{"id":343511,"date":"2016-12-29T18:00:52","date_gmt":"2016-12-30T02:00:52","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&p=343511"},"modified":"2018-10-16T21:32:47","modified_gmt":"2018-10-17T04:32:47","slug":"designing-end-user-interactive-concept-learning-cueflik","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/designing-end-user-interactive-concept-learning-cueflik\/","title":{"rendered":"Designing for End-User Interactive Concept Learning in CueFlik"},"content":{"rendered":"

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.<\/p>\n","protected":false},"excerpt":{"rendered":"

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 […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13554],"msr-publication-type":[193716],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-343511","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-human-computer-interaction","msr-locale-en_us"],"msr_publishername":"","msr_edition":"(2009) Neural Information Processing Systems (NIPS) Workshop on Analysis and Design of Algorithms for Interactive Machine 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