Results of the sixth edition of the BioASQ Challenge
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Ioannis A. Kakadiaris | Georgios Paliouras | Anastasia Krithara | Anastasios Nentidis | Konstantinos Bougiatiotis | I. Kakadiaris | G. Paliouras | Anastasia Krithara | A. Nentidis | K. Bougiatiotis
[1] Luis Gravano,et al. Snowball: extracting relations from large plain-text collections , 2000, DL '00.
[2] ChengXiang Zhai,et al. DeepMeSH: deep semantic representation for improving large-scale MeSH indexing , 2016, Bioinform..
[3] Dina Demner-Fushman,et al. Using Learning-To-Rank to Enhance NLM Medical Text Indexer Results , 2016, Proceedings of the Fourth BioASQ workshop.
[4] Bowen Zhou,et al. ABCNN: Attention-Based Convolutional Neural Network for Modeling Sentence Pairs , 2015, TACL.
[5] Dina Demner-Fushman,et al. Recent Enhancements to the NLM Medical Text Indexer , 2014, CLEF.
[6] Jian Zhang,et al. SQuAD: 100,000+ Questions for Machine Comprehension of Text , 2016, EMNLP.
[7] Yanchun Zhang,et al. The Fudan Participation in the 2015 BioASQ Challenge: Large-scale Biomedical Semantic Indexing and Question Answering , 2015, CLEF.
[8] Gerard de Melo,et al. PACRR: A Position-Aware Neural IR Model for Relevance Matching , 2017, EMNLP.
[9] Jeffrey Dean,et al. Distributed Representations of Words and Phrases and their Compositionality , 2013, NIPS.
[10] Xu-Cheng Yin,et al. A Multi-strategy Query Processing Approach for Biomedical Question Answering: USTB_PRIR at BioASQ 2017 Task 5B , 2017, BioNLP.
[11] Luis M. de Campos,et al. CoLe and UTAI at BioASQ 2015: Experiments with Similarity Based Descriptor Assignment , 2015, CLEF.
[12] Georgios Paliouras,et al. Evaluation measures for hierarchical classification: a unified view and novel approaches , 2013, Data Mining and Knowledge Discovery.
[13] Yi Liu,et al. Statistical Machine Translation for Query Expansion in Answer Retrieval , 2007, ACL.
[14] Janez Demsar,et al. Statistical Comparisons of Classifiers over Multiple Data Sets , 2006, J. Mach. Learn. Res..
[15] Eric Nyberg,et al. Learning to Answer Biomedical Questions: OAQA at BioASQ 4B , 2016 .
[16] Tie-Yan Liu,et al. Adapting ranking SVM to document retrieval , 2006, SIGIR.
[17] Tao Qin,et al. LETOR: A benchmark collection for research on learning to rank for information retrieval , 2010, Information Retrieval.
[18] Tapio Salakoski,et al. Distributional Semantics Resources for Biomedical Text Processing , 2013 .
[19] Jason Weston,et al. Reading Wikipedia to Answer Open-Domain Questions , 2017, ACL.
[20] Eric Nyberg,et al. Tackling Biomedical Text Summarization: OAQA at BioASQ 5B , 2017, BioNLP.
[21] Zhiyong Lu,et al. Beyond accuracy: creating interoperable and scalable text-mining web services , 2016, Bioinform..
[22] Grigorios Tsoumakas,et al. Large-Scale Semantic Indexing of Biomedical Publications , 2013, BioASQ@CLEF.
[23] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.
[24] Pierre Zweigenbaum,et al. MEANS: A medical question-answering system combining NLP techniques and semantic Web technologies , 2015, Inf. Process. Manag..
[25] Anni Coden,et al. The ConceptMapper Approach to Named Entity Recognition , 2010, LREC.
[26] Robert Krovetz,et al. Viewing morphology as an inference process , 1993, Artif. Intell..
[27] Jeffrey Pennington,et al. GloVe: Global Vectors for Word Representation , 2014, EMNLP.
[28] Bernd Müller,et al. LIVIVO – the Vertical Search Engine for Life Sciences , 2017, Datenbank-Spektrum.
[29] Christopher D. Manning,et al. Get To The Point: Summarization with Pointer-Generator Networks , 2017, ACL.
[30] Diego Mollá. Macquarie University at BioASQ 5b – Query-based Summarisation Techniques for Selecting the Ideal Answers , 2017 .
[31] Jimeng Sun,et al. Explainable Prediction of Medical Codes from Clinical Text , 2018, NAACL.
[32] Hyoil Han,et al. BioChain: lexical chaining methods for biomedical text summarization , 2006, SAC.
[33] Tie-Yan Liu,et al. Learning to rank: from pairwise approach to listwise approach , 2007, ICML '07.
[34] Grigorios Tsoumakas,et al. Large-Scale Semantic Indexing and Question Answering in Biomedicine , 2016 .
[35] Yoshua Bengio,et al. Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation , 2014, EMNLP.
[36] Krys J. Kochut,et al. Text Summarization Techniques: A Brief Survey , 2017, International Journal of Advanced Computer Science and Applications.
[37] Alan R. Aronson,et al. An overview of MetaMap: historical perspective and recent advances , 2010, J. Am. Medical Informatics Assoc..
[38] Stephen E. Robertson,et al. Relevance weighting of search terms , 1976, J. Am. Soc. Inf. Sci..
[39] Diego Mollá-Aliod. Towards the Use of Deep Reinforcement Learning with Global Policy for Query-based Extractive Summarisation , 2017, ALTA.
[40] W. Bruce Croft,et al. A Deep Relevance Matching Model for Ad-hoc Retrieval , 2016, CIKM.