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Ctrip Technology
Ctrip Technology
Dec 10, 2020 · Artificial Intelligence

Automatic Extraction of Theme-based Recommendation Reasons: Framework, Model Selection, Data Augmentation, and Optimization

This article presents a comprehensive study on automatically extracting theme‑based recommendation reasons for travel content, detailing a three‑stage retrieval framework, the advantages of interactive matching models over classification, rule‑based and back‑translation data augmentation techniques, and various model optimization strategies including priors, transfer learning, seed selection, optimizer choice, and layer‑wise learning rates.

AINatural Language Processingdata augmentation
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Automatic Extraction of Theme-based Recommendation Reasons: Framework, Model Selection, Data Augmentation, and Optimization