2017/04/11 by Zahra Mousavi, Mousavi, Zahra, Heshaam Faili +1
Computer Science · Mathematics · #Advanced Text Analysis Techniques #Natural Language Processing Techniques #Topic Modeling #cs.CL #cs.LG #stat.ML
paper · pdf · doi:10.48550/arxiv.1704.03223
arxiv created 2017/04/11 · arxiv updated 2017/04/12
This paper presents an automated supervised method for Persian wordnet construction. Using a Persian corpus and a bi-lingual dictionary, the initial links between Persian words and Princeton WordNet synsets have been generated. These links will be discriminated later as correct or incorrect by employing seven features in a trained classification system. The whole method is just a classification system, which has been trained on a train set containing FarsNet as a set of correct instances. State of the art results on the automatically derived Persian wordnet is achieved. The resulted wordnet with a precision of 91.18% includes more than 16,000 words and 22,000 synsets.