Watson–Crick Context-Free Grammars: Grammar Simplifications and a Parsing Algorithm

2018 ◽  
Vol 61 (9) ◽  
pp. 1361-1373
Author(s):  
Nurul Liyana Mohamad Zulkufli ◽  
Sherzod Turaev ◽  
Mohd Izzuddin Mohd Tamrin ◽  
Azeddine Messikh
2001 ◽  
Vol 27 (2) ◽  
pp. 277-285
Author(s):  
Noriko Tomuro ◽  
Steven L. Lytinen

Shieber's abstract parsing algorithm (Shieber 1992) for unification grammars is an extension of Earley's algorithm (Earley 1970) for context-free grammars to feature structures. In this paper, we show that, under certain conditions, Shieber's algorithm produces what we call a nonminimal derivation: a parse tree which contains additional features that are not in the licensing productions. While Shieber's definition of parse tree allows for such nonminimal derivations, we claim that they should be viewed as invalid. We describe the sources of the nonminimal derivation problem, and propose a precise definition of minimal parse tree, as well as a modification to Shieber's algorithm which ensures minimality, although at some computational cost.


2006 ◽  
Vol 17 (03) ◽  
pp. 629-664 ◽  
Author(s):  
ALEXANDER OKHOTIN

The generalized LR parsing algorithm for context-free grammars is extended for the case of Boolean grammars, which are a generalization of the context-free grammars with logical connectives added to the formalism of rules. In addition to the standard LR operations, Shift and Reduce, the new algorithm uses a third operation called Invalidate, which reverses a previously made reduction. This operation makes the mathematical justification of the algorithm significantly different from its prototype. On the other hand, the changes in the implementation are not very substantial, and the algorithm still works in time O(n4).


2008 ◽  
Vol 5 (2) ◽  
Author(s):  
Petteri Sevon ◽  
Lauri Eronen

SummaryWe describe a method for querying vertex- and edge-labeled graphs using context-free grammars to specify the class of interesting paths. We introduce a novel problem, finding the connection subgraph induced by the set of matching paths between given two vertices or two sets of vertices. Such a subgraph provides a concise summary of the relationship between the vertices. We also present novel algorithms for parsing subgraphs directly without enumerating all the individual paths. We evaluate experimentally the presented parsing algorithms on a set of real graphs derived from publicly available biomedical databases and on randomly generated graphs. The results indicate that parsing the connection subgraph directly is much more effective than parsing individual paths separately. Furthermore, we show that using a bidirectional parsing algorithm, in most cases, allows for searching twice as long paths as using a unidirectional search strategy.


Sign in / Sign up

Export Citation Format

Share Document