Crossing framework: A dynamic infrastructure to develop knowledge-based recommenders in cross domains

Azak M., Birturk A.

6th International Conference on Web Information Systems and Technologies, WEBIST 2010, Valencia, İspanya, 7 - 10 Nisan 2010, cilt.2, ss.125-130, (Tam Metin Bildiri) identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası: 2
  • Basıldığı Şehir: Valencia
  • Basıldığı Ülke: İspanya
  • Sayfa Sayıları: ss.125-130
  • Anahtar Kelimeler: Cross domain recommendation, Recommendation frameworks, Recommender engines, Recommender systems, Web personalization
  • TED Üniversitesi Adresli: Hayır

Özet

We propose a dynamic framework that differs from the previous works as it focuses on the easy development of knowledge-based recommenders and it proposes an intensive cross domain capability with the help of domain knowledge. The framework has a generic and flexible structure that data models and user interfaces are generated based on ontologies. New recommendation domains can be integrated to the framework easily in order to improve recommendation diversity. We accomplish the cross-domain recommendation via an abstraction in domain features if the direct matching of the domain features is not possible when the domains are not very close to each other.