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2020 | OriginalPaper | Chapter

Similarity Evaluation with Wikipedia Features

Authors : Shahbaz Wasti, Jawad Hussain, Guangjiang Huang, Yuncheng Jiang

Published in: Intelligent Information Processing X

Publisher: Springer International Publishing

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Abstract

Wikipedia provides rich semantic features e.g., text, link, and category structure. These features can be used to compute semantic similarity (SS) between words or concepts. However, some existing Wikipedia-based SS methods either rely on a single feature or do not incorporate the underlying statistics of different features. We propose novel vector representations of Wikipedia concepts by integrating their multiple semantic features. We utilize the available statistics of these features in Wikipedia to compute their weights. These weights signify the contribution of each feature in similarity evaluation according to its level of importance. The experimental evaluation shows that our new methods obtain better results on SS datasets in comparison with state-of-the-art SS methods.

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Metadata
Title
Similarity Evaluation with Wikipedia Features
Authors
Shahbaz Wasti
Jawad Hussain
Guangjiang Huang
Yuncheng Jiang
Copyright Year
2020
DOI
https://doi.org/10.1007/978-3-030-46931-3_10

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