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Height Optimized Tries

We present the Height Optimized Trie (HOT), a fast and space-efficient in-memory index structure. The core algorithmic idea of HOT is to dynamically vary the number of bits considered at each node, which enables a consistently high fanout and thereby …

Report on the 1st Workshop on the Perspectives on the Evaluation of Recommender Systems (PERSPECTIVES 2021) at RecSys 2021

Leveraging Affective Hashtags for Ranking Music Recommendations

Support the underground: characteristics of beyond-mainstream music listeners

User models for multi-context-aware music recommendation

User Models for Culture-Aware Music Recommendation: Fusing Acoustic and Cultural Cues

Creative GANs for generating poems, lyrics, and metaphors

Understanding User-curated Playlists on Spotify: A Machine Learning Approach

SentiStorm: Realtime Sentiment Detection von Tweets

Guided Curation of Semistructured Data in Collaboratively-built Knowledge Bases