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7 papers · 2 filters
Teaching a New Dog Old Tricks: Resurrecting Multilingual Retrieval Using Zero-shot Learning
Sean MacAvaney, Luca Soldaini, Nazli Goharian
While billions of non-English speaking users rely on search engines every day, the problem of ad-hoc information retrieval is rarely studied for non-English languages. This is prim…
Research Commentary on Recommendations with Side Information: A Survey and Research Directions
Zhu Sun, Qing Guo, Jie Yang +4
Recommender systems have become an essential tool to help resolve the information overload problem in recent decades. Traditional recommender systems, however, suffer from data spa…
A Study of Context Dependencies in Multi-page Product Search
Keping Bi, Choon Hui Teo, Yesh Dattatreya +2
In product search, users tend to browse results on multiple search result pages (SERPs) (e.g., for queries on clothing and shoes) before deciding which item to purchase. Users' cli…
Leverage Implicit Feedback for Context-aware Product Search
Keping Bi, Choon Hui Teo, Yesh Dattatreya +2
Product search serves as an important entry point for online shopping. In contrast to web search, the retrieved results in product search not only need to be relevant but also shou…
A Zero Attention Model for Personalized Product Search
Qingyao Ai, Daniel N. Hill, S. V. N. Vishwanathan +1
Product search is one of the most popular methods for people to discover and purchase products on e-commerce websites. Because personal preferences often have an important influenc…
Generative Question Refinement with Deep Reinforcement Learning in Retrieval-based QA System
Ye Liu, Chenwei Zhang, Xiaohui Yan +2
In real-world question-answering (QA) systems, ill-formed questions, such as wrong words, ill word order, and noisy expressions, are common and may prevent the QA systems from unde…