this media together and assemble it coherently. It annotates each media with a small sentence

Discussion:
I feel like I would not use this because I feel it is the same as going thru someones facebook album with their comments. I make videos with images and videos and I like the challenge of seeing how I can incorporate images into the video.

Paper Reading #20: iSlideShow: a content-aware slideshow system

Comments:
Michael Atkinson
Jaideep Balekar

Reference Info:

iSlideshow: a Content-Aware Slideshow System
Jiajian Chen, Jun Xiao, Yuli Gao
IUI '10 Proceedings of the 15th international conference on Intelligent user interfaces


Summary:
The paper discusses an intelligent slide show presentation system that analyzes information about the photo and uses it to generate transitions between them. The algorithm clusters pictures according to the content analyzed. It can tile them together to make a larger picture. The algorithms analyzes the flow of color from one edge to another to tie them in together.

Discussion:
I feel like this is a novelty program that is fun to play with but will not be used for any real purpose other than entertainment. It seems like one of those features that will be pushed aside after a while and its there but no one really uses it.

Paper Reading #19: From documents to tasks: deriving user tasks from document usage patterns

Comments:
Jaideep Balekar

Cindy Skach



Reference Info:
Title: From Documents to Tasks: Deriving User Tasks from Document Usage Patterns
Authors: Oliver Brdiczka
Conference: IUI '10 Proceedings of the 15th international conference on Intelligent 
  
Summary:
A knowledge worker is typically involved with multiple tasks and must switch often between them on a daily basis. The frequency of the switches between tasks become time expensive because of the recovery between tasks. Systems to aid users in switching exist but require too much from the user for their proper use. The paper proposes a system in which i automatically estimates a user's tasks from interactions with documents. The system focuses more on the document indentifiers rather than information contained within the document. The system monitors desktop activity and logs documents with focus on the desktop. Depending on their dwell time and similarity with other documents, frequencies and switches are estimated. The documents are then clustered according to the tasks.
 

Discussion:
I think it would be interesting to use such a system. I would like to have my tasks automated and switched for me to make it easier on me and more productive. I wonder if it would also group together unproductive things, or documents that may not be related to the work.