Abstract not found

Abstract not found

This article reviews, and rethinks, a few leading themes of the biolinguistic program since its inception in the early 1950s, at each stage influenced by developments in the biological sciences. The following also discusses how the questions now entering the research agenda develop in a natural

describe a method for statistical modeling based on maximum entropy. We present a maximum-likelihood approach for automatically constructing maximum entropy models and describe how to implement this approach efficiently, using as examples several problems in natural language processing.

find that we are able to extract classes that have the flavor of either syntactically based groupings or semantically based groupings, depending on the nature of the underlying statistics.

Abstract not found

towards programming languages, but the same methods appear to be relevant also in the study of natural anguages. 1. Introduction. Let

formalism is very similar to temporal logics. This allows the language to be used for both writing programs and expressing program properties, which results in an original program verification methodology. 1 Introduction Reactive systems Reactive systems have been defined as computing systems which

This article presents a measure of semantic similarityinanis-a taxonomy based on the notion of shared information content. Experimental evaluation against a benchmark set of human similarity judgments demonstrates that the measure performs better than the traditional edge-counting approach. The article presents algorithms that take advantage of taxonomic similarity in resolving syntactic and semantic ambiguity, along with experimental results demonstrating their e#ectiveness. 1. Introduction Evaluating semantic relatedness using network representations is a problem with a long history in arti#cial intelligence and psychology, dating back to the spreading activation approach of Quillian #1968# and Collins and Loftus #1975#. Semantic similarity represents a special case of semantic relatedness: for example, cars and gasoline would seem to be more closely related than, say, cars and bicycles, but the latter pair are certainly more similar. Rada et al. #Rada, Mili, Bicknell, & Blett...

this paper, we will describe a simple rule-based approach to automated learning of linguistic knowledge. This approach has been shown for a number of tasks to capture information in a clearer and more direct fashion without a compromise in performance. We present a detailed case study of this learning method applied to part of speech tagging