(Data|Text) Mining - Word-sense disambiguation (WSD)

About

Word-sense disambiguation (WSD) is an open problem of natural language processing, which governs the process of identifying which sense of a word (i.e. meaning) is used in a sentence, when the word has multiple meanings.

Articles Related

Techniques

A rich variety of techniques have been researched:

• dictionary-based methods that use the knowledge encoded in lexical resources,
• supervised machine learning methods in which a classifier is trained for each distinct word on a corpus of manually sense-annotated examples,
• completely unsupervised methods that cluster occurrences of words, thereby inducing word senses.

Supervised learning approaches have been the most successful algorithms to date.

Documentation / Reference

• wiki/Word-sense disambiguation
• Free Corpus