Papers by Gregor Leusch

2 papers
Quality Estimation for Automatically Generated Titles of eCommerce Browse Pages (N18-3)

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Challenge: We are generating millions of titles using machine translation, but they are prone to errors.
Approach: They propose a Random Forest model which explores hand-crafted features and new features . they also propose SNs which embed metadata and generated title in the same space .
Outcome: The proposed models outperform the existing models on in-house data.
Multi-lingual neural title generation for e-Commerce browse pages (N18-3)

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Challenge: e-Commerce websites are automatically generating millions of browse pages . manual creation of titles is infeasible due to the huge number of browse page types .
Approach: They propose to use sequence-to-sequence models to generate titles for languages . they train the models on multi-lingual data, thereby creating one joint model .
Outcome: The proposed model can generate titles in three different languages, with a focus on low-resource French.

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