Not Seeing the Parse Trees from the Parse Forest of a Context-Free Parallel Communicating Grammar System

2013 ◽  
Author(s):  
Stefan D. Bruda ◽  
Mary Sarah Ruth Wilkin
Keyword(s):  
Grammar System ◽  
Parse Trees ◽  
Context Free

scholarly journals Empirical Analysis of Context Free Grammars and Parse Trees

2014 ◽  
Vol 98 (6) ◽  
pp. 38-40
Author(s):  
J. Sreedhar ◽  
S. Viswanadha Raju ◽  
A. Vinaya Babu
Keyword(s):  
Empirical Analysis ◽  
Parse Trees ◽  
Context Free ◽  
Context Free Grammars

scholarly journals INCREMENTAL REFINEMENT OF FAÇADE MODELS WITH ATTRIBUTE GRAMMAR FROM 3D POINT CLOUDS

2016 ◽  
Vol III-3 ◽  
pp. 311-316 ◽  
Author(s):  
Y. Dehbi ◽  
C. Staat ◽  
L. Mandtler ◽  
L. Pl¨umer
Keyword(s):  
A Priori ◽  
Point Clouds ◽  
3D Point Clouds ◽  
Architectural Patterns ◽  
Grammar Rules ◽  
Probability Densities ◽  
Parse Trees ◽  
Incremental Interpretation ◽  
Context Free ◽  
Building Reconstruction

Data acquisition using unmanned aerial vehicles (UAVs) has gotten more and more attention over the last years. Especially in the field of building reconstruction the incremental interpretation of such data is a demanding task. In this context formal grammars play an important role for the top-down identification and reconstruction of building objects. Up to now, the available approaches expect offline data in order to parse an a-priori known grammar. For mapping on demand an on the fly reconstruction based on UAV data is required. An incremental interpretation of the data stream is inevitable. This paper presents an incremental parser of grammar rules for an automatic 3D building reconstruction. The parser enables a model refinement based on new observations with respect to a weighted attribute context-free grammar (WACFG). The falsification or rejection of hypotheses is supported as well. The parser can deal with and adapt available parse trees acquired from previous interpretations or predictions. Parse trees derived so far are updated in an iterative way using transformation rules. A diagnostic step searches for mismatches between current and new nodes. Prior knowledge on fac¸ades is incorporated. It is given by probability densities as well as architectural patterns. Since we cannot always assume normal distributions, the derivation of location and shape parameters of building objects is based on a kernel density estimation (KDE). While the level of detail is continuously improved, the geometrical, semantic and topological consistency is ensured.

scholarly journals A Statistical Parsing Framework for Sentiment Classification

2015 ◽  
Vol 41 (2) ◽  
pp. 293-336 ◽  
Author(s):  
Li Dong ◽  
Furu Wei ◽  
Shujie Liu ◽  
Ming Zhou ◽  
Ke Xu
Keyword(s):  
Sentiment Analysis ◽  
Sentiment Classification ◽  
Training Data ◽  
Data Sets ◽  
Syntactic Parsing ◽  
Benchmark Data ◽  
Sentence Level ◽  
Statistical Parsing ◽  
Parse Trees ◽  
Context Free

We present a statistical parsing framework for sentence-level sentiment classification in this article. Unlike previous works that use syntactic parsing results for sentiment analysis, we develop a statistical parser to directly analyze the sentiment structure of a sentence. We show that complicated phenomena in sentiment analysis (e.g., negation, intensification, and contrast) can be handled the same way as simple and straightforward sentiment expressions in a unified and probabilistic way. We formulate the sentiment grammar upon Context-Free Grammars (CFGs), and provide a formal description of the sentiment parsing framework. We develop the parsing model to obtain possible sentiment parse trees for a sentence, from which the polarity model is proposed to derive the sentiment strength and polarity, and the ranking model is dedicated to selecting the best sentiment tree. We train the parser directly from examples of sentences annotated only with sentiment polarity labels but without any syntactic annotations or polarity annotations of constituents within sentences. Therefore we can obtain training data easily. In particular, we train a sentiment parser, s.parser, from a large amount of review sentences with users' ratings as rough sentiment polarity labels. Extensive experiments on existing benchmark data sets show significant improvements over baseline sentiment classification approaches.

scholarly journals INCREMENTAL REFINEMENT OF FAÇADE MODELS WITH ATTRIBUTE GRAMMAR FROM 3D POINT CLOUDS

2016 ◽  
Vol III-3 ◽  
pp. 311-316
Author(s):  
Y. Dehbi ◽  
C. Staat ◽  
L. Mandtler ◽  
L. Pl¨umer
Keyword(s):  
A Priori ◽  
Point Clouds ◽  
3D Point Clouds ◽  
Architectural Patterns ◽  
Grammar Rules ◽  
Probability Densities ◽  
Parse Trees ◽  
Incremental Interpretation ◽  
Context Free ◽  
Building Reconstruction

