Electric Words : Dictionaries, Computers, and Meanings

Electric Words delves first into the philosophical background of the study of meaning, specifically word meaning, then into the early work on treating dictionaries as texts, the first serious efforts at extracting information from machine-readable dictionaries (MRDs), and the conversion of MRDs into usable lexical knowledge bases. The use of computers to understand words continues to be an area of burgeoning research.

Electric Words is the first general survey of and introduction to the entire range of work in lexical linguistics and corpora-the study of such on-line resources as dictionaries and other texts-in the broader fields of natural-language processing and artificial intelligence.

The authors integrate and synthesize the goals and methods of computational lexicons in relation to AI's sister disciplines of philosophy, linguistics, and psychology.

One of the underlying messages of the book is that current research should be guided by both computational and theoretical tools and not only by statistical techniques-that matters have gone far beyond counting to encompass the difficult province of meaning itself and how it can be formally expressed. Electric Words delves first into the philosophical background of the study of meaning, specifically word meaning, then into the early work on treating dictionaries as texts, the first serious efforts at extracting information from machine-readable dictionaries (MRDs), and the conversion of MRDs into usable lexical knowledge bases.

The authors provide a comparative survey of worldwide work on extracting usable structures from dictionaries for computational-linguistic purposes and a discussion of how those structures differ from or interact with structures derived from standard texts (or corpora).

Also covered are automatic techniques for analyzing MRDs, genus hierarchies and networks, numerical methods of language processing related to dictionaries, automatic processing of bilingual dictionaries, and consumer projects using MRDs.