International Journal of Knowledge and Web Intelligence
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International Journal of Knowledge and Web Intelligence (1 paper in press)
A Method for Word Sense Disambiguation using Unsupervised Deep Belief Network by Nazreena Rahman Abstract: This paper presents a new method to find the correct sense of a word according to its context. Based on collocation extraction score, the proposed method extracts three different features for each sense definition of a target word. These features create a feature vector and all the feature vectors create a sense matrix. Here, an unsupervised Deep Belief Network (DBN) is used to enhance the sense matrix. Comparison of the proposed WSD method is made with current state-of-the-art systems using SENSEVAL and Sem Eval datasets. The proposed WSD method shows the practical implementation by applying on query-based text summary. For evaluation on query-based text summary, the proposed WSD method uses DUC datasets containing news-wire articles and SKE and BC3 datasets containing emails. Finally, the experimental analysis illustrates the significance of the proposed approach over many existing systems. Keywords: Collocation extraction score; Feature vector; Sense matrix; Unsupervised Deep Belief Network (DBN). DOI: 10.1504/IJKWI.2020.10029082