Data acquisition using unmanned aerial vehicles (UAVs) has gotten more and more attention over the last years. Especially in the field of building reconstruction the incremental interpretation of such data is a demanding task. In this context formal grammars play an important role for the top-down identification and reconstruction of building objects. Up to now, the available approaches expect offline data in order to parse an a-priori known grammar. For mapping on demand an on the fly reconstruction based on UAV data is required. An incremental interpretation of the data stream is inevitable. This paper presents an incremental parser of grammar rules for an automatic 3D building reconstruction. The parser enables a model refinement based on new observations with respect to a weighted attribute context-free grammar (WACFG). The falsification or rejection of hypotheses is supported as well. The parser can deal with and adapt available parse trees acquired from previous interpretations or predictions. Parse trees derived so far are updated in an iterative way using transformation rules. A diagnostic step searches for mismatches between current and new nodes. Prior knowledge on fac¸ades is incorporated. It is given by probability densities as well as architectural patterns. Since we cannot always assume normal distributions, the derivation of location and shape parameters of building objects is based on a kernel density estimation (KDE). While the level of detail is continuously improved, the geometrical, semantic and topological consistency is ensured.

ON METALINEAR PARALLEL COMMUNICATING GRAMMAR SYSTEMS

2007 ◽  
Vol 18 (06) ◽  
pp. 1313-1322
Author(s):  
ANDREAS MALCHER ◽  
BETTINA SUNCKEL
Keyword(s):  
Intermediate Model ◽  
Grammar System ◽  
Grammar Systems ◽  
Context Free ◽  
Parallel Communicating Grammar Systems

A generalization of centralized and returning parallel communicating grammar systems with linear components (linear CPC grammar systems) is studied. It is known that linear CPC grammar systems are more powerful than regular CPC grammar systems and that CPC grammar systems with context-free components are more powerful than linear CPC grammar systems. Here, the intermediate model of metalinear CPC grammar systems is studied. This is a CPC grammar system where the master is allowed to use metalinear rules whereas the remaining components are restricted to use linear rules only. It turns out that metalinear CPC grammar systems are more powerful than linear CPC grammar systems and less powerful than CPC grammar systems with context-free components. Furthermore, it is shown that all languages generated by metalinear CPC grammar systems are semilinear.

ON THE DESCRIPTIONAL COMPLEXITY OF METALINEAR CD GRAMMAR SYSTEMS

2005 ◽  
Vol 16 (05) ◽  
pp. 1011-1025
Author(s):  
BETTINA SUNCKEL
Keyword(s):  
Recursive Function ◽  
Trade Off ◽  
Descriptional Complexity ◽  
Grammar System ◽  
Trade Offs ◽  
Grammar Systems ◽  
Context Free ◽  
Context Free Grammars

Metalinear CD grammar systems are context-free CD grammar systems where each component consists of metalinear productions. The maximal number of nonterminals in all starting productions is referred to as the width of a CD grammar system. It is shown that between the class of CD grammar systems of width m + 1 and of width m there are savings concerning the size of the grammar system not bounded by any recursive function. This is called a non-recursive trade-off. Furthermore, it is proven that there are non-recursive trade-offs between the class of metalinear CD grammar systems of width m and the class of (2m - 1)-linear context-free grammars. In addition, some decidability results are presented.

scholarly journals Vector Symbolic Architectures for Context-Free Grammars

2021 ◽  
Author(s):  
Peter beim Graben ◽  
Markus Huber ◽  
Werner Meyer ◽  
Ronald Römer ◽  
Matthias Wolff
Keyword(s):  
Fock Space ◽  
Principal Component ◽  
Mathematical Framework ◽  
Infinite Dimensional ◽  
Symbolic Data ◽  
Parse Trees ◽  
Viable Approach ◽  
Low Dimensional ◽  
Context Free ◽  
Context Free Grammars

AbstractVector symbolic architectures (VSA) are a viable approach for the hyperdimensional representation of symbolic data, such as documents, syntactic structures, or semantic frames. We present a rigorous mathematical framework for the representation of phrase structure trees and parse trees of context-free grammars (CFG) in Fock space, i.e. infinite-dimensional Hilbert space as being used in quantum field theory. We define a novel normal form for CFG by means of term algebras. Using a recently developed software toolbox, called FockBox, we construct Fock space representations for the trees built up by a CFG left-corner (LC) parser. We prove a universal representation theorem for CFG term algebras in Fock space and illustrate our findings through a low-dimensional principal component projection of the LC parser state. Our approach could leverage the development of VSA for explainable artificial intelligence (XAI) by means of hyperdimensional deep neural computation.

scholarly journals Partial parsing via finite-state cascades

1996 ◽  
Vol 2 (4) ◽  
pp. 337-344 ◽  
Author(s):  
STEVEN ABNEY
Keyword(s):  
Exhaustive Search ◽  
Partial Parsing ◽  
Feature Structures ◽  
Finite State ◽  
Parse Trees ◽  
Context Free

Finite state cascades represent an attractive architecture for parsing unrestricted text. Deterministic parsers specified by finite state cascades are fast and reliable. They can be extended at modest cost to construct parse trees with finite feature structures. Finally, such deterministic parsers do not necessarily involve trading off accuracy against speed — they may in fact be more accurate than exhaustive search stochastic context free parsers.

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