Processing natural language with schema constraint networks

Incremental Natural{language Processing with Schema{tree Adjoining Grammars

Constraint Logic Programming for Natural Language Processing

This paper proposes an evaluation of the adequacy of the constraint logic programming paradigm for natural language processing. Theoretical aspects of this question have been discussed in several works (see for example [Smolka89] or [Aı̈t-Kaci92]). We adopt here a pragmatic point of view and our argumentation relies on concrete solutions. Using actual contraints (in the CLP sense) is neither eas...

Natural Language Processing With Modular PDP Networks

An approach to connectionist natural language processing is proposed, which is based on hierarchically organized modular Parallel Distributed Processing (PDP) networks and a central lexicon of distributed input/output representations. The modules communicate using these representations, which are global and publicly available in the system. The representations are developed automatically by all...

Natural Language Processing with Subsymbolic Neural Networks

Natural language processing appears on the surface to be a strongly symbolic activity. Words are symbols that stand for objects and concepts in the real world, and they are put together into sentences that obey well-speci ed grammar rules. It is no surprise that for several decades natural language processing research has been dominated by the symbolic approach. Linguists have focused on descri...

Networks and Natural Language Processing

Over the last few years, a number of areas of natural language processing have begun applying graph-based techniques. These include, among others, text summarization, syntactic parsing, word sense disambiguation, ontology construction, sentiment and subjectivity analysis, text clustering. In this paper, we present some of the most successful graph-based representations and algorithms used in la...