193 citations · 501 across the 18 of their papers we have counts for
4 papers · 1 filter
A Transformer-based Embedding Model for Personalized Product Search
Keping Bi, Qingyao Ai, W. Bruce Croft
Product search is an important way for people to browse and purchase items on E-commerce platforms. While customers tend to make choices based on their personal tastes and preferen…
Artemis: A Novel Annotation Methodology for Indicative Single Document Summarization
Rahul Jha, Keping Bi, Yang Li +4
We describe Artemis (Annotation methodology for Rich, Tractable, Extractive, Multi-domain, Indicative Summarization), a novel hierarchical annotation process that produces indicati…
Learning a Fine-Grained Review-based Transformer Model for Personalized Product Search
Keping Bi, Qingyao Ai, W. Bruce Croft
Product search has been a crucial entry point to serve people shopping online. Most existing personalized product models follow the paradigm of representing and matching user inten…
AREDSUM: Adaptive Redundancy-Aware Iterative Sentence Ranking for Extractive Document Summarization
Keping Bi, Rahul Jha, W. Bruce Croft +1
Redundancy-aware extractive summarization systems score the redundancy of the sentences to be included in a summary either jointly with their salience information or separately as…