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Reading the Mood: Emotion-Guided Book-to-Music Recommendation via CGANs and LLMs

Paper recorded by Signals 4 on 2026-10-05 in cs.CL. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-05 on arXiv · recorded by Signals 4 on 2026-10-06

Category: cs.CL · 自然语言处理 · first seen 2026-10-06

Abstract

Background music that matches the mood of a text has been shown to make readers feel more immersed and improve their reading experience, motivating recommender systems that pair books with mood-matched music. In this direction, we present Sentiment Aware Generative Adversarial Network for Cross Domain Recommendation (SAGA-CDR), a two-phase cross-domain recommendation framework that personalizes mu

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#326 most recent of 660 cs.CL papers we have recorded · ↑ newer: SAFE-MR: Evidence Sufficiency Learning for Selective Multimodal Rumor · ↓ older: MedPrune: Topology-Efficient Multimodal Multi-Agent Communication Evol
Cite this page: Reading the Mood: Emotion-Guided Book-to-Music Recommendation via CGANs and LLMs: the #326 most recent of 660 cs.CL papers we have recorded (as of 2026-10-05). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/reading-the-mood-emotion-guided-book-to-music-recommendation-via-cgans-and-llms.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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