Computational models of meaning trained on naturally occurring text successfully model human performance on tasks involving simple similarity measures, but they characterize meani...
Marco Baroni, Brian Murphy, Eduard Barbu, Massimo ...
Text categorization involves mapping of documents to a fixed set of labels. A similar but equally important problem is that of assigning labels to large corpora. With a deluge of ...
This paper presents an empirical comparison of similarity measures for pairs of concepts based on Information Content. It shows that using modest amounts of untagged text to deriv...
This paper presents a method for measuring the semantic similarity of texts, using corpus-based and knowledge-based measures of similarity. Previous work on this problem has focus...
Measuring information content (IC) from the intrinsic information of an ontology is an important however a formidable task. IC is useful for further measurement of the semantic si...