Scaling question answering to the Web
Proceedings of the 10th international conference on World Wide Web
Computer Models of Thought and Language
Computer Models of Thought and Language
The Black Swan: The Impact of the Highly Improbable
The Black Swan: The Impact of the Highly Improbable
ICCS '07 Proceedings of the 15th international conference on Conceptual Structures: Knowledge Architectures for Smart Applications
Revelator's Complex Adaptive Reasoning Methodology for Resource Infrastructure Evolution
ICCS '08 Proceedings of the 16th international conference on Conceptual Structures: Knowledge Visualization and Reasoning
Large-scale extraction and use of knowledge from text
Proceedings of the fifth international conference on Knowledge capture
Learning to map the virtual evolution of knowledge
ICCS'10 Proceedings of the 18th international conference on Conceptual structures: from information to intelligence
Reality Is Broken: Why Games Make Us Better and How They Can Change the World
Reality Is Broken: Why Games Make Us Better and How They Can Change the World
Building a pragmatic methodology for KR tool research and development
ICCS'06 Proceedings of the 14th international conference on Conceptual Structures: inspiration and Application
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Recent efforts to create natural-language, question-answering systems for the World Wide Web exploit the vast availability of information in Web resources as a knowledge base. Researchers who develop these systems explicitly assume that what is most often repeated in that knowledge base is the truth. Their assumption implicitly relies on a fallacy in classical logic: "proof by assertion" (or proof by repeated assertion). This paper considers the implications--both hazardous and hopeful--of the Most Often Repeated (MOR) assumption, and suggests Peirce's "economy of research" (EOR), in his evolutionary view of logic, as a promising alternative to MOR for truth-finding in the increasing complexity of crowdsourced knowledge.