Graph Branch Algotithm : An Optimum Tree Search Method for Scored Dependency Graph with Arc Co-occurrence Constraints

概要

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Preference Dependency Grammar (PDG) is a framework for the morphological, syntactic and semantic analysis of natural language sentences. PDG gives packed shared data structures for encompassing the various ambiguities in each levels of sentence analysis with preference scores and a method for calculating the most plausible interpretation of a sentence. This paper proposes the Graph Branch Algorithm for computing the optimum dependency tree (the most plausible interpretation of a sentence) from a scored dependency forest which is a packed shared data structure encompassing all possible dependency trees (interpretations) of a sentence. The graph branch algorithm adopts the branch and bound principle for managing arbitral arc co-occurrence constraints including the single valence occupation constraint which is a basic semantic constraint in PDG.
一般社団法人情報処理学会の論文
2005-09-29