We present a system that learns to follow navigational natural language directions. Where traditional models learn from linguistic annotation or word distributions, our approach i...
Stemming algorithms find canonical forms for inflected words, e. g. for declined nouns or conjugated verbs. Since such a unification of words with respect to gender, number, time, ...
Computational models of grounded language learning have been based on the premise that words and concepts are learned simultaneously. Given the mounting cognitive evidence for conc...
Many cooperated web cache systems and protocols have been proposed. But, these systems need the expensive resources, such as core-link bandwidth and proxy cpu or storage, and need...
In this work, a novel probability distribution is proposed to model sparse directional data. The Directional Laplacian Distribution (DLD) is a hybrid between the linear Laplacian d...