Word Sense Disambiguation with Chinese Wordnet
Date Issued
2016
Date
2016
Author(s)
Wu, Yi-An
Abstract
The aim of the thesis attempts to establish a sense tagger for the Chinese Wordnet, which is an important representations of lexical semantics and provides distinction of senses and lexical semantic relations. The construction of the sense tagger requires the techniques of Word Sense Disambiguation (WSD), which is an old but still unsolved problem in Natural Language Processing (NLP). The approaches of the study involve the supervised learning methods and the neural word embeddings for certain lexical samples. The training corpora are the human annotated texts from Sinica Corpus and PTT Corpus. The LOPE Text Analytics, which is the implementation of the study, provides several applications including sense tagger and other text analytic modules for researchers.
Subjects
Chinese Wordnet
Word Sense Disambiguation
Sense Tagging
Supervised Learning
Neural Word Embedding
Type
thesis
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ntu-105-R02142007-1.pdf
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