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TinderBook: Fall in love with culture

Enrico Palumbo; Alberto Buzio; Andrea Gaiardo; Giuseppe Rizzo; Raphael Troncy; Elena Baralis


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  "@id": "https://doi.org/10.1007/978-3-030-21348-0_38", 
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      "name": "Enrico Palumbo"
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      "name": "Alberto Buzio"
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      "name": "Andrea Gaiardo"
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    {
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      "name": "Giuseppe Rizzo"
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      "name": "Raphael Troncy"
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    {
      "@type": "Person", 
      "name": "Elena Baralis"
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  ], 
  "datePublished": "2019-06-02", 
  "description": "More than 2 millions of new books are published every year and choosing a good book among the huge amount of available options can be a challenging endeavor. Recommender systems help in choosing books by providing personalized suggestions based on the user reading history. However, most book recommender systems are based on collaborative filtering, involving a long onboarding process that requires to rate many books before providing good recommendations. Tinderbook provides book recommendations, given a single book that the user likes, through a card-based playful user interface that does not require an account creation. Tinderbook is strongly rooted in semantic technologies, using the DBpedia knowledge graph to enrich book descriptions and extending a hybrid state-of-the-art knowledge graph embeddings algorithm to derive an item relatedness measure for cold start recommendations. Tinderbook is publicly available (http://www.tinderbook.it) and has already generated interest in the public, involving passionate readers, students, librarians, and researchers. The online evaluation shows that Tinderbook achieves almost 50% of precision of the recommendations.", 
  "headline": "TinderBook: Fall in love with culture", 
  "identifier": "https://doi.org/10.1007/978-3-030-21348-0_38", 
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  "license": "https://creativecommons.org/licenses/by/4.0/", 
  "name": "TinderBook: Fall in love with culture", 
  "url": "https://www.openaccessrepository.it/record/31222"
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