Evaluating Various Linguistic Features on Semantic Relation Extraction
Authors | Marcos Garcia Pablo Gamallo |
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Publication date | 2011 |
ISSN | 13138502 |
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Evaluating Various Linguistic Features on Semantic Relation Extraction - scientific work about Wikipedia quality published in 2011, written by Marcos Garcia and Pablo Gamallo.
Overview
Machine learning approaches for Information Extraction use different types of features to acquire semantically related terms from free text. These features may contain several kinds of linguistic knowledge: from orthographic or lexical to more complex features, like PoStags or syntactic dependencies. In this paper authors select fourmain types of linguistic features and evaluate their performance in a systematic way. Despite the combination of some types of features allows us to improve the f-score of the extraction, authors observed that by adjusting the positive and negative ratio of the training examples, authors can build high quality classifiers with just a single type of linguistic feature, based on generic lexico-syntactic patterns. Experiments were performed on the Portuguese version of Wikipedia.
Embed
Wikipedia Quality
Garcia, Marcos; Gamallo, Pablo. (2011). "[[Evaluating Various Linguistic Features on Semantic Relation Extraction]]". ICIC Express Letters Volume 5, Issue 12, December 2011, pp. 4395-4401. ISSN: 13138502.
English Wikipedia
{{cite journal |last1=Garcia |first1=Marcos |last2=Gamallo |first2=Pablo |title=Evaluating Various Linguistic Features on Semantic Relation Extraction |date=2011 |issn=13138502 |url=https://wikipediaquality.com/wiki/Evaluating_Various_Linguistic_Features_on_Semantic_Relation_Extraction |journal=ICIC Express Letters Volume 5, Issue 12, December 2011, pp. 4395-4401}}
HTML
Garcia, Marcos; Gamallo, Pablo. (2011). "<a href="https://wikipediaquality.com/wiki/Evaluating_Various_Linguistic_Features_on_Semantic_Relation_Extraction">Evaluating Various Linguistic Features on Semantic Relation Extraction</a>". ICIC Express Letters Volume 5, Issue 12, December 2011, pp. 4395-4401. ISSN: 13138502.