2,102 research outputs found
A grammatical specification of human-computer dialogue
The Seeheim Model of human-computer interaction partitions an interactive application into a user-interface, a dialogue controller and the application itself. One of the formal techniques of implementing the dialogue controller is based on context-free grammars and automata. In this work, we modify an off-the-shelf compiler generator (YACC) to generate the dialogue controller. The dialogue controller is then integrated into the popular X-window system, to create an interactive-application generator. The actions of the user drive the automaton, which in turn controls the application
BSML: A Binding Schema Markup Language for Data Interchange in Problem Solving Environments (PSEs)
We describe a binding schema markup language (BSML) for describing data
interchange between scientific codes. Such a facility is an important
constituent of scientific problem solving environments (PSEs). BSML is designed
to integrate with a PSE or application composition system that views model
specification and execution as a problem of managing semistructured data. The
data interchange problem is addressed by three techniques for processing
semistructured data: validation, binding, and conversion. We present BSML and
describe its application to a PSE for wireless communications system design
SLR inference: An inference system for fixed-mode logic programs, based on SLR parsing
AbstractDefinite-clause grammars (DCGs) generalize context-free grammars in such a way that Prolog can be used as a parser in the presence of context-sensitive information. Prolog's proof procedure, however, is based on backtracking, which may be a source of inefficiency. Parsers for context-free grammars that use backtracking, for instance, were soon replaced by more efficient methods, such as LR parsers. This suggests incorporating the principles underlying LR parsing into a parser for grammars with context-sensitive information. We present a technique that applies a transformation to the program/grammar by adding leaves to the proof/parse trees and placing the contextual information in such leaves. An inference system is then easily obtained from an LR parser, since only the parts dealing with terminals (which appear at the leaves) must be modified. Although our method is restricted to programs with fixed modes, it may be preferable to DCGs under Prolog for some programs
Data-Oriented Language Processing. An Overview
During the last few years, a new approach to language processing has started
to emerge, which has become known under various labels such as "data-oriented
parsing", "corpus-based interpretation", and "tree-bank grammar" (cf. van den
Berg et al. 1994; Bod 1992-96; Bod et al. 1996a/b; Bonnema 1996; Charniak
1996a/b; Goodman 1996; Kaplan 1996; Rajman 1995a/b; Scha 1990-92; Sekine &
Grishman 1995; Sima'an et al. 1994; Sima'an 1995-96; Tugwell 1995). This
approach, which we will call "data-oriented processing" or "DOP", embodies the
assumption that human language perception and production works with
representations of concrete past language experiences, rather than with
abstract linguistic rules. The models that instantiate this approach therefore
maintain large corpora of linguistic representations of previously occurring
utterances. When processing a new input utterance, analyses of this utterance
are constructed by combining fragments from the corpus; the
occurrence-frequencies of the fragments are used to estimate which analysis is
the most probable one.
In this paper we give an in-depth discussion of a data-oriented processing
model which employs a corpus of labelled phrase-structure trees. Then we review
some other models that instantiate the DOP approach. Many of these models also
employ labelled phrase-structure trees, but use different criteria for
extracting fragments from the corpus or employ different disambiguation
strategies (Bod 1996b; Charniak 1996a/b; Goodman 1996; Rajman 1995a/b; Sekine &
Grishman 1995; Sima'an 1995-96); other models use richer formalisms for their
corpus annotations (van den Berg et al. 1994; Bod et al., 1996a/b; Bonnema
1996; Kaplan 1996; Tugwell 1995).Comment: 34 pages, Postscrip
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