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Efficient Enumeration Algorithms for Annotated Grammars [article]

Antoine Amarilli, Louis Jachiet, Martín Muñoz, Cristian Riveros
2022 arXiv   pre-print
Our first result is an algorithm for unambiguous annotated grammars, which preprocesses the input string in cubic time and enumerates all annotations with output-linear delay.  ...  We study the enumeration problem for annotated grammars: fixing a grammar, and given a string as input, enumerate all annotations of the string that form a word derivable from the grammar.  ...  We then introduce the arity-two normal form for annotated grammars, designed to ensure efficient enumeration, and which can be enforced in linear time.  ... 
arXiv:2201.00549v2 fatcat:hbchqvyjkrfuvhoozd4ktnia5y

On Repair with Probabilistic Attribute Grammars [article]

Manos Koukoutos, Mukund Raghothaman, Etienne Kneuss, Viktor Kuncak
2017 arXiv   pre-print
We implement our algorithm in a framework for verification, synthesis and repair of functional programs, demonstrating that our approach can repair programs that are beyond the reach of previous tools.  ...  Our approach combines semantic specifications, in the form of pre- and post-conditions and input-output examples with syntactic specifications in the form of term grammars and AST-level statistics extracted  ...  To make search driven by probabilistic grammars efficient, we adopt a top-down approach for search.  ... 
arXiv:1707.04148v1 fatcat:goxtgzjq4raolhrcwzkpxchvgm

Algebraic Dynamic Programming [chapter]

Robert Giegerich, Carsten Meyer
2002 Lecture Notes in Computer Science  
Yet, no methodology is available for designing such algorithms.  ...  We define the formal framework including a formalization of Bellman's principle, specify an executable specification language, and show how algorithm design decisions and tuning for efficiency can be described  ...  For the sake of efficiency, we shall annotate the tree grammar to indicate the cases where h is to be applied.  ... 
doi:10.1007/3-540-45719-4_24 fatcat:4mqvukect5amhmj2jyvf5uum7q

Scope Underspecification with Tree Descriptions: Theory and Practice [chapter]

Alexander Koller, Stefan Thater, Manfred Pinkal
2010 Resource-Adaptive Cognitive Processes  
In this paper, we outline the results of the CHORUS project on the topic of semantic underspecification, along two major lines of research: We review a series of solvers for dominance constraints and dominance  ...  But how can we retrieve the set of solved forms of an underspecified description efficiently? This is the enumeration problem; algorithms for the enumeration problem are called solvers.  ...  Current algorithms (see Sect. 3) support the efficient enumeration of readings from underspecified descriptions.  ... 
doi:10.1007/978-3-540-89408-7_15 dblp:series/cogtech/KollerTP11 fatcat:bg5gl3ehbjedjh7r3jmlmvynve

Replaceable Substructures for Efficient Part-Based Modeling

Han Liu, Ulysse Vimont, Michael Wand, Marie-Paule Cani, Stefanie Hahmann, Damien Rohmer, Niloy J. Mitra
2015 Computer graphics forum (Print)  
The key challenge is to efficiently synthesize shape variations that are plausible, both locally and globally.  ...  We demonstrate the algorithm on a range of test examples producing plausible shape variations, both from a geometric and from a topological viewpoint.  ...  Acknowledgements We are grateful to the anonymous reviewers for their comments, suggestions, and additional references.  ... 
doi:10.1111/cgf.12579 fatcat:bl3jjj3ksjf25pouyyzou3slvq

Automatic wrappers for large scale web extraction

Nilesh Dalvi, Ravi Kumar, Mohamed Soliman
2011 Proceedings of the VLDB Endowment  
We present a generic framework to make wrapper induction algorithms tolerant to noise in the training data.  ...  En route, we obtain provably efficient algorithms for the enumeration problem that may be of independent interest.  ...  In the next section, we give an efficient algorithm that takes a well-behaved φ as a blackbox, a set of labels L, and efficiently enumerates the wrapper space of L.  ... 
doi:10.14778/1938545.1938547 fatcat:i7f4ecwnx5gqzntssqw2vapsc4

Correcting Syntactic Annotation Errors Based on Tree Mining

Kanta SUZUKI, Yoshihide KATO, Shigeki MATSUBARA
2017 IEICE transactions on information and systems  
This paper provides a new method to correct annotation errors in a treebank.  ...  In our method, we consider that if an infrequent pattern can be transformed to a frequent one, then it is an annotation error pattern.  ...  Acknowledgments This research was partially supported by the Grand-in-Aid for Scientific Research (B) (No. 26280082) of JSPS.  ... 
doi:10.1587/transinf.2016edp7357 fatcat:hk7tb7uhfvajvll5rx2eej63ty

Spoken language understanding from unaligned data using discriminative classification models

