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The Contribution of Lyrics and Acoustics to Collaborative Understanding of Mood
We find that a pretrained transformer-based language model in a zero-shot setting -- i. e., out of the box with no further training on our data -- is powerful for capturing song-mood associations.
CEQE: Contextualized Embeddings for Query Expansion
We find that CEQE outperforms static embedding-based expansion methods on multiple collections (by up to 18% on Robust and 31% on Deep Learning on average precision) and also improves over proven probabilistic pseudo-relevance feedback (PRF) models.
Semantic Driven Fielded Entity Retrieval
A common approach for knowledge-base entity search is to consider an entity as a document with multiple fields.
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