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HLT @ DISP, Tor Vergata

Prof. Maria Teresa PAZIENZA Prof. Roberto BASILI 2-4 Researchers 1-2 PhD students 1-2 Visiting scientists URL: ai-nlp.info.uniroma2.it. HLT @ DISP, Tor Vergata. The AI-NLP group at Computer Science Dept. HLT @ Rome, Tor Vergata. Aree di Ricerca: Ingegneria delle Lingue

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HLT @ DISP, Tor Vergata

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  1. Prof. Maria Teresa PAZIENZA Prof. Roberto BASILI 2-4 Researchers 1-2 PhD students 1-2 Visiting scientists URL: ai-nlp.info.uniroma2.it HLT @ DISP, Tor Vergata The AI-NLP group at Computer Science Dept

  2. HLT @ Rome, Tor Vergata Aree di Ricerca: • Ingegneria delle Lingue • Metodi robusti per il TAL • Modelli Computazionali del Lessico e Disambiguazione del Senso • Apprendimento Automatico per il TAL su larga scala • Applicationi del TAL: • Information Extraction e Retrieval (Categorizzazione) • Question Answering • Ingegneria della Conoscenza Ontologica mediata linguisticamente

  3. Sistemi HLT @ DISP, Tor Vergata • ARIOSTO (’92): Acquisizione Automatica di conoscenza lessicale • CHAOS (’98.02): Analizzatore sintattico (Italiano, Inglese) • RGL (’97): Analisi formale dei concetti per l’acquisizione di schemi di sottocategorizzazione verbale (Reticoli di GALOIS) • GoDoT (‘98): Disambiguazione Semantica • SATOR (’00): Apprendimento Automatico di schemi per IE • ONTOLOAD (’01): Acquisizione di ontologie di dominio a partire dai testi

  4. Analisi Sintattica • Riconoscimento Grammaticale Robusto (CHAOS) (Basili et al., ECAI98, IWPT2000, NLE2002) • Modularità e Lesssicalizzazione (Ing/It) • Rappresentazione OO (orientata agli oggetti) dei dati linguistici • 6 fasi inernedie di eaborazione grammaticale (e.g. etichettatura sintattica, i.e. POS tagging) • Riusabilita’ tra lingue e domini diversi • 80% Prec/Rec per l’inglese (IWPT’00) • 90 p/sec (per l’italiano e l’inglese) (Ecai ‘98)

  5. Analisi Sintattica: CHAOS

  6. HLT @ Rome, Tor Vergata Progetti Internazionali (EU Esprit, 5-6 FW) • ECRAN (97-98)Apprendimento lessicale per IE adattivo • TREVI (99-00) Categorizzazione e personalizzazione basata sul testo • NAMIC (00-02) Hyperlinking multilinguale su flussi di notizie di agenzia • MOSES (02-04)Question Answering basato su ontologie • PrestoSpace (04-) Indicizzazione ed Interrogazione Semantica di dati multimediali (RAI)

  7. The NAMIC architecture News streams NAMIC English MS English EM XML Objective Representation Hyperlinking Engine Italian MS Italian EM Spanish MS Spanish EM World Model Multilingual Hypernews Engine Language processors NAMIC monitor

  8. Il progetto: PrestoSpace • The objective of the project is to provide technical devices and systems for digital preservation of all types of audio-visual collections. The aim is to build-up preservation factories providing affordable services to all kinds of collections owners to manage and distribute their assets. • The 20th Century was the first with an audiovisual record. Audiovisual media became the new form of cultural expression. These historical, cultural and commercial assets are now entirely at risk from deterioration. • Broadcasters have begun to digitise their large holdings, at high cost and using complex technology. The preservation factory approach aims for an integrated automated solution of sufficient low cost so that the small-to-medium collections can be saved through common standardised services.

  9. The Partnership

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