Semisupervied Data Driven Word Sense Disambiguation for Resource-poor Languages
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Word Sense DisambiguationSimilar Papers 제목 키워드 기반
Quantum-inspired Representation for Long-tail Senses of Word Sense Disambiguation
Data imbalance, also known as the long-tailed distribution of data, is an important challenge for data-driven models. Due to the long tail phenomenon of word sense distribution in linguistics, it is difficult to learn ac…
Data AugmentationWord Sense DisambiguationKDSL: a Knowledge-Driven Supervised Learning Framework for Word Sense Disambiguation
We propose KDSL, a new word sense disambiguation (WSD) framework that utilizes knowledge to automatically generate sense-labeled data for supervised learning. First, from WordNet, we automatically construct a semantic kn…
Word Sense DisambiguationA Quadratic 0-1 Programming Approach for Word Sense Disambiguation
Word Sense Disambiguation (WSD) is the task to determine the sense of an ambiguous word in a given context. Previous approaches for WSD have focused on supervised and knowledge-based methods, but inter-sense interactions…
Combinatorial OptimizationWord Sense DisambiguationWord SimilarityChinese Word Sense Embedding with SememeWSD and Synonym Set
Word embedding is a fundamental natural language processing task which can learn feature of words. However, most word embedding methods assign only one vector to a word, even if polysemous words have multi-senses. To add…
Semantic SimilaritySemantic Textual SimilarityWord Sense DisambiguationContext-Aware Semantic Similarity Measurement for Unsupervised Word Sense Disambiguation
The issue of word sense ambiguity poses a significant challenge in natural language processing due to the scarcity of annotated data to feed machine learning models to face the challenge. Therefore, unsupervised word sen…
Semantic SimilaritySemantic Textual SimilarityWord Sense Disambiguation