Part-of-speech (POS) tag distributions are known to exhibit sparsity -- a word is likely to take a single predominant tag in a corpus. Recent research has demonstrated that incorp...
We present the first unsupervised approach to the problem of learning a semantic parser, using Markov logic. Our USP system transforms dependency trees into quasi-logical forms, r...
Multi-category bootstrapping algorithms were developed to reduce semantic drift. By extracting multiple semantic lexicons simultaneously, a category's search space may be res...
We present a novel approach to distributionalonly, fully unsupervised, POS tagging, based on an adaptation of the EM algorithm for the estimation of a Gaussian mixture. In this ap...
Determining semantic relatedness between words or concepts is a fundamental process to many Natural Language Processing applications. Approaches for this task typically make use o...
Ziqi Zhang, Anna Lisa Gentile, Lei Xia, José...