On the value of purpose-orientation and focus on locals in recommending leisure activities

Beatrice Valeri, Fabio Casati, Florian Daniel

Результат исследований: Материалы для журналаСтатья

1 Цитирования (Scopus)

Аннотация

Recommender systems are omnipresent today, especially on the Web, and the quality of their recommendations is crucial for user satisfaction. Unlike most works on the topic, in this article we do not focus on the algorithmic side of the problem (i.e., searching for the algorithm that better learns from the collected user feedback) and instead study the importance of the data in input to the algorithms, identifying the information that should be collected from users to build better recommendations. We study restaurant recommendations for locals and show that fine-tuned data and state-of-the-art algorithms can outperform the leading recommendation service, TripAdvisor. The findings make a case for better-thought and purpose-tailored data collection techniques.

Язык оригиналаАнглийский
Страницы (с-по)63-74
Число страниц12
ЖурналJournal of Web Engineering
Том16
Номер выпуска1-2
СостояниеОпубликовано - 1 мар 2017
Опубликовано для внешнего пользованияДа

ASJC Scopus subject areas

  • Software
  • Information Systems
  • Computer Networks and Communications

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