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19962023
most citedOn Application of Learning to Rank for E-Commerce Search

143 citations · 506 across the 22 of their papers we have counts for

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10 papers · 1 filter

cs.CL2023

Measuring the Effect of Influential Messages on Varying Personas

Chenkai Sun, Jinning Li, Hou Pong Chan +2

Predicting how a user responds to news events enables important applications such as allowing intelligent agents or content producers to estimate the effect on different communitie…

cs.CL2022

Entity Set Co-Expansion in StackOverflow

Yu Zhang, Yunyi Zhang, Yucheng Jiang +5

Given a few seed entities of a certain type (e.g., Software or Programming Language), entity set expansion aims to discover an extensive set of entities that share the same type as…

cs.CL2022★ 3 cited

Improving Candidate Retrieval with Entity Profile Generation for Wikidata Entity Linking

Tuan Manh Lai, Heng Ji, ChengXiang Zhai

Entity linking (EL) is the task of linking entity mentions in a document to referent entities in a knowledge base (KB). Many previous studies focus on Wikipedia-derived KBs. There…

cs.CL2022★ 1 cited

Domain Representative Keywords Selection: A Probabilistic Approach

Pritom Saha Akash, Jie Huang, Kevin Chen-Chuan Chang +3

We propose a probabilistic approach to select a subset of a \textit{target domain representative keywords} from a candidate set, contrasting with a context domain. Such a task is c…

cs.CL2021★ 1 cited

BERT might be Overkill: A Tiny but Effective Biomedical Entity Linker based on Residual Convolutional Neural Networks

Tuan Lai, Heng Ji, ChengXiang Zhai

Biomedical entity linking is the task of linking entity mentions in a biomedical document to referent entities in a knowledge base. Recently, many BERT-based models have been intro…

cs.CL2021

Fine-Grained Chemical Entity Typing with Multimodal Knowledge Representation

Chenkai Sun, Weijiang Li, Jinfeng Xiao +3

Automated knowledge discovery from trending chemical literature is essential for more efficient biomedical research. How to extract detailed knowledge about chemical reactions from…