Abstract. This paper describes an experimental comparison between two standard supervised learning methods, namely Naive Bayes and Exemplar–basedclassification, on the Word Sens...
This paper addresses the issue of word-sense ambiguity in extraction from machine-readable resources for the construction of large-scale knowledge sources. We describe two experim...
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...
This paper presents an algorithm for unsupervised noun sense induction, based on clustering of Web search results. The algorithm does not utilize labeled training instances or any...
Goldee Udani, Shachi Dave, Anthony Davis, Tim Sibl...
— In this paper we propose a new technique allowing to map descriptive data into relative distance space, which is based primarily on senses of the terms stored in our data. We u...
M. Shahriar Hossain, Monika Akbar, Rafal A. Angryk