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» Word Importance Discrimination Using Context Information
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IWC
2007
100views more  IWC 2007»
14 years 9 months ago
Usefulness of VRML building models in a direction finding context
This paper describes an experiment which aims to examine the effectiveness and efficiency of a Virtual Reality Modelling Language (VRML) building model compared with equivalent ar...
Pietro Murano, Dino Mackey
ACL
2003
14 years 11 months ago
A Syllable Based Word Recognition Model for Korean Noun Extraction
Noun extraction is very important for many NLP applications such as information retrieval, automatic text classification, and information extraction. Most of the previous Korean ...
Do-Gil Lee, Hae-Chang Rim, Heui-Seok Lim
ACL
2011
14 years 1 months ago
Learning Word Vectors for Sentiment Analysis
Unsupervised vector-based approaches to semantics can model rich lexical meanings, but they largely fail to capture sentiment information that is central to many word meanings and...
Andrew L. Maas, Raymond E. Daly, Peter T. Pham, Da...
CHI
2006
ACM
15 years 10 months ago
A fisheye follow-up: further reflections on focus + context
Information worlds continue to grow, posing daunting challenges for interfaces. This paper tries to increase our understanding of approaches to the problem, building on the Genera...
George W. Furnas
FCCM
2008
IEEE
112views VLSI» more  FCCM 2008»
15 years 4 months ago
Power-Aware and Branch-Aware Word-Length Optimization
Power reduction is becoming more important as circuit size increases. This paper presents a tool called PowerCutter which employs accuracy-guaranteed word-length optimization to r...
William G. Osborne, José Gabriel F. Coutinh...