This paper investigates using social tags for the purpose of making personalized content recommendations. Our tag-based recommender creates a personalized bookmark recommendation ...
Pavan Kumar Vatturi, Werner Geyer, Casey Dugan, Mi...
We study the problem of context-sensitive ranking for document retrieval, where a context is defined as a sub-collection of documents, and is specified by queries provided by do...
This paper presents an ontology-based semantic portal, SEMPort, which aims to support both content providers and the users of the portal during providing information, browsing and...
Melike Sah, Wendy Hall, Nicholas Gibbins, David De...
We introduce a new dissimilarity function for ranked lists, the expected weighted Hoeffding distance, that has several advantages over current dissimilarity measures for ranked s...
Users who are unfamiliar with database query languages can search XML data sets using keyword queries. Current approaches for supporting such queries are either for textcentric XM...