F. Mairesse, M. Gasic, F. Jurcicek, S. Keizer, B. Thomson, K. Yu, S. Young
2009 2009 IEEE International Conference on Acoustics, Speech and Signal Processing  
While data-driven methods for spoken language understanding reduce maintenance and portability costs compared with handcrafted parsers, the collection of word-level semantic annotations for training remains  ...  Results show that it outperforms existing generative models, while performance is close to more complex grammar induction techniques.  ...  While keeping the same constraints on the level of semantic annotation, this paper presents an efficient yet simple technique that learns discriminative semantic concept classifiers whose output is used  ... 
doi:10.1109/icassp.2009.4960692 dblp:conf/icassp/MairesseGJKTYY09 fatcat:klmusbleybffxoo3nxyxuh34zu

Bottom-up tree acceptors

C. Hemerik, J.P. Katoen
1989 Science of Computer Programming  
This paper deals with the formal derivation of an efficient tabulation algorithm for table-driven bottom-up tree acceptors.  ...  Use Definitions 3.3, 2.4 and 4.7. 0 The following algorithm A2 is a more efficient version of algorithm A, in which the match sets are enumerated and Nclosure is used.  ...  Concluding remarks We have derived a rather efficient tabulation algorithm for table-driven bottom-up tree acceptors.  ... 
doi:10.1016/0167-6423(89)90015-4 fatcat:7ey55zselne6bolj5zigte2yza

Probabilistic Models for Learning a Semantic Parser Lexicon

Jayant Krishnamurthy
2016 Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies  
Lexicon learning is the first step of training a semantic parser for a new application domain and the quality of the learned lexicon significantly affects both the accuracy and efficiency of the final  ...  We introduce several probabilistic models for learning the lexicon of a semantic parser.  ...  Acknowledgments We gratefully acknowledge Oyvind Tafjord, Matt Gardner, Peter Turney, Oren Etzioni and the anonymous reviewers for their helpful comments.  ... 
doi:10.18653/v1/n16-1074 dblp:conf/naacl/Krishnamurthy16 fatcat:kllq5qvz7bccbehnjt2zrcz3wy

Robust Processing of Situated Spoken Dialogue [chapter]

Pierre Lison, Geert-Jan M. Kruijff
2009 Lecture Notes in Computer Science  
The approach is fully implemented in a dialogue system for autonomous robots.  ...  Second, speech recognition remains a highly errorprone task, especially for complex, open-ended domains.  ...  In order to handle disfluent, partial, ill-formed or misrecognized utterances, the grammar used by the parser is "relaxed" via the introduction of a set of non-standard rules which allow for the combination  ... 
doi:10.1007/978-3-642-04617-9_31 fatcat:x7hdjodgbnfefb3r2xvijwewqy

A discipline of dynamic programming over sequence data

R GIEGERICH
2004 Science of Computer Programming  
We suggest a language used for algorithm design on a convenient level of abstraction. We outline three ways of implementing this language, including an embedding in a lazy functional language.  ...  We define its formal framework, based on a combination of grammars and algebras, and including a formalization of Bellman's Principle.  ...  is in the grammar, and efficiency concerns are treated by the grammar annotation.  ... 
doi:10.1016/s0167-6423(04)00017-6 fatcat:szewhvvkjncanc6vuswnlyfj5m

A discipline of dynamic programming over sequence data

Robert Giegerich, Carsten Meyer, Peter Steffen
2004 Science of Computer Programming  
We suggest a language used for algorithm design on a convenient level of abstraction. We outline three ways of implementing this language, including an embedding in a lazy functional language.  ...  We define its formal framework, based on a combination of grammars and algebras, and including a formalization of Bellman's Principle.  ...  is in the grammar, and efficiency concerns are treated by the grammar annotation.  ... 
doi:10.1016/j.scico.2003.12.005 fatcat:gvscd5y2zveopi73ckl5mtgsia

Matching and Significance Evaluation of Combined Sequence-Structure Motifs in RNA

Carsten Meyer, Robert Giegerich
2002 Zeitschrift fur physikalische Chemie (Munchen. 1991)  
The discipline of Algebraic Dynamic Programming is a powerful method to design and implement versatile pattern matching algorithms on sequences; here we consider mixed sequence and secondary structure  ...  Acknowledgement We thank Thomas Töller for providing informations about the IRE and the SECIS patterns as well as the sequences for testing our programms.  ...  Making explicit the grammar behind the algorithm helps to clarify properties relating to ambiguity as well as efficiency.  ... 
doi:10.1524/zpch.2002.216.2.193 fatcat:2iue37au4jfglmbz7gk67oekva

EMBEDDING DSLS INTO GPLS: A GRAMMATICAL INFERENCE APPROACH *

Dejan Hrnčič, Marjan Mernik, Barrett R. Bryant
2011 Information Technology and Control  
Grammatical inference can be used for grammar extraction from input examples. A memetic algorithm for grammatical inference, named MAGIc, was implemented to extract grammar from DSL examples.  ...  From the results it can be concluded that MAGIc is successful for DSL embedding and that the inference process is improved with use of negative examples.  ...  The results of grammatical inference in programming languages are still premature and a need for a robust and efficient algorithm exists.  ... 
doi:10.5755/j01.itc.40.4.980 fatcat:76kbzuev5nbwtps54z4mkdqdsq
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