Papers by Paola Velardi
Multiple Knowledge GraphDB (MKGDB) (2020.lrec-1)
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| Challenge: | ConceptNet, DBpedia, WebIsAGraph, WordNet and Wikipedia category hierarchy are used to create a large-scale graph database. |
| Approach: | They propose to use multiple taxonomy backbones extracted from 5 existing knowledge graphs to create a large-scale graph database. |
| Outcome: | The proposed database is intended to favour and support the development of open-domain natural language processing applications relying on knowledge bases. |
A Large Interlinked Knowledge Graph of the Italian Cultural Heritage (2022.lrec-1)
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| Challenge: | Existing efforts to create knowledge bases are limited to relatively small resources, such as entities from libraries, archeological sites and museums. |
| Approach: | They propose to create a large knowledge graph linking Italian cultural heritage entities with concepts defined on well-known knowledge bases. |
| Outcome: | The proposed graph shows that the Italian cultural heritage entities are interlinked with concepts defined on well-known knowledge bases. |
A Large Multilingual and Multi-domain Dataset for Recommender Systems (L18-1)
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| Challenge: | Existing algorithms for recommending items are limited and focused on specific domains. |
| Approach: | They propose a multi-domain interests dataset to train and test Recommender Systems . the english dataset includes an average of 90 preferences per user on music, books, movies, celebrities, sport, politics . |
| Outcome: | The proposed method exploits popular services such as Spotify, Goodreads and others to extract preferences from Twitter messages in Italian and English. |