Automatically building research reading lists

@inproceedings{Ekstrand2010AutomaticallyBR,
  title={Automatically building research reading lists},
  author={Michael D. Ekstrand and P. Kannan and J. Stemper and John T. Butler and J. Konstan and J. Riedl},
  booktitle={RecSys '10},
  year={2010}
}
All new researchers face the daunting task of familiarizing themselves with the existing body of research literature in their respective fields. Recommender algorithms could aid in preparing these lists, but most current algorithms do not understand how to rate the importance of a paper within the literature, which might limit their effectiveness in this domain. We explore several methods for augmenting existing collaborative and content-based filtering algorithms with measures of the influence… Expand
An Analysis of Citation Recommender Systems: Beyond the Obvious
A graph based approach to scientific paper recommendation
Automatic Generation of Initial Reading Lists: Requirements and Solutions
RTRS: a recommender system for academic researchers
Exploiting the wisdom of social connections to make personalized recommendations on scholarly articles
Topical PageRank: A Model of Scientific Expertise for Bibliographic Search
From Community Detection to Mentor Selection in Rating-Free Collaborative Filtering
Scientific publication recommendations based on collaborative citation networks
...
1
2
3
4
5
...

References

SHOWING 1-3 OF 3 REFERENCES
Evaluation of Item-Based Top-N Recommendation Algorithms
Algorithms for estimating relative importance in networks
Authoritative sources in a hyperlinked environment