Knowledge Mining
DOI: 10.1007/3-540-32394-5_9
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Text Mining Applied to Multilingual Corpora

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Cited by 14 publications
(9 citation statements)
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“…The Word Sense Disambiguation algorithm considers also possible super-subordinate related concepts in order to find common senses in lemmas being analysed. The detected terms are then extracted, reduced to their Part Of Speech (Noun, Verb, Adjective, Adverb, etc) and Functional (Agent, Object, Where, Cause, etc) tagged base form [10] [11]. The 96% of the words in a sentence is normally classified without any ambiguity, while the complete syntactic tree for the sentence is extracted in the 77% of the cases.…”
Section: B the Lexical Systemmentioning
confidence: 99%
“…The Word Sense Disambiguation algorithm considers also possible super-subordinate related concepts in order to find common senses in lemmas being analysed. The detected terms are then extracted, reduced to their Part Of Speech (Noun, Verb, Adjective, Adverb, etc) and Functional (Agent, Object, Where, Cause, etc) tagged base form [10] [11]. The 96% of the words in a sentence is normally classified without any ambiguity, while the complete syntactic tree for the sentence is extracted in the 77% of the cases.…”
Section: B the Lexical Systemmentioning
confidence: 99%
“…Beside Named Entities, locations, time-points, etc, it detects relevant information like noun phrases which comply with a set of pre-defined morphological patterns and whose information exceeds a threshold of significance [8]. The detected terms are then extracted, reduced to their Part Of Speech (Noun, Verb, Adjective, Adverb, etc) and Functional (Agent, Object, Where, Cause, etc) tagged base form [9][10] (see Fig.…”
Section: The Lexical Systemmentioning
confidence: 99%
“…By including semantic information directly in the dependency grammar structures, the system relies on the lexical semantic information combined with functional relations. Beside Named Entities, locations, time-points, etc, it detects relevant information like noun phrases which comply with a set of pre-defined morphological patterns and whose information exceeds a threshold of significance [13]. The detected terms are then extracted, reduced to their Part Of Speech(NOUN, VERB, ADJECTIVE, ADVERB, etc.)…”
Section: The Lexical Systemmentioning
confidence: 99%
“…tagged base form [12]. Once referred to their synset -namely a group of (near) synonyms -inside the domain dictionaries and knowledge bases, they are used as documents metadata [12][13][14].…”
Section: The Lexical Systemmentioning
confidence: 99%