June 2, 2019 Book section Closed Access

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

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{
  "DOI": "10.1007/978-3-030-21348-0_38", 
  "abstract": "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.", 
  "author": [
    {
      "family": "Enrico Palumbo"
    }, 
    {
      "family": "Alberto Buzio"
    }, 
    {
      "family": "Andrea Gaiardo"
    }, 
    {
      "family": "Giuseppe Rizzo"
    }, 
    {
      "family": "Raphael Troncy"
    }, 
    {
      "family": "Elena Baralis"
    }
  ], 
  "id": "31222", 
  "issued": {
    "date-parts": [
      [
        2019, 
        6, 
        2
      ]
    ]
  }, 
  "language": "und", 
  "note": "", 
  "title": "TinderBook: Fall in love with culture", 
  "type": "chapter"
}