Lesk algorithm: Difference between revisions

Revision as of 10:53, 2 June 2010

Revision as of 23:05, 3 June 2010

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3. fruit of certain evergreen trees

As you can see the best intersection is Pine#1 ⋂ Cone#3 = 2.

==Criticisms and other Lesk-based methods==

Unfortunately, Lesk’s approach is very sensitive to the exact wording of definitions, so the absence of a certain word can radically change the results. Further, the algorithm determines overlaps only among the glosses of the senses being considered. 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.

Recently, a lot of works appeared which offer different modifications of this algorithm. These works uses other resources for analysis (thesauruses, synonyms dictionaries or morphological and syntaxical models): for instance, it may use such information as synonyms, different derivatives, or words from definitions of words from definitions<ref>Alexander Gelbukh, Grigori Sidorov. Automatic resolution of ambiguity of word senses in dictionary definitions (in Russian). J. Nauchno-Tehnicheskaya Informaciya (NTI), ISSN 0548-0027, ser. 2, N 3, 2004, pp. 10–15.</ref>.

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* Kilgarriff & Rosensweig, 2000,

* Alexander Gelbukh, Grigori Sidorov, 2004.

==Accuracy==

AccuracyThe original method achieved 50–70% accuracy (depending on the word) on ''[[Pride and Prejudice]]'' and selected papers of the [[Associated Press]] was found to be in the 50% to 70% range.

Senseval results.

== References ==