Optimizing feature set for Chinese Word Sense Disambiguation

The Effect of the Number of Features to Supervised Chinese Word Sense Disambiguation

Although feature selection is very important during either supervised or unsupervised word sense disambiguation processing, there is no systematic study on investigating the relationship between the number of features and the performance as we know yet. This paper investigates the effect of the number of features to supervised Chinese word sense disambiguation through thousands of experiments o...

رفع ابهام معنایی واژگان مبهم فارسی با مدل موضوعی LDA

Word sense disambiguation is the task of identifying the correct sense for the word in a given context among a finite set of possible sense. In this paper a model for farsi word sense disambiguation is presented. The model use two group of features: first, all word and stop words around target word and topic models as second features. We extract topics from a farsi corpus with Latent Dirichlet ...

A Chinese Corpus with Word Sense Annotation

This paper presents the construction of a Chinese word sense-tagged corpus. The resulting lexical resource includes mainly three components: 1) a corpus annotated with word senses; 2) a lexicon containing sense distinction and description in the feature-based formalism; 3) the linking between the sense entries in the lexicon and CCD synsets. A dynamic model is put forward to build the three kno...

詞義辨識: 機器學習演算法特徵的選取與組合 (Feature Selections in Word Sense Disambiguation) [In Chinese]

An Equivalent Pseudoword Solution to Chinese Word Sense Disambiguation

This paper presents a new approach based on Equivalent Pseudowords (EPs) to tackle Word Sense Disambiguation (WSD) in Chinese language. EPs are particular artificial ambiguous words, which can be used to realize unsupervised WSD. A Bayesian classifier is implemented to test the efficacy of the EP solution on Senseval-3 Chinese test set. The performance is better than state-of-the-art results wi...