MMR (Maximum Marginal Relevance) is widely used in summarization for its simplicity and efficacy, and has been demonstrated to achieve comparable performance to other approaches ...
In this paper we propose and evaluate an algorithm that learns a similarity measure for comparing never seen objects. The measure is learned from pairs of training images labeled ...
This paper presents the results of using Roget's International Thesaurus as the taxonomy in a semantic similarity measurement task. Four similarity metrics were taken from th...
Quantitative evaluation and comparison of image segmentation algorithms is now feasible owing to the recent availability of collections of hand-labeled images. However, little att...
— Semantic relatedness between words or concepts is a fundamental problem in many applications of computational linguistics and artificial intelligence. In this paper, a new mea...