Thus instead of terms the specic meanings could be

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Unformatted text preview: , etc. for each term. Text chunking aims at grouping adjacent words in a sentence. An example of a chunk is the noun phrase “the current account deficit”. Word Sense Disambiguation (WSD) tries to resolve the ambiguity in the meaning of single words or phrases. An example is ‘bank’ which may have – among others – the senses ‘financial institution’ or the ‘border of a river or lake’. Thus, instead of terms the specific meanings could be stored in the vector space representation. This leads to a bigger dictionary but considers the semantic of a term in the representation. Parsing produces a full parse tree of a sentence. From the parse, we can find the relation of each word in the sentence to all the others, and typically also its function in the sentence (e.g. subject, object, etc.). Linguistic processing either uses lexica and other resources as well as handcrafted rules. If a set of examples is available machine learning methods as described in section 3, especially in section 3.3, may be employed to learn the desired tags. It turned out, however, that for many text mining tasks li...
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This note was uploaded on 06/19/2011 for the course IT 2258 taught by Professor Aymenali during the Summer '11 term at Abu Dhabi University.

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