60,021 research outputs found
Decompositions of Grammar Constraints
A wide range of constraints can be compactly specified using automata or
formal languages. In a sequence of recent papers, we have shown that an
effective means to reason with such specifications is to decompose them into
primitive constraints. We can then, for instance, use state of the art SAT
solvers and profit from their advanced features like fast unit propagation,
clause learning, and conflict-based search heuristics. This approach holds
promise for solving combinatorial problems in scheduling, rostering, and
configuration, as well as problems in more diverse areas like bioinformatics,
software testing and natural language processing. In addition, decomposition
may be an effective method to propagate other global constraints.Comment: Proceedings of the Twenty-Third AAAI Conference on Artificial
Intelligenc
Flexible RNA design under structure and sequence constraints using formal languages
The problem of RNA secondary structure design (also called inverse folding)
is the following: given a target secondary structure, one aims to create a
sequence that folds into, or is compatible with, a given structure. In several
practical applications in biology, additional constraints must be taken into
account, such as the presence/absence of regulatory motifs, either at a
specific location or anywhere in the sequence. In this study, we investigate
the design of RNA sequences from their targeted secondary structure, given
these additional sequence constraints. To this purpose, we develop a general
framework based on concepts of language theory, namely context-free grammars
and finite automata. We efficiently combine a comprehensive set of constraints
into a unifying context-free grammar of moderate size. From there, we use
generic generic algorithms to perform a (weighted) random generation, or an
exhaustive enumeration, of candidate sequences. The resulting method, whose
complexity scales linearly with the length of the RNA, was implemented as a
standalone program. The resulting software was embedded into a publicly
available dedicated web server. The applicability demonstrated of the method on
a concrete case study dedicated to Exon Splicing Enhancers, in which our
approach was successfully used in the design of \emph{in vitro} experiments.Comment: ACM BCB 2013 - ACM Conference on Bioinformatics, Computational
Biology and Biomedical Informatics (2013
Introduction
This chapter will motivate why it is useful to consider the topic of derivations
and filtering in more detail. We will argue against the popular belief that
the minimalist program and optimality theory are incompatible theories in that the
former places the explanatory burden on the generative device (the computational
system) whereas the latter places it on the fi ltering device (the OT evaluator).
Although this belief may be correct in as far as it describes existing tendencies,
we will argue that minimalist and optimality theoretic approaches normally adopt
more or less the same global architecture of grammar: both assume that a generator
defines a set S of potentially well-formed expressions that can be generated on the
basis of a given input and that there is an evaluator that selects the expressions from
S that are actually grammatical in a given language L. For this reason, we believe
that it has a high priority to investigate the role of the two components in more detail
in the hope that this will provide a better understanding of the differences and similarities
between the two approaches. We will conclude this introduction with a brief
review of the studies collected in this book.
TDL--- A Type Description Language for Constraint-Based Grammars
This paper presents \tdl, a typed feature-based representation language and
inference system. Type definitions in \tdl\ consist of type and feature
constraints over the boolean connectives. \tdl\ supports open- and closed-world
reasoning over types and allows for partitions and incompatible types. Working
with partially as well as with fully expanded types is possible. Efficient
reasoning in \tdl\ is accomplished through specialized modules.Comment: Will Appear in Proc. COLING-9
Best-First Surface Realization
Current work in surface realization concentrates on the use of general,
abstract algorithms that interpret large, reversible grammars. Only little
attention has been paid so far to the many small and simple applications that
require coverage of a small sublanguage at different degrees of sophistication.
The system TG/2 described in this paper can be smoothly integrated with deep
generation processes, it integrates canned text, templates, and context-free
rules into a single formalism, it allows for both textual and tabular output,
and it can be parameterized according to linguistic preferences. These features
are based on suitably restricted production system techniques and on a generic
backtracking regime.Comment: 10 pages, LaTeX source, one EPS figur
Concurrent Lexicalized Dependency Parsing: The ParseTalk Model
A grammar model for concurrent, object-oriented natural language parsing is
introduced. Complete lexical distribution of grammatical knowledge is achieved
building upon the head-oriented notions of valency and dependency, while
inheritance mechanisms are used to capture lexical generalizations. The
underlying concurrent computation model relies upon the actor paradigm. We
consider message passing protocols for establishing dependency relations and
ambiguity handling.Comment: 90kB, 7pages Postscrip
A Graph Grammar for Modelling RNA Folding
We propose a new approach for modelling the process of RNA folding as a graph
transformation guided by the global value of free energy. Since the folding
process evolves towards a configuration in which the free energy is minimal,
the global behaviour resembles the one of a self-adaptive system. Each RNA
configuration is a graph and the evolution of configurations is constrained by
precise rules that can be described by a graph grammar.Comment: In Proceedings GaM 2016, arXiv:1612.0105
Robust Processing of Natural Language
Previous approaches to robustness in natural language processing usually
treat deviant input by relaxing grammatical constraints whenever a successful
analysis cannot be provided by ``normal'' means. This schema implies, that
error detection always comes prior to error handling, a behaviour which hardly
can compete with its human model, where many erroneous situations are treated
without even noticing them.
The paper analyses the necessary preconditions for achieving a higher degree
of robustness in natural language processing and suggests a quite different
approach based on a procedure for structural disambiguation. It not only offers
the possibility to cope with robustness issues in a more natural way but
eventually might be suited to accommodate quite different aspects of robust
behaviour within a single framework.Comment: 16 pages, LaTeX, uses pstricks.sty, pstricks.tex, pstricks.pro,
pst-node.sty, pst-node.tex, pst-node.pro. To appear in: Proc. KI-95, 19th
German Conference on Artificial Intelligence, Bielefeld (Germany), Lecture
Notes in Computer Science, Springer 199
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