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20152022
most citedSTFNets: Learning Sensing Signals from the Time-Frequency Perspective with Short-Time Fourier Neural Networks

71 citations · 246 across the 22 of their papers we have counts for

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14 papers · 1 filter

cs.CL202221 cited

OA-Mine: Open-World Attribute Mining for E-Commerce Products with Weak Supervision

Xinyang Zhang, Chenwei Zhang, Xian Li +4

Automatic extraction of product attributes from their textual descriptions is essential for online shopper experience. One inherent challenge of this task is the emerging nature of…

cs.CL201921 cited

HiExpan: Task-Guided Taxonomy Construction by Hierarchical Tree Expansion

Jiaming Shen, Zeqiu Wu, Dongming Lei +5

Taxonomies are of great value to many knowledge-rich applications. As the manual taxonomy curation costs enormous human effects, automatic taxonomy construction is in great demand.…

cs.CL2019

SetExpan: Corpus-Based Set Expansion via Context Feature Selection and Rank Ensemble

Jiaming Shen, Zeqiu Wu, Dongming Lei +3

Corpus-based set expansion (i.e., finding the "complete" set of entities belonging to the same semantic class, based on a given corpus and a tiny set of seeds) is a critical task i…

cs.CL2019

Task-Guided Pair Embedding in Heterogeneous Network

Chanyoung Park, Donghyun Kim, Qi Zhu +2

Many real-world tasks solved by heterogeneous network embedding methods can be cast as modeling the likelihood of pairwise relationship between two nodes. For example, the goal of…

cs.CL20182 cited

Weakly-Supervised Hierarchical Text Classification

Yu Meng, Jiaming Shen, Chao Zhang +1

Hierarchical text classification, which aims to classify text documents into a given hierarchy, is an important task in many real-world applications. Recently, deep neural models a…

cs.CL2018

Mining Entity Synonyms with Efficient Neural Set Generation

Jiaming Shen, Ruiliang Lyu, Xiang Ren +3

Mining entity synonym sets (i.e., sets of terms referring to the same entity) is an important task for many entity-leveraging applications. Previous work either rank terms based on…