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Erschienen in:
2020 | OriginalPaper | Buchkapitel
Quality Evaluation
verfasst von : Jose Manuel Gomez-Perez, Ronald Denaux, Andres Garcia-Silva
Erschienen in: A Practical Guide to Hybrid Natural Language Processing
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In the previous chapters we have discussed various methods for generating embeddings for both words and concepts. Once you have applied some embedding learning mechanism you may wonder how good are these embeddings? In this chapter we look at methods for assessing the quality of the learned embeddings: from visualizations to intrinsic evaluations like predicting alignment with human-rated word similarity and extrinsic evaluations based on downstream tasks. As in the previous chapters, we provide hands-on practical sections for gaining experience in applying evaluation methods. We also discuss the methodology and results used for a real-world evaluation of Vecsigrafo compared to various other methods, which provides a sense for how thorough real-world evaluations can be performed.