Concept drifting is an important and challenging research issue in the field of machine learning. This paper mainly addresses the issue of semantic concept drifting in time series...
This poster reports upon the ongoing efforts being made to establish TREC-like and other comprehensive evaluation paradigms within the Music IR (MIR) and Music Digital Library (MD...
There has been recent interest in collecting user or assessor preferences, rather than absolute judgments of relevance, for the evaluation or learning of ranking algorithms. Since...
Taking advantage of the well-known cluster hypothesis that “closely associated documents tend to be relevant to the same request”, we can use inter-document similarity to prov...
The ability to accurately judge the similarity between natural language sentences is critical to the performance of several applications such as text mining, question answering, an...