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2005
SIGIR Forum
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Only four venues provided more than one nominated paper: SIGIR (16), JASIST (4), IPM (3), and SIGIR Forum (2). However, TREC work featured prominently. ...
A total of 38 international and Australian researchers and Australian graduate students took part. ...
We gratefully acknowledge the support of Frontiers of Science and Technology Mission and Workshop component of the Innovation Access Program. part of the Australian Government's Innovation Statement, Backing ...
doi:10.1145/1113343.1113344
fatcat:lx4laud5urhh7ediq3z2vi66ju
Corpus-Level Evaluation for Event QA: The IndiaPoliceEvents Corpus Covering the 2002 Gujarat Violence
2021
Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
unpublished
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, document ranking, and temporal aggregation of target events. ...
We present baseline results from zero-shot BERT-based models fine-tuned on natural language inference and passage retrieval tasks. ...
Acknowledgments For helpful comments, we're grateful to Aidan Milliff, the UMass NLP group, and anonymous ACL reviewers. ...
doi:10.18653/v1/2021.findings-acl.371
fatcat:gduhfkimxbf6fhzomq4zpjjzxy
BioCreative II Workshop Proceedings
2007
Zenodo
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Match Based Two-Layer Support Vector Machines 97 Using Semi-Supervised Techniques to Detect Gene Mentions 101 BioCreative II Gene Mention Tagging System at IBM Watson 105 Rich Feature Set, Unifi cation ...
in Biomedical Text Classifi cation 119 Penn/UMass/CHOP Biocreative II systems 125 Text Detective: Gene/protein annotation tool by Alma Bioinformatics 131 Peregrine: Lightweight gene name normalization ...
We would also like to thank the FLAD Computational Biology Collaboratorium at the Gulbenkian Institute in Oeiras, Portugal, for hosting and providing facilities used to conduct part of this research during ...
doi:10.5281/zenodo.4274543
fatcat:3sa3fvgngffjrblxzgswof42tq
Effective Distant Supervision for End-To-End Knowledge Base Population Systems
2014
unpublished
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the most pressing issues were identified and quantified at all steps. (2) The quality of semi-automatically generated training data was increased by developing noise-reduction methods, decreasing the ...
argument level. (4) A new set of effective methods for generating training data, encoding features and training relational classifiers was developed and compared with previous state-of-the-art methods ...
, 2013) ) and others which are dissimilar in the overall approach (e.g. the UMass system ). ...
fatcat:lb6nyaug6nfk3bvr37w4lddcmi