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Tesi etd-05262009-114423
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Tipo di tesi Tesi di laurea specialistica
Autore BENOTTO, GIULIA
URN etd-05262009-114423
Titolo Semantic relation extraction and classification. Experiments on Wikipedia.it
Settore scientifico disciplinare INTERFACOLTA'
Corso di studi INFORMATICA UMANISTICA
Commissione
Nome Commissario Qualifica
Prof. Alessandro Lenci Relatore
Parole chiave
  • relation classification
  • wikipedia
  • semantic web
  • relation extraction
Data inizio appello 2009-06-11
Disponibilità unrestricted
Riassunto analitico
Semantic relations between concepts or entities exist in textual documents, keywords or key
phrases, and tags generated in social tagging systems. Relation extraction refers to the
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.
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.
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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