This paper presents a comparison of three computational approaches to selectional preferences: (i) an intuitive distributional approach that uses second-order co-occurrence of pre...
A number of recent systems for unsupervised featurebased learning of object models take advantage of cooccurrence: broadly, they search for clusters of discriminative features tha...
Distributional, corpus-based descriptions have frequently been applied to model aspects of word meaning. However, distributional models that use corpus data as their basis have on...
We present a simple framework to model contextual
relationships between visual concepts. The new framework
combines ideas from previous object-centric methods
(which model conte...
Nikhil Rasiwasia (University Of California, San Di...
— A novel framework to context modeling, based on the probability of co-occurrence of objects and scenes is proposed. The modeling is quite simple, and builds upon the availabili...