Ebook: New Developments in Parsing Technology
- Tags: Artificial Intelligence (incl. Robotics), Computational Linguistics, Algorithms
- Series: Text Speech and Language Technology 23
- Year: 2005
- Publisher: Springer Netherlands
- Edition: 1
- Language: English
- pdf
Parsing can be defined as the decomposition of complex structures into their constituent parts, and parsing technology as the methods, the tools, and the software to parse automatically. Parsing is a central area of research in the automatic processing of human language. Parsers are being used in many application areas, for example question answering, extraction of information from text, speech recognition and understanding, and machine translation. New developments in parsing technology are thus widely applicable.
This book contains contributions from many of today's leading researchers in the area of natural language parsing technology. The contributors describe their most recent work and a diverse range of techniques and results. This collection provides an excellent picture of the current state of affairs in this area. This volume is the third in a series of such collections, and its breadth of coverage should make it suitable both as an overview of the current state of the field for graduate students, and as a reference for established researchers.
Parsing can be defined as the decomposition of complex structures into their constituent parts, and parsing technology as the methods, the tools, and the software to parse automatically. Parsing is a central area of research in the automatic processing of human language. Parsers are being used in many application areas, for example question answering, extraction of information from text, speech recognition and understanding, and machine translation. New developments in parsing technology are thus widely applicable.
This book contains contributions from many of today's leading researchers in the area of natural language parsing technology. The contributors describe their most recent work and a diverse range of techniques and results. This collection provides an excellent picture of the current state of affairs in this area. This volume is the third in a series of such collections, and its breadth of coverage should make it suitable both as an overview of the current state of the field for graduate students, and as a reference for established researchers.
Parsing can be defined as the decomposition of complex structures into their constituent parts, and parsing technology as the methods, the tools, and the software to parse automatically. Parsing is a central area of research in the automatic processing of human language. Parsers are being used in many application areas, for example question answering, extraction of information from text, speech recognition and understanding, and machine translation. New developments in parsing technology are thus widely applicable.
This book contains contributions from many of today's leading researchers in the area of natural language parsing technology. The contributors describe their most recent work and a diverse range of techniques and results. This collection provides an excellent picture of the current state of affairs in this area. This volume is the third in a series of such collections, and its breadth of coverage should make it suitable both as an overview of the current state of the field for graduate students, and as a reference for established researchers.
Content:
Front Matter....Pages i-xi
Developments in Parsing Technology: From Theory to Application....Pages 1-18
Parameter Estimation for Statistical Parsing Models: Theory and Practice of Distribution-Free Methods....Pages 19-55
High Precision Extraction of Grammatical Relations....Pages 57-72
Automated Extraction of Tags from the Penn Treebank....Pages 73-89
Computing the Most Probable Parse for a Discontinuous Phrase Structure Grammar....Pages 91-106
A Neural Netword Parser that Handles Sparse Data....Pages 107-124
An Efficient LR Parser Generator for Tree-Adjoining Grammars....Pages 125-155
Relating Tabular Parsing Algorithms for LIG and TAG....Pages 157-184
Improved Left-Corner Chart Parsing for Large Context-Free Grammars....Pages 185-201
On Two Classes of Feature Paths in Large-Scale Unification Grammars....Pages 203-228
A Context-Free Superset Approximation of Unification-Based Grammars....Pages 229-250
A Recognizer for Minimalist Languages....Pages 251-268
Range Concatenation Grammars....Pages 269-289
Grammar Induction by MDL-Based Distributional Classification....Pages 291-306
Optimal Ambiguity Packing in Context-Free Parsers with Interleaved Unification....Pages 307-321
Robust Data Oriented Spoken Language Understanding....Pages 323-338
Soup: A Parser for Real-World Spontaneous Speech....Pages 339-350
Parsing and Hypergraphs....Pages 351-372
Measure for Measure: Towards Increased Component Comparability and Exchange....Pages 373-395
Back Matter....Pages 397-404
Parsing can be defined as the decomposition of complex structures into their constituent parts, and parsing technology as the methods, the tools, and the software to parse automatically. Parsing is a central area of research in the automatic processing of human language. Parsers are being used in many application areas, for example question answering, extraction of information from text, speech recognition and understanding, and machine translation. New developments in parsing technology are thus widely applicable.
This book contains contributions from many of today's leading researchers in the area of natural language parsing technology. The contributors describe their most recent work and a diverse range of techniques and results. This collection provides an excellent picture of the current state of affairs in this area. This volume is the third in a series of such collections, and its breadth of coverage should make it suitable both as an overview of the current state of the field for graduate students, and as a reference for established researchers.
Content:
Front Matter....Pages i-xi
Developments in Parsing Technology: From Theory to Application....Pages 1-18
Parameter Estimation for Statistical Parsing Models: Theory and Practice of Distribution-Free Methods....Pages 19-55
High Precision Extraction of Grammatical Relations....Pages 57-72
Automated Extraction of Tags from the Penn Treebank....Pages 73-89
Computing the Most Probable Parse for a Discontinuous Phrase Structure Grammar....Pages 91-106
A Neural Netword Parser that Handles Sparse Data....Pages 107-124
An Efficient LR Parser Generator for Tree-Adjoining Grammars....Pages 125-155
Relating Tabular Parsing Algorithms for LIG and TAG....Pages 157-184
Improved Left-Corner Chart Parsing for Large Context-Free Grammars....Pages 185-201
On Two Classes of Feature Paths in Large-Scale Unification Grammars....Pages 203-228
A Context-Free Superset Approximation of Unification-Based Grammars....Pages 229-250
A Recognizer for Minimalist Languages....Pages 251-268
Range Concatenation Grammars....Pages 269-289
Grammar Induction by MDL-Based Distributional Classification....Pages 291-306
Optimal Ambiguity Packing in Context-Free Parsers with Interleaved Unification....Pages 307-321
Robust Data Oriented Spoken Language Understanding....Pages 323-338
Soup: A Parser for Real-World Spontaneous Speech....Pages 339-350
Parsing and Hypergraphs....Pages 351-372
Measure for Measure: Towards Increased Component Comparability and Exchange....Pages 373-395
Back Matter....Pages 397-404
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