Information filtering and information retrieval: two sides of the same coin?
Communications of the ACM - Special issue on information filtering
Combining collaborative filtering with personal agents for better recommendations
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Modern Information Retrieval
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
SimRank: a measure of structural-context similarity
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Content-boosted collaborative filtering for improved recommendations
Eighteenth national conference on Artificial intelligence
Robust and efficient fuzzy match for online data cleaning
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
P-Grid: a self-organizing structured P2P system
ACM SIGMOD Record
A collaborative filtering algorithm and evaluation metric that accurately model the user experience
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Domain-independent data cleaning via analysis of entity-relationship graph
ACM Transactions on Database Systems (TODS)
Merging the results of approximate match operations
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Trend detection in folksonomies
SAMT'06 Proceedings of the First international conference on Semantic and Digital Media Technologies
Information retrieval in folksonomies: search and ranking
ESWC'06 Proceedings of the 3rd European conference on The Semantic Web: research and applications
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In this paper we present metadata based recommendation algorithms addressing two scenarios within social desktop communities: a) recommendation of resources from the co-worker's desktop, and b) recommendation of metadata for enriching the own annotation layer. Together with the algorithms we present first evaluation results as well as empirical evaluations showing that metadata based recommendations can be used in such distributed social desktop communities.