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.

== Overview ==

A Survey of Trust and Reputation Systems for Online Service Provision
[http://www.oasis-open.org/committees/download.php/28303/JIB2007-DSS-Survey.pdf Link]

== Collaborative Filtering ==
(in order of estimated relevance)

Incremental Collaborative Filtering for Highly-Scalable Recommendation Algorithms
[http://citeseer.ist.psu.edu/papagelis05incremental.html Link] [[BR]]
user-similarity, Pearson-correlation, incremental algorithm

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 Link] [[BR]]
Pearson-correlation, explicit trust, web of trust, decentralized

On User Recommendations Based on Multiple Cues
[http://citeseer.ist.psu.edu/dudek03user.html Link] [[BR]]
user similarity, Pearson-correlation, semantic features, user-specified features

Item-based Collaborative Filtering Recommendation Algorithms
[http://citeseer.ist.psu.edu/sarwar01itembased.html Link] [[BR]]
comparison of item-based recommendation algorithms (performance, quality, similarity) using Pearson-correlation, cosine-similarity, regression

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

Content-Based versus Collaborative Filtering
[http://www.is-frankfurt.de/uploads/down417.pdf Link] [[BR]]
overview, references (Seminararbeit)

Slope One Predictors for Online Rating-Based Collaborative Filtering
[http://citeseer.ist.psu.edu/lemire05slope.html Link] [[BR]]
slope one predictor, quick cold-start

Distributed Collaborative Filtering for Peer-to-Peer File Sharing Systems
[http://ict.ewi.tudelft.nl/pub/jun/sac06.pdf Link] [[BR]]
distributed collaborative filtering, p2p, bayesian

Collaborative Filtering with Privacy via Factor Analysis
[http://www.cs.berkeley.edu/~jfc/'mender/sigir.pdf Link] [[BR]]
expectation maximization (EM), privacy


== Content-based ==

Content-based, Collaborative Recommendation ([http://portal.acm.org/citation.cfm?doid=245108.245124 Link]) [[BR]]
no algorithms given, irrelevant

Improving Interoperability using Query Interpretation in Semantic Vector Spaces ([http://www.springerlink.com/content/r3610g058065m17q/ Link]) [[BR]]
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 Link] [[BR]]
Pearson-correlation