
Catia Blengino
Improving Document Summarization Using Crosslingual Word Embeddings.
Rel. Luca Cagliero, Paolo Garza. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering), 2020
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Abstract: |
In recent years, due to the increase of information available online in multiple languages and the inability of a user to examine it manually, several text summarization techniques have been developed. This thesis proposes a new methodology to extract significant sentences from a collection of textual documents written in multiple languages. Specifically, it aims at extracting a summary in any of the source languages by exploiting also the semantic relationships between cross-lingual content. To this purpose, it exploits aligned word embedding models to extract cross-lingual relationships and a graph-based approach to pick the most significant sentences. The results demonstrate that using cross-lingual text correlations improves summarizer performance. |
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Relators: | Luca Cagliero, Paolo Garza |
Academic year: | 2019/20 |
Publication type: | Electronic |
Number of Pages: | 83 |
Subjects: | |
Corso di laurea: | Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering) |
Classe di laurea: | New organization > Master science > LM-32 - COMPUTER SYSTEMS ENGINEERING |
Aziende collaboratrici: | UNSPECIFIED |
URI: | http://webthesis.biblio.polito.it/id/eprint/14348 |
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