Applications of WordNet (2)

Topic discussed on the 5th September 2008
Where wordnet is used, give some applications.
Give detail explanations of the applications.
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Detail Applications of WordNet (WN)
Information retrieval
It has been closely related to organisation and representation of knowledge on the internet. The application of Artificial Intelligence has helped for the retrieval of information, a method of incorporating logic and inference focus on WN.
Wordnet has been used as a semantic lexicon, in which queries have been expanded through keyword design, like in full text retrieval in a communication aid. It can be implemented as a linguistic knowledge tool to represent and interpret the meaning of. The user will be provided with efficient and integrated access to information. The development of a natural language interface can be done using wordnet, to optimise the precision of internet search engines by expanding queries.

Conceptual identification/disambiguation
Semantic disambiguation as follows:

i. All the noun-verb pairs in the sentence are selected.

ii. The most likely meaning of the term is chosen. Internet is used with this goal.

iii. Drawing from the most frequently appearing concepts (step ii), all the nouns are selected in the “glossaries” of each verb and its hierarchical subordinates.

iv. Drawing from the most frequently appearing concepts, all the nouns are selected in the “glossaries” of each noun and its hierarchical subordinates.

v. A formula is applied to calculate the concepts common to the nouns in point’s (iii) and (iv).

Disambiguation is very often and varies wordnet application. IWA/H, ARPA and KRSL have been created to avoid ambiguity, later AutoASC, proved very effective for disambiguation in information retrieval. The product has the latest wordnet gloss definition.

Query expansion
An expansion system was proposed in 1994, based on the calculation the tf-idf (term frequency–inverse document frequency) for the query terms and adding to it half the tf-idf for the WN synonyms for these terms. The benefits of applying wordnet to queries, using a Word Sense Disambiguator (WSD) enhance the search process.

Document classification
Semantic traits are extracted by grammatical categorisation of WN nouns, verbs, adjectives and categorisation of the relevance of data. An algorithm was designed by Judith Klavans for automatically determining the genre of a paper on the grounds of the WN verb categories used.