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Probabilistic word sense disambiguation
Computer Speech & Language, 2004We present a theoretically motivated method for creating probabilistic word sense disambiguation (WSD) systems. The method works by composing multiple probabilistic components: such modularity is made possible by an application of Bayesian statistics and Lidstone's smoothing method. We show that a probabilistic WSD system created along these lines is a
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Smoothing and Word Sense Disambiguation
2004This paper presents an algorithm to apply the smoothing techniques described in [15] to three different Machine Learning (ML) methods for Word Sense Disambiguation (WSD). The method to obtain better estimations for the features is explained step by step, and applied to n-way ambiguities.
Eneko Agirre, David Martínez 0001
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Word Sense Disambiguation Based on Word Sense Clustering
2006In this paper we address the problem of Word Sense Disambiguation by introducing a knowledge-driven framework for the disambiguation of nouns. The proposal is based on the clustering of noun sense representations and it serves as a general model that includes some existing disambiguation methods.
Henry Anaya-Sánchez +2 more
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The Effect of Windowing in Word Sense Disambiguation
2005In this paper, the effect of different windowing schemes to the success rate of word sense disambiguation is probed. In these windowing schemes it is considered that the impact of a neighbor word to the correct sense of the target word should be somewhat related to it’s distance to the target word.
Ergin Altintas +2 more
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Word Sense Disambiguation with GermaNet
2015The subject of this dissertation is boosting research on word sense disambiguation (WSD) for German. WSD is a very active area of research in computational linguistics, but most of the work is focused on English. One of the factors that has hampered WSD research for other languages such as German is the lack of appropriate resources, particularly in ...
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Word Sense Disambiguation Based on Vicarious Words
2008 Fourth International Conference on Natural Computation, 2008This paper presents the concept of vicarious words and develops a new unsupervised Chinese word sense disambiguation method. This method, after statistical learning from the vicarious words, realizes unsupervised word sense disambiguation by calculating mutual information to measure the degree of collocation information between the ambiguous words and ...
Zhimao Lu, Dongmei Fan, Rubo Zhang
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Practice of Word Sense Disambiguation
2018The paper aims at the community of researchers and practitioners that work in the area of natural language processing but do not specialize in the word sense disambiguation (WSD). It contains a brief introduction into WSD and describes the classical approaches to solve the problem.
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Graph and Word Similarity for Word Sense Disambiguation
2020 13th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI), 2020This paper proposes a graph and word similarity method for word sense disambiguation. Perform word sense mapping on the context words of a given ambiguous sentence to obtain the corresponding English words; compute the English word similarity of the obtained English words, and take the English words as vertices, the semantic relations between words as ...
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Margin perceptron for word sense disambiguation
Proceedings of the 2010 Symposium on Information and Communication Technology - SoICT '10, 2010Word Sense Disambiguation (WSD) is an AI-complete problem where senses of words in the documents must be correctly selected from a senses inventory. Support Vector Machines (SVM) method has been successfully applied to supervised WSD. In contrast, perceptron has not been popular in supervised WSD.
Kiem-Hieu Nguyen, Cheol-Young Ock
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Word sense disambiguation by semantic inference
2017 International Conference on Behavioral, Economic, Socio-cultural Computing (BESC), 2017This paper proposes an algorithm for unsupervised Word Sense Disambiguation to bypass the knowledge bottleneck faced by supervised approaches. By simulating the semantic inference process performed by human language users, the algorithm makes use of a thesaurus to obtain potential substitute words for the target word in a sentence, builds substitute ...
Xinda Wang 0003 +3 more
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