A small matter of programming: perspectives on end user computing
A small matter of programming: perspectives on end user computing
Watch what I do: programming by demonstration
Watch what I do: programming by demonstration
Tourmaline: text formatting by demonstration
Watch what I do
Communications of the ACM
The selection recognition agent: instant access to relevant information and operations
Proceedings of the 2nd international conference on Intelligent user interfaces
Instructible agents
Integrating user interface agents with conventional applications
IUI '98 Proceedings of the 3rd international conference on Intelligent user interfaces
Collaborative, programmable intelligent agents
Communications of the ACM
From documents to objects: an overview of LiveDoc
ACM SIGCHI Bulletin
Drop zones: an extension to LiveDoc
ACM SIGCHI Bulletin
Machine Learning and Grammar Induction
Machine Learning
Toped: enabling end-user programmers to validate data
CHI '08 Extended Abstracts on Human Factors in Computing Systems
Intelligently creating and recommending reusable reformatting rules
Proceedings of the 14th international conference on Intelligent user interfaces
Fast, Accurate Creation of Data Validation Formats by End-User Developers
IS-EUD '09 Proceedings of the 2nd International Symposium on End-User Development
Collaborative browsing system based on semantic mashup with open APIs
Expert Systems with Applications: An International Journal
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An important function of an agent is to be “on the lookout” for bits of information that are interesting to its user, even if these items appear in the midst of a larger body of unstructured information. But how to tell these agents which patterns are meaningful and what to do with the result? Especially when agents are used to recognize text, they are usually driven by parsers which require input in the form of textual grammar rules. Editing grammars is difficult and error-prone for end users. Grammex [“Grammars by Example”] is the first direct manipulation interface designed to allow non-expert users to define grammars interactively. The user presents concrete examples of text that he or she would like the agent to recognize. Rules are constructed by an iterative process, where Grammex heuristically parses the example, displays a set of hypotheses, and the user critiques the system's suggestions. Actions to take upon recognition are also demonstrated by example.