We propose a weakly-supervised approach for extracting class attributes from structured text available within Web documents. The overall precision of the extracted attributes is a...
Open-text semantic parsers are designed to interpret any statement in natural language by inferring a corresponding meaning representation (MR – a formal representation of its s...
Antoine Bordes, Xavier Glorot, Jason Weston, Yoshu...
In this paper, we present a novel framework for machine learning-based cross-media knowledge extraction. The framework is specifically designed to handle documents composed of th...
This paper addresses the problem of categorizing terms or lexical entities into a predefined set of semantic domains exploiting the knowledge available on-line in the Web. The prop...
Leonardo Rigutini, Ernesto Di Iorio, Marco Ernande...
This paper presents novel methods for classifying images based on knowledge discovered from annotated images using WordNet. The novelty of this work is the automatic class discove...