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1st AKBC 2019: Amherst, MA, USA
- 1st Conference on Automated Knowledge Base Construction, AKBC 2019, Amherst, MA, USA, May 20-22, 2019. 2019
Archival Papers
- John M. Winn, John Guiver, Sam Webster, Yordan Zaykov, Martin Kukla, Dany Fabian:
Alexandria: Unsupervised High-Precision Knowledge Base Construction using a Probabilistic Program. - Aishwarya Kamath, Rajarshi Das:
A Survey on Semantic Parsing. - Angrosh Mandya, Danushka Bollegala, Frans Coenen, Katie Atkinson:
Combining Long Short Term Memory and Convolutional Neural Network for Cross-Sentence n-ary Relation Extraction. - Arcchit Jain, Tal Friedman, Ondrej Kuzelka, Guy Van den Broeck, Luc De Raedt
:
Scalable Rule Learning in Probabilistic Knowledge Bases. - Dustin Wright, Yannis Katsis, Raghav Mehta, Chun-Nan Hsu:
NormCo: Deep Disease Normalization for Biomedical Knowledge Base Construction. - Ryan Musa, Xiaoyan Wang, Achille Fokoue, Nicholas Mattei, Maria Chang, Pavan Kapanipathi, Bassem Makni, Kartik Talamadupula, Michael Witbrock:
Answering Science Exam Questions Using Query Reformulation with Background Knowledge. - Antonios Minas Krasakis, Evangelos Kanoulas
Semi-supervised Ensemble Learning with Weak Supervision for Biomedical Relationship Extraction. - Kiril Gashteovski, Sebastian Wanner, Sven Hertling, Samuel Broscheit, Rainer Gemulla:
OPIEC: An Open Information Extraction Corpus. - Mohammed Alsuhaibani, Takanori Maehara, Danushka Bollegala:
Joint Learning of Hierarchical Word Embeddings from a Corpus and a Taxonomy. - Satoshi Sekine, Akio Kobayashi, Kouta Nakayama:
SHINRA: Structuring Wikipedia by Collaborative Contribution. - Abhishek Abhishek, Sanya Bathla Taneja, Garima Malik, Ashish Anand, Amit Awekar
Fine-grained Entity Recognition with Reduced False Negatives and Large Type Coverage. - Christoph Alt, Marc Hübner, Leonhard Hennig:
Improving Relation Extraction by Pre-trained Language Representations. - Sunil Mohan, Donghui Li:
MedMentions: A Large Biomedical Corpus Annotated with UMLS Concepts. - Huda Hakami, Danushka Bollegala:
Learning Relation Representations from Word Representations. - Daniel Oñoro-Rubio, Mathias Niepert, Alberto García-Durán, Roberto Gonzalez-Sanchez, Roberto Javier López-Sastre:
Answering Visual-Relational Queries in Web-Extracted Knowledge Graphs. - Michael L. Wick, Swetasudha Panda, Joseph Tassarotti, Jean-Baptiste Tristan:
Scaling Hierarchical Coreference with Homomorphic Compression. - Bhushan Kotnis, Alberto García-Durán:
Learning Numerical Attributes in Knowledge Bases. - Elliot Schumacher, Mark Dredze:
Discriminative Candidate Generation for Medical Concept Linking. - Adrian Boteanu, Adam Kiezun, Shay Artzi:
Synonym Expansion for Large Shopping Taxonomies. - Ari Kobren, Nicholas Monath, Andrew McCallum:
Integrating User Feedback under Identity Uncertainty in Knowledge Base Construction.
Non-Archival Papers
- Tal Friedman, Guy Van den Broeck:
On Constrained Open-World Probabilistic Databases. - Ginger Tsueng, Max Nanis, Jennifer T. Fouquier, Michael Mayers, Benjamin M. Good, Andrew I. Su:
Applying Citizen Science to Gene, Drug, Disease Relationship Extraction from Biomedical Abstracts. - Pouya Pezeshkpour, Yifan Tian, Sameer Singh:
Investigating Robustness and Interpretability of Link Prediction via Adversarial Modifications. - Gaetano Rossiello
Learning Relational Representations by Analogy using Hierarchical Siamese Networks.
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