Word Sense Disambiguation
Words have different meanings based on the
context of the word usage in a sentence. Word sense is one of the meanings of a
word. Human language is ambiguous, so that many words can be interpreted in
multiple ways depending on the context in which they occur. Word sense
disambiguation (WSD) is the ability to identify the meaning of words in context
in a computational manner. WSD is considered an AIcomplete problem, that is, a
task whose solution is at least as hard as the most difficult problems in
artificial intelligence.
WSD can be viewed as a classification task: word
senses are the classes, and an automatic classification method is used to
assign each occurrence of a word to one or more classes based on the evidence
from the context and from external knowledge sources. WSD heavily relies on
knowledge. Knowledge sources provide data which are essential to associate
senses with words. The assessment of WSD systems is discussed in the context of
the Senseval/Semeval campaigns, aiming at the objective evaluation of systems
participating in several different disambiguation tasks. Here, some of the
knowledge sources used in WSD, different approaches for WSD (supervised,
unsupervised and Knowledge-based ) and evaluation of WSD systems are discussed.
The applications of WSD are also seen.
You can download Word Sense Disambiguation seminar abstract from here.
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