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Tesi etd-05262009-114423


Thesis type
Tesi di laurea specialistica
Author
BENOTTO, GIULIA
URN
etd-05262009-114423
Title
Semantic relation extraction and classification. Experiments on Wikipedia.it
Struttura
INTERFACOLTA'
Corso di studi
INFORMATICA UMANISTICA
Commissione
Relatore Prof. Lenci, Alessandro
Parole chiave
  • relation classification
  • wikipedia
  • semantic web
  • relation extraction
Data inizio appello
11/06/2009;
Consultabilità
completa
Riassunto analitico
Semantic relations between concepts or entities exist in textual documents, keywords or key<br>phrases, and tags generated in social tagging systems. Relation extraction refers to the<br>identification and assignment of relations between concepts or entities. Basically, it can explore relations that are implicit to underlying data and then add new knowledge to the different domains. <br>The purpose of our work was to develop a semi-unsupervised system that was able to automatically extract semantical relations between nominals in a dump extracted from the ialian Wikipedia in November 2008. In addition, we wanted it to correctly classify semantical relations between nominals. <br>We used a seed-based, pattern-based, semi-unsupervised approach for Relation extraction, while we implemented a variation of Vector Space Model for relation classification. we used manually selected seeds for both purposes. in addition, we implemented a script for the automatic extraction of seed pair to be used with our algorithm.
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