3 papers
cs.IR2025
A Simple but Effective Elaborative Query Reformulation Approach for Natural Language Recommendation
Qianfeng Wen, Yifan Liu, Justin Cui +4
Natural Language (NL) recommender systems aim to retrieve relevant items from free-form user queries and item descriptions. Existing systems often rely on dense retrieval (DR), whi…
cs.CL2025
Q-STRUM Debate: Query-Driven Contrastive Summarization for Recommendation Comparison
George-Kirollos Saad, Scott Sanner
Query-driven recommendation with unknown items poses a challenge for users to understand why certain items are appropriate for their needs. Query-driven Contrastive Summarization (…
cs.IR2024
Elaborative Subtopic Query Reformulation for Broad and Indirect Queries in Travel Destination Recommendation
Qianfeng Wen, Yifan Liu, Joshua Zhang +4
In Query-driven Travel Recommender Systems (RSs), it is crucial to understand the user intent behind challenging natural language(NL) destination queries such as the broadly worded…