We initiate a novel study of clustering problems. Rather than specifying an explicit objective function to optimize, our framework allows the user of clustering algorithm to speci...
We consider the problem of recommending the best set of k items when there is an inherent ordering between items, expressed as a set of prerequisites (e.g., the course ‘Real Ana...
Clustering hypertext document collection is an important task in Information Retrieval. Most clustering methods are based on document content and do not take into account the hype...
Konstantin Avrachenkov, Vladimir Dobrynin, Danil N...
In recent years, there has been significant interest in development of ranking functions and efficient top-k retrieval algorithms to help users in ad-hoc search and retrieval in da...
Muhammed Miah, Gautam Das, Vagelis Hristidis, Heik...
When attempting to annotate music, it is important to consider both acoustic content and social context. This paper explores techniques for collecting and combining multiple sourc...
Douglas Turnbull, Luke Barrington, Gert R. G. Lanc...