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Challenges and solutions for synthesis of knowledge regarding collaborative filtering algorithms

Creator:

Lowd, Daniel, Godde, Olivier, McLaughlin, Matthew, Nong, Shuzhen, Wang, Yun, and Herlocker, Jonathan L.

Abstract:

Collaborative filtering (CF)-based recommender systems predict what items a user will like or find useful based on the recommendations (active or implicit) of other members of a networked community. In spite of more than ten years of research, there is little consensus on state-of-the-art knowledge regarding CF predictive algorithms. There...

Resource Type:

Research Paper

Full Text:

for Synthesis of Knowledge Regarding Collaborative Filtering Algorithms Daniel Lowd†, Olivier Godde
Collaborative filtering: possibilities for libraries

Creator:

Webster, Janet G., Herlocker, Jonathan L., Pennington-Lehman, Heather, and Jung, Seikyung

Abstract:

As librarians, we recognize that users seldom approach a research project with a clear search strategy and thus we develop means to help them clarify their research objectives. However, our traditional methods do not translate well to the web environment, while at the same time demand for web access increases....

Resource Type:

Conference Proceeding