Robert Clawson

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David W. Embley†, Stephen W. Liddle‡, Deryle Lonsdale∗∗, George Nagy††, Yuri Tijerino‡‡, Robert Clawson†, Jordan Crabtree†, Yihong Ding†, Piyushee Jha††, Zonghui Lian†, Stephen Lynn†, Raghav K. Padmanabhan††, Jeff Peters†, Cui Tao†, Robby Watts†, Charla Woodbury†, and Andrew Zitzelberger† †Department of Computer Science ‡Department of Information Systems(More)
We present Intelligent Indexing: a general, scalable, collaborative approach to indexing and transcription of non-machinereadable documents that exploits visual consensus and group labeling while harnessing human recognition and domain expertise. In our system, indexers work directly on the page, and with minimal context switching can navigate the page,(More)
Human-based computation is an approach that utilizes the abilities and strengths of both humans and computers to achieve a symbiotic interaction that is stronger than either agent in isolation. We propose a system that amplifies the capacity of a human indexer by adding an intelligent handwriting recognition engine to the indexing process. This recognition(More)
In the absence of accurate handwriting recognition for historical documents, computer assisted transcription (CAT) methods move into the spotlight. We explore some of the weaknesses of current CAT systems and propose a CAT system which relies on subword spotting that overcomes most of these. The system is ideal crowdsourcing transcription to mobile users.
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