Geometric Algebra Rotors for Sub-Symbolic Coding of Natural Language Sentences (Contributo in atti di convegno)

Type
Label
  • Geometric Algebra Rotors for Sub-Symbolic Coding of Natural Language Sentences (Contributo in atti di convegno) (literal)
Anno
  • 2007-01-01T00:00:00+01:00 (literal)
Alternative label
  • Pilato Giovanni; Gaglio Salvatore; Vassallo Giorgio; Augello Agnese (2007)
    Geometric Algebra Rotors for Sub-Symbolic Coding of Natural Language Sentences
    in 11th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES 2007) - XVII Italian Workshop on Neural Networks, Vietri sul Mare, Italy, 12-14 September 2007
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Pilato Giovanni; Gaglio Salvatore; Vassallo Giorgio; Augello Agnese (literal)
Pagina inizio
  • 42 (literal)
Pagina fine
  • 51 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#titoloVolume
  • Knowledge-Based Intelligent Information and Engineering Systems: KES 2007 - WIRN 2007, Pt I, Proceedings (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#volumeInCollana
  • 4692 (literal)
Note
  • ISI Web of Science (WOS) (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • ICAR; DINFO (literal)
Titolo
  • Geometric Algebra Rotors for Sub-Symbolic Coding of Natural Language Sentences (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn
  • 978-3-540-74817-5 (literal)
Abstract
  • A sub-symbolic encoding methodology for natural language sentences is presented. The procedure is based on the creation of an LSA-inspired semantic space and associates rotation operators derived from Geometric Algebra to word bigrams of the sentence. The operators are subsequently applied to an orthonormal standard basis of the created semantic space according to the order in which words appear in the sentence. The final rotated basis is then coded as a vector and its orthogonal part constitutes the sub-symbolic coding of the sentence. Preliminary experimental results for a classification task, compared with the traditional LSA methodology, show the effectiveness of the approach. (literal)
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