@inproceedings{amershi2009designing,
author = {Amershi, Saleema and Fogarty, James and Kapoor, Ashish and Tan, Desney},
title = {Designing for End-User Interactive Concept Learning in CueFlik},
booktitle = {(2009) Neural Information Processing Systems (NIPS) Workshop on Analysis and Design of Algorithms for Interactive Machine Learning},
year = {2009},
month = {August},
abstract = {The current information explosion fundamentally changes how people live and work with computing: vast numbers of documents and images are available on the Web; ubiquitous sensing enables near-continuous tracking and monitoring of people and objects; and inexpensive storage allows people to keep near-unlimited personal data and sensing archives. One strategy to enable effective access to and interaction with such large unstructured datasets is to support example-based iterative end-user training of machine learning systems to identify relevant concepts. These concepts can then be used specify desired manipulations. In the context of the CueFlik system for re-ranking Web image search results according to their visual characteristics, we have been examining general questions surrounding the design of end-user interactive machine learning.},
url = {http://approjects.co.za/?big=en-us/research/publication/designing-end-user-interactive-concept-learning-cueflik/},
edition = {(2009) Neural Information Processing Systems (NIPS) Workshop on Analysis and Design of Algorithms for Interactive Machine Learning},
}