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...
A variety of web sites and web based services produce textual lists at varying time granularities ranked according to several criteria. For example, Google Trends produces lists o...
We present a novel approach to learn distance metric for information retrieval. Learning distance metric from a number of queries with side information, i.e., relevance judgements...
Local invariant feature based methods have been proven to be effective in computer vision for object recognition and learning. But for an image, the number of points detected and ...
Our system, based on a multiagent framework called collaborative understanding of distributed knowledge (CUDK), is designed with the overall goal of balancing agents' conceptu...