12 citations · 12 across the 3 of their papers we have counts for
6 papers · 1 filter
Embracing Structure in Data for Billion-Scale Semantic Product Search
Vihan Lakshman, Choon Hui Teo, Xiaowen Chu +4
We present principled approaches to train and deploy dyadic neural embedding models at the billion scale, focusing our investigation on the application of semantic product search.…
Extreme Multi-label Learning for Semantic Matching in Product Search
Wei-Cheng Chang, Daniel Jiang, Hsiang-Fu Yu +9
We consider the problem of semantic matching in product search: given a customer query, retrieve all semantically related products from a huge catalog of size 100 million, or more.…
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…
Semantic Product Search
Priyanka Nigam, Yiwei Song, Vijai Mohan +7
We study the problem of semantic matching in product search, that is, given a customer query, retrieve all semantically related products from the catalog. Pure lexical matching via…
Adaptive, Personalized Diversity for Visual Discovery
Choon Hui Teo, Houssam Nassif, Daniel Hill +4
Search queries are appropriate when users have explicit intent, but they perform poorly when the intent is difficult to express or if the user is simply looking to be inspired. Vis…