Below is a list of papers that might be interesting for [wiki:FloriansDiplomaThesis Florian's diploma thesis] or Skipforward in general.

This list is in no way complete or correct, as many papers have not been read, yet, and some were only skimmed. Feel free to add notes, if you found something interesting or useful.


== Collaborative Filtering ==

Distributed Collaborative Filtering for Peer-to-Peer File Sharing Systems
http://ict.ewi.tudelft.nl/pub/jun/sac06.pdf

Collaborative Filtering with Privacy via Factor Analysis
http://www.cs.berkeley.edu/~jfc/'mender/sigir.pdf

Incremental Collaborative Filtering for Highly-Scalable Recommendation Algorithms
http://citeseer.ist.psu.edu/papagelis05incremental.html

Item-based Collaborative Filtering Recommendation Algorithms
http://citeseer.ist.psu.edu/sarwar01itembased.html

On User Recommendations Based on Multiple Cues
http://citeseer.ist.psu.edu/dudek03user.html

Slope One Predictors for Online Rating-Based Collaborative Filtering
http://citeseer.ist.psu.edu/lemire05slope.html

Trust in Recommender Systems
http://portal.acm.org/ft_gateway.cfm?id=1040870&type=pdf&coll=GUIDE&dl=GUIDE&CFID=58637181&CFTOKEN=67159970

Trust-aware Collaborative Filtering for Recommender Systems
http://sra.itc.it/people/massa/publications/massa_paolo_coopis_2004_trust-aware_Collaborative_Filtering_for_Recommender_Systems.pdf

Content-Based versus Collaborative Filtering
http://www.is-frankfurt.de/uploads/down417.pdf


== Content-based ==

 * Content-based, Collaborative Recommendation ([http://portal.acm.org/citation.cfm?doid=245108.245124 Link])
 * Improving Interoperability using Query Interpretation in Semantic Vector Spaces ([http://www.springerlink.com/content/r3610g058065m17q/ Link])
   * The aim of this paper is providing some interoperability between several ontologies for queries. However, as many of our Features also are interrelated/similar, even in the same ontology, we need a similar query expansion technique for computing Feature/Item similarity.


== Context ==
Using Semantic Cues for Contextual Recommendation (1997)
http://clinton.cs.depaul.edu/upe/CTIRS/papers/Ramezani.pdf