Data-oriented parsing - Info and Reading Options

"Data-oriented parsing" Table Of Contents:

• 1- Part I: The basic data-oriented parsing model
• 2- A DOP model for phrase-structure trees / Rens Bod and Remko Scha
• 3- Reconsidering the probability model for DOP / Remko Bonnema and Remko Scha
• 4- Encoding frequency information / John Carroll and David Weir
• 5- Part II: Computational issues
• 6- Computational complexity of disambiguation under DOP1 / Khalil Simaản
• 7- Parsing DOP with Monte-Carlo techniques / Jean-Cedric Chappelier and Martin Rajman
• 8- An alternative approach to Monte Carlo parsing / Remko Bonnema
• 9- Efficient parsing of DOP with PCFG-reductions / Joshua Goodman
• 10- An approximation of DOP through memory-based learning / Guy De Pauw
• 11- Compositional partial parsing by memory-based sequence learning / Ido Dagan and Yuval Krymolowski
• 12- Part III: Richer models
• 13- Tree-gram parsing / Khalil Simaản
• 14- A DOP model for lexical-functional grammar / Rens Bod and Ronald Kaplan
• 15- A data-driven approach to head-driven phrase structure grammar / Günter Neumann
• 16- Tree adjoining grammars and their application to statistical parsing / Aravind Joshi and Anoop Sarkar
• 17- Localizing dependencies and supertagging / Srinivas Bangalore
• 18- Statistical parsing with a tag / David Chiang
• 19- Extending DOP with insertion / Lars Hoogweg
• 20- Part IV: Beyond parsing
• 21- Machine translation with tree-DOP / Arjen Poutsma
• 22- Machine translation using LFG-DOP / Andy Way
• 23- Alignment-based learning versus data-oriented parsing / Menno van Zaanen.

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