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Jingrong Feng

dblp:251/9205 · DBLP profile ↗
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3ranked-venue papers
1as first author
1since 2021 · last 2021
0009-0008-4421-8470ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1Databases, data management, data science and information retrieval · 1Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Information extraction and text analysis · 87% Question answering and dialogue systems · 13%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Natural language and speech › Information extraction and text analysis
named entity recognition		 0.412020
A Unified MRC Framework for Named Entity Recognition · ACL 2020
Natural language and speech › Information extraction and text analysis › named entity recognition
nested named entity recognition		 0.412020
A Unified MRC Framework for Named Entity Recognition · ACL 2020
Natural language and speech › Question answering and dialogue systems
machine reading comprehension		 0.112020
A Unified MRC Framework for Named Entity Recognition · ACL 2020

Methods — techniques the papers use, named apart from their topics

sequence labeling · 0.4machine reading comprehension framework · 0.4
YearPublicationVenuePosition
2021 Towards Difficulty Controllable Selection of Next-Sentence Prediction Questions
Jingrong Feng, Jack Mostow
 EDM1
2020 A Unified MRC Framework for Named Entity Recognition
abstract
The task of named entity recognition (NER) is normally divided into nested NER and flat NER depending on whether named entities are nested or not.Models are usually separately developed for the two tasks, since sequence labeling models are only able to assign a single label to a particular token, which is unsuitable for nested NER where a token may be assigned several labels.
Xiaoya Li 0001, Jingrong Feng, Yuxian Meng, Qinghong Han, Fei Wu 0001, Jiwei Li 0001
 ACL2
2020 Sentiment strength detection with a context-dependent lexicon-based convolutional neural network
Minghui Huang, Haoran Xie 0001, Yanghui Rao, Jingrong Feng, Fu Lee Wang
 Inf. Sci.4