Jinxiu Chen

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6ranked-venue papers

5as first author

1since 2021 · last 2021

—ORCID · unresolved

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

Artificial intelligence and machine learning · 6 · 5 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 3 papers		Information extraction and text analysis · 100%
Databases, data mining, and information retrieval 2 papers		Data mining · 100%
Theoretical computer science 1 paper		Graph algorithms and graph theory · 100%

Topics — the 6 heaviest of 6, each with the papers that count most for it

Topic	Weight	Papers	Last	Evidence papers
Natural language and speech › Information extraction and text analysis relation extraction	0.2	3	2006	Unsupervised Relation Disambiguation with Order Identification Capabilities · EMNLP 2006 Unsupervised Relation Disambiguation Using Spectral Clustering · ACL 2006 Relation Extraction Using Label Propagation Based Semi-Supervised Learning · ACL 2006
Data mining clustering	0.1	2	2006	Unsupervised Relation Disambiguation with Order Identification Capabilities · EMNLP 2006 Unsupervised Relation Disambiguation Using Spectral Clustering · ACL 2006
Natural language and speech › Information extraction and text analysis › relation extraction semi-supervised relation extraction	0.1	1	2006	Relation Extraction Using Label Propagation Based Semi-Supervised Learning · ACL 2006
Data mining › clustering unsupervised learning	0.1	1	2006	Unsupervised Relation Disambiguation with Order Identification Capabilities · EMNLP 2006
Data mining › clustering spectral clustering	0.0	1	2006	Unsupervised Relation Disambiguation Using Spectral Clustering · ACL 2006
Graph algorithms and graph theory › network analysis › network diffusion label propagation	0.0	1	2006	Relation Extraction Using Label Propagation Based Semi-Supervised Learning · ACL 2006

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

spectral clustering · 0.1order identification · 0.1label propagation · 0.1graph-based semi-supervised learning · 0.1

Year	Publication	Venue	Position
2021	A cognitive vision method for the detection of plant disease images Junde Chen, Jinxiu Chen, Yaser Ahangari Nanehkaran, Yuandong Sun	Mach. Vis. Appl.	2
2006	Relation Extraction Using Label Propagation Based Semi-Supervised Learning abstract Shortage of manually labeled data is an obstacle to supervised relation extraction methods. In this paper we investigate a graph based semi-supervised learning algorithm, a label propagation (LP) algorithm, for relation extraction. It represents labeled and unlabeled examples and their distances as the nodes and the weights of edges of a graph, and tries to obtain a labeling function to satisfy two constraints: 1) it should be fixed on the labeled nodes, 2) it should be smooth on the whole graph. Experiment results on the ACE corpus showed that this LP algorithm achieves better performance than SVM when only very few labeled examples are available, and it also performs better than bootstrapping for the relation extraction task. Jinxiu Chen, Donghong Ji, Chew Lim Tan, Zhengyu Niu	ACL	1
2006	Unsupervised Relation Disambiguation Using Spectral Clustering Jinxiu Chen, Donghong Ji, Chew Lim Tan, Zhengyu Niu	ACL	1
2006	Unsupervised Relation Disambiguation with Order Identification Capabilities Jinxiu Chen, Donghong Ji, Chew Lim Tan, Zhengyu Niu	EMNLP	1
2006	Semi-supervised Relation Extraction with Label Propagation Jinxiu Chen, Donghong Ji, Chew Lim Tan, Zhengyu Niu	HLT-NAACL	1
2005	Automatic Relation Extraction with Model Order Selection and Discriminative Label Identification Jinxiu Chen, Donghong Ji, Chew Lim Tan, Zhengyu Niu	IJCNLP	1