Applied Text Analysis with Python: Enabling Language-Aware Data Products with Machine Learning
WordNet is an on-line lexical reference system whose design isinspired by current psycholinguistic theories of human lexical memory;version 1.6 is the most up-to-date version of the system.
WordNet, an electronic lexical database, is considered to be the most important resource available to researchers in computational linguistics, text analysis, and many related areas. Its design is inspired by current psycholinguistic and computational theories of human lexical memory. English nouns, verbs, adjectives, and adverbs are organized into synonym sets, each representing one underlying lexicalized concept. Different relations link the synonym sets.The purpose of this volume is twofold. First, it discusses the design of WordNet and the theoretical motivations behind it. Second, it provides a survey of representative applications, including word sense identification, information retrieval, selectional preferences of verbs, and lexical chains.
Reem Al-Halimi, Robert C. Berwick, J. F. M. Burg, Martin Chodorow, Christiane Fellbaum, Joachim Grabowski, Sanda Harabagiu, Marti A. Hearst, Graeme Hirst, Douglas A. Jones, Rick Kazman, Karen T. Kohl, Shari Landes, Claudia Leacock, George A. Miller, Katherine J. Miller, Dan Moldovan, Naoyuki Nomura, Uta Priss, Philip Resnik, David St-Onge, Randee Tengi, Reind P. van de Riet, Ellen Voorhees
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