Deriving Meaning of Trending Words for Expanding Thesaurus

Automatically Expanding the Lexicon of Roget's Thesaurus

In recent years much research has been conducted on building Thesauri and enhancing them with new terms and relationships. I propose to build and evaluate a system for automatically updating the lexicon of Roget’s Thesaurus. Roget’s has been shown to lend itself well to many Natural Language Processing tasks. One of the factors limiting Roget’s use is that the only publicly available version of...

Deriving Meaning From the Data

Entangling words and meaning

Human memory experiments appear to be generating “nonlocal” effects (Nelson & McEvoy 2007b). In this paper the possibility that words might be entangled in human semantic space is seriously entertained. This approach leads to a very natural picture of the way in which context might affect word association via the standard interpretation of quantum measurement. Two possible scenarios for testing...

Extending A Thesaurus By Classifying Words

This paper proposes a method for extending an existing thesaurus through classification of new words in terms of that thesaurus. New words are classified on the basis of relative probabilities of.a word belonging to a given word class, with the probabilities calculated using nounverb co-occurrence pairs. Experiments using the Japanese Bunruigoihy5 thesaurus on about 420,000 co-occurrences showe...

Deriving Meaning Vectors from Large Corpora

A neural network model for deriving meaning vectors for words from information retrieval based document vectors is described. A small scale experiment is performed using the model and results compared with an actual thesaurus. Although the results are not good, they show that a full scale experiment may be worth investigating to determine if the poor results are due to the model itself or the v...