Loading...
Search for:
tagging
0.058 seconds
Sense Tagging a Persian Corpus
, M.Sc. Thesis Sharif University of Technology ; Khosravizade, Parvaneh (Supervisor) ; Shams Fard, Mehrnoosh (Co-Advisor)
Abstract
The main focus of this research is to resolve the semantic ambiguity in Persian. In this study, a semi-supervised machine learning method is proposed to choose the most proper meaning of a target word in the context. Several statistical methods are compared, and the most accurate one is chosen for developing a sense tagger. An initial seed data is built by searching collocation lists for each sense. After developing the sense tagger and initial seed set, a bootstrapping method is used to sense tag all occurences of a target word in corpus with 90% accuracy