Anzeige
Erschienen in:
2013 | OriginalPaper | Buchkapitel
Taxonomy-Driven Filtering
verfasst von : Cai-Nicolas Ziegler
Erschienen in: Social Web Artifacts for Boosting Recommenders
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
One of the primary issues that recommender systems are facing is rating sparsity, resulting in a decrease of the recommendations’ accuracy.Hence, high-quality product suggestions are only feasible when information density is high, i.e., large numbers of users voting for small numbers of items and issuing large numbers of explicit ratings each. Smaller-sized, decentralized and open communities are typical for the Web 2.0. Here, ratings are mainly derived
implicitly
from user behavior and interaction patterns. However, these communities poorly qualify for blessings provided by recommender systems.