Word-based context models for text compression have the capacity to outperform more simple character-based models, but are generally unattractive because of inherent problems with exponential model growth and corresponding data sparseness. These ill-effects can be mitigated in an adaptive lossless compression scheme by modelling syntactic and semantic lexical dependencies independently
In this thesis we develop models for sentence compression. This text rewriting task has recently att...
Institute for Communicating and Collaborative SystemsIn this thesis we develop models for sentence c...
Semistatic word-based byte-oriented compression codes are known to be attractive alternatives to com...
Word-based context models for text compression have the capacity to outperform more simple character...
The best general-purpose compression schemes make their gains by estimating a probability distributi...
196 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2000.We then turn to construction ...
New methods of acquiring structural information in text documents may support better compression by ...
Context modeling has emerged as the most promising new approach to compressing text. While context-m...
We describe two systems for text simplification using typed dependency structures, one that performs...
In this thesis we develop models for sentence compression. This text rewriting task has recently att...
Semistatic byte-oriented word-based compression codes have been shown to be an attractive alternativ...
the importance of lexicalized models of syntax. By contrast, these models do not appear to have had ...
Semistatic word-based byte-oriented compressors are known to be attractive alternatives to compress ...
Dictionary-based compression algorithms include a parsing strategy to transform the input text into ...
Real-world business applications require a trade-off between language model performance and size. We...
In this thesis we develop models for sentence compression. This text rewriting task has recently att...
Institute for Communicating and Collaborative SystemsIn this thesis we develop models for sentence c...
Semistatic word-based byte-oriented compression codes are known to be attractive alternatives to com...
Word-based context models for text compression have the capacity to outperform more simple character...
The best general-purpose compression schemes make their gains by estimating a probability distributi...
196 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2000.We then turn to construction ...
New methods of acquiring structural information in text documents may support better compression by ...
Context modeling has emerged as the most promising new approach to compressing text. While context-m...
We describe two systems for text simplification using typed dependency structures, one that performs...
In this thesis we develop models for sentence compression. This text rewriting task has recently att...
Semistatic byte-oriented word-based compression codes have been shown to be an attractive alternativ...
the importance of lexicalized models of syntax. By contrast, these models do not appear to have had ...
Semistatic word-based byte-oriented compressors are known to be attractive alternatives to compress ...
Dictionary-based compression algorithms include a parsing strategy to transform the input text into ...
Real-world business applications require a trade-off between language model performance and size. We...
In this thesis we develop models for sentence compression. This text rewriting task has recently att...
Institute for Communicating and Collaborative SystemsIn this thesis we develop models for sentence c...
Semistatic word-based byte-oriented compression codes are known to be attractive alternatives to com...
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