Relation extraction with weakly supervised learning based on process-structure-property-performance reciprocity
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[1] Ramesh Nallapati,et al. Multi-instance Multi-label Learning for Relation Extraction , 2012, EMNLP.
[2] Daniel Jurafsky,et al. Distant supervision for relation extraction without labeled data , 2009, ACL.
[3] G. B. Olson,et al. Designing a New Material World , 2000, Science.
[4] Yuyong Chen,et al. A study on the microstructures and mechanical properties of Ti–B20–0.1B alloys of direct rolling in the α + β phase region , 2015 .
[5] Mihai Surdeanu,et al. The Stanford CoreNLP Natural Language Processing Toolkit , 2014, ACL.
[6] N. Zabaras,et al. Investigating variability of fatigue indicator parameters of two-phase nickel-based superalloy microstructures , 2012 .
[7] Wenya Li,et al. Microstructural evolution and mechanical properties of linear friction welded Ti2AlNb joint during solution and aging treatment , 2016 .
[8] Zhiyuan Liu,et al. Neural Relation Extraction with Selective Attention over Instances , 2016, ACL.
[9] Jun Zhao,et al. Distant Supervision for Relation Extraction via Piecewise Convolutional Neural Networks , 2015, EMNLP.
[10] R. Cochrane,et al. Microstructure evolution and mechanical properties of drop-tube processed, rapidly solidified grey cast iron , 2016 .
[11] Jeffrey Pennington,et al. GloVe: Global Vectors for Word Representation , 2014, EMNLP.
[12] Distant Supervision for Relation Extraction with Matrix Completion , 2014, ACL.
[13] L. Du,et al. Effect of thermo-mechanical cycling on the microstructure and toughness in the weld CGHAZ of a novel high strength low carbon steel , 2015 .
[14] W. Zeng,et al. Study on the microstructure and mechanical properties of Aermet 100 steel at the tempering temperature around 482 °C , 2016 .
[15] Jie Su,et al. Microstructure analysis and yield strength simulation in high Co–Ni secondary hardening steel , 2016 .
[16] A. Schino,et al. Effect of microstructure on cleavage resistance of high-strength quenched and tempered steels , 2009 .
[17] Julie Carte. Vancouver, Canada , 2003 .
[18] Guohua Wu,et al. Effects of Sc addition on the microstructure and mechanical properties of cast Al-3Li-1.5Cu-0.15Zr alloy , 2017 .
[19] William Yang Wang,et al. Deep Residual Learning for Weakly-Supervised Relation Extraction , 2017, EMNLP.
[20] Isabelle Augenstein,et al. SemEval 2017 Task 10: ScienceIE - Extracting Keyphrases and Relations from Scientific Publications , 2017, *SEMEVAL.
[21] Gregory B Olson,et al. Genomic materials design: The ferrous frontier , 2013 .
[22] Andrew McCallum,et al. Modeling Relations and Their Mentions without Labeled Text , 2010, ECML/PKDD.
[23] Wei Xiong,et al. Cybermaterials: materials by design and accelerated insertion of materials , 2016 .
[24] P. Yao,et al. Effects of solution treatment on microstructure and mechanical properties of thixoformed Mg2Sip/AM60B composite , 2015 .
[25] Pierre Villars,et al. Inorganic Materials Database for Exploring the Nature of Material , 2011 .
[26] Jun Zhao,et al. Distant Supervision for Relation Extraction with Sentence-Level Attention and Entity Descriptions , 2017, AAAI.
[27] Xia Fuzhong,et al. Effect of ingot grain refinement on the tensile properties of 2024 Al alloy sheets , 2017 .
[28] Zhifang Sui,et al. A Soft-label Method for Noise-tolerant Distantly Supervised Relation Extraction , 2017, EMNLP.
[29] Zhenhua Wang,et al. Preparation and properties of an Al2O3/Ti(C,N) micro-nano-composite ceramic tool material by microwave sintering , 2016 .
[30] Luke S. Zettlemoyer,et al. Knowledge-Based Weak Supervision for Information Extraction of Overlapping Relations , 2011, ACL.