Improving word-recognizers using an interactive lexicon with active and passive words

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Improving word-recognizers using an interactive lexicon with active and passive words

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International Conference on Intelligent User Interfaces archive
Proceedings of the 13th international conference on Intelligent user interfaces table of contents

Gran Canaria, Spain

SESSION: Short papers table of contents

Pages 353-356

Year of Publication: 2008

ISBN:978-1-59593-987-6

Authors

Per Ola Kristensson	University of Cambridge, Cambridge, UK
Shumin Zhai	IBM Almaden Research Center, San Jose, CA

Sponsors

SIGART: ACM Special Interest Group on Artificial Intelligence
AAAI : Association for the Advancement of Artifical Intelligence
SIGCHI: ACM Special Interest Group on Computer-Human Interaction
ACM: Association for Computing Machinery

Publisher

ACM New York, NY, USA

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Downloads (6 Weeks): 7, Downloads (12 Months): 60, Citation Count: 1

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ABSTRACT

The words a user is likely to write comprise the user's active vocabulary. This vocabulary is considerably smaller than the passive vocabulary of words a user reads. We explore an interactive adaptive lexicon method that separates a large lexicon into active and passive sets, and gradually expands and adapts the active set to reflect the user's active vocabulary. The adaptation is achieved through lightweight interaction as a by product of actual use. The effectiveness of the technique is demonstrated through a computational experiment and a user study.

REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

	1	Scott D. Connell , Anil K. Jain, Writer Adaptation for Online Handwriting Recognition, IEEE Transactions on Pattern Analysis and Machine Intelligence, v.24 n.3, p.329-346, March 2002 [doi>10.1109/34.990135]
	2	G. W. Furnas , T. K. Landauer , L. M. Gomez , S. T. Dumais, The vocabulary problem in human-system communication, Communications of the ACM, v.30 n.11, p.964-971, Nov. 1987 [doi>10.1145/32206.32212]
	3	Klimt, B. and Yang, Y. Introducing the Enron Corpus. Proc. CEAS 2004.
	4	Per-Ola Kristensson , Shumin Zhai, SHARK²: a large vocabulary shorthand writing system for pen-based computers, Proceedings of the 17th annual ACM symposium on User interface software and technology, October 24-27, 2004, Santa Fe, NM, USA [doi>10.1145/1029632.1029640]
	5	Simpson, J. and Weiner, E. C. Oxford English Dictionary. Clarendon Press, 1989.
	6	Hanhong Xue , Venu Govindaraju, On the Dependence of Handwritten Word Recognizers on Lexicons, IEEE Transactions on Pattern Analysis and Machine Intelligence, v.24 n.12, p.1553-1564, December 2002 [doi>10.1109/TPAMI.2002.1114848]