Entity Relation Extraction from geological text using Conditional Random Fields and subsequence kernels

2012 ◽  
Author(s):  
N. V Sobhana ◽  
S.K Ghosh ◽  
Pabitra Mitra
Keyword(s):  
Random Fields ◽  
Conditional Random Fields ◽  
Relation Extraction ◽  
Entity Relation Extraction

scholarly journals Beyond Word Attention: Using Segment Attention in Neural Relation Extraction

2019 ◽  
Author(s):  
Bowen Yu ◽  
Zhenyu Zhang ◽  
Tingwen Liu ◽  
Bin Wang ◽  
Sujian Li ◽  
...  
Keyword(s):  
Random Fields ◽  
Latent Variables ◽  
Large Scale ◽  
Conditional Random Fields ◽  
Marginal Distribution ◽  
State Of The Art ◽  
Linear Chain ◽  
Relation Extraction ◽  
Word Attention ◽  
Attention Weight

Relation extraction studies the issue of predicting semantic relations between pairs of entities in sentences. Attention mechanisms are often used in this task to alleviate the inner-sentence noise by performing soft selections of words independently. Based on the observation that information pertinent to relations is usually contained within segments (continuous words in a sentence), it is possible to make use of this phenomenon for better extraction. In this paper, we aim to incorporate such segment information into neural relation extractor. Our approach views the attention mechanism as linear-chain conditional random fields over a set of latent variables whose edges encode the desired structure, and regards attention weight as the marginal distribution of each word being selected as a part of the relational expression. Experimental results show that our method can attend to continuous relational expressions without explicit annotations, and achieve the state-of-the-art performance on the large-scale TACRED dataset.

Detection Approach of DDoS Attacks Based on Conditional Random Fields

2011 ◽  
Vol 22 (8) ◽  
pp. 1897-1910 ◽  
Author(s):  
Yun LIU ◽  
Zhi-Ping CAI ◽  
Ping ZHONG ◽  
Jian-Ping YIN ◽  
Jie-Ren CHENG
Keyword(s):  
Random Fields ◽  
Conditional Random Fields ◽  
Ddos Attacks ◽  
Detection Approach

Long-range Terrain Perception Based on Conditional Random Fields

ROBOT ◽  
2010 ◽  
Vol 32 (3) ◽  
pp. 326-333
Author(s):  
Mingjun WANG ◽  
Jun ZHOU ◽  
Jun TU ◽  
Chengliang LIU
Keyword(s):  
Long Range ◽  
Random Fields ◽  
Conditional Random Fields
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