Researchers have sought to enhance its accuracy by incorporating additional resources like thesauruses and syntactic models.
The Lesk algorithm is based on the assumption that words in a given "neighborhood" (section of text) will tend to share a common topic.
A simplified version of the Lesk algorithm is to compare the dictionary definition of an ambiguous word with the terms contained in its neighborhood.
Note: Vasilescu et al. implementation considers a back-off strategy for words not covered by the algorithm, consisting of the most frequent sense defined in WordNet.
This is a significant limitation in that dictionary glosses tend to be fairly short and do not provide sufficient vocabulary to relate fine-grained sense distinctions.