1. A method for WSD on Unrestricted Text
Authors: Rada Mihalcea and Dan Moldovan
Presenter: Marian Olteanu

2. Introduction WSD methods: Hybrid methods
Information in MRD (machine readable dictionaries)
Supervised training (info from a disambiguated corpus)
Unsupervised training (info from a raw corpus)
Hybrid methods

3. Approach Unsupervised learning
Tag all content words (nouns, verbs, adjectives, adverbs)
Use Web as a corpus (Altavista search engine)
Use semantic density (using WordNet)

4. Algorithm Use word pairs (one word in the context of the other)
Verb-noun pairs (syntactically linked)
I.e.: investigate report
{report#1, study}, {report#2, news report, story, account, write up}

5. Algorithm (cont.)
Search for “investigate report” and “investigate study” – first sense
Search for “investigate report”, “investigate news report”, …, “investigate write up” – second sense
Order sense # by counts

6. Algorithm (cont.) Repeat for verbs
Use both phrases and NEAR operator – similar results
Select first 4 senses for N and V, first 2 for J and R

7. Algorithm – step 2 Compute conceptual density
Apply only for N-V pair (because WN doesn’t have adequate hierarchies for J and R)
Between senses found at step 1
Count match between nouns in the sub-glosses of the verb and all the hyponyms (+noun) for the noun

8. Algorithm – step 2 (cont.)
Formula:
I find it flawed (log part)
revise law:

9. Evaluation
SemCor
Step 1:
Step 2:

10. Comparison