Elsevier’s approach to the bioCADDIE 2016 Dataset Retrieval Challenge

We developed a two-stream, Apache Solr-based information retrieval system in response to the bioCADDIE 2016 Dataset Retrieval Challenge. One stream was based on the principle of word embeddings, the other was rooted in ontology based indexing. Despite encountering several issues in the data, the eva...

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Detalles Bibliográficos
Autores principales: Scerri, Antony, Kuriakose, John, Deshmane, Amit Ajit, Stanger, Mark, Cotroneo, Peter, Moore, Rebekah, Naik, Raj, de Waard, Anita
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2017
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5737073/
https://www.ncbi.nlm.nih.gov/pubmed/29220454
http://dx.doi.org/10.1093/database/bax056
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author Scerri, Antony
Kuriakose, John
Deshmane, Amit Ajit
Stanger, Mark
Cotroneo, Peter
Moore, Rebekah
Naik, Raj
de Waard, Anita
author_facet Scerri, Antony
Kuriakose, John
Deshmane, Amit Ajit
Stanger, Mark
Cotroneo, Peter
Moore, Rebekah
Naik, Raj
de Waard, Anita
author_sort Scerri, Antony
collection PubMed
description We developed a two-stream, Apache Solr-based information retrieval system in response to the bioCADDIE 2016 Dataset Retrieval Challenge. One stream was based on the principle of word embeddings, the other was rooted in ontology based indexing. Despite encountering several issues in the data, the evaluation procedure and the technologies used, the system performed quite well. We provide some pointers towards future work: in particular, we suggest that more work in query expansion could benefit future biomedical search engines. Database URL: https://data.mendeley.com/datasets/zd9dxpyybg/1
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spelling pubmed-57370732018-01-08 Elsevier’s approach to the bioCADDIE 2016 Dataset Retrieval Challenge Scerri, Antony Kuriakose, John Deshmane, Amit Ajit Stanger, Mark Cotroneo, Peter Moore, Rebekah Naik, Raj de Waard, Anita Database (Oxford) Original Article We developed a two-stream, Apache Solr-based information retrieval system in response to the bioCADDIE 2016 Dataset Retrieval Challenge. One stream was based on the principle of word embeddings, the other was rooted in ontology based indexing. Despite encountering several issues in the data, the evaluation procedure and the technologies used, the system performed quite well. We provide some pointers towards future work: in particular, we suggest that more work in query expansion could benefit future biomedical search engines. Database URL: https://data.mendeley.com/datasets/zd9dxpyybg/1 Oxford University Press 2017-08-21 /pmc/articles/PMC5737073/ /pubmed/29220454 http://dx.doi.org/10.1093/database/bax056 Text en © The Author(s) 2017. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Scerri, Antony
Kuriakose, John
Deshmane, Amit Ajit
Stanger, Mark
Cotroneo, Peter
Moore, Rebekah
Naik, Raj
de Waard, Anita
Elsevier’s approach to the bioCADDIE 2016 Dataset Retrieval Challenge
title Elsevier’s approach to the bioCADDIE 2016 Dataset Retrieval Challenge
title_full Elsevier’s approach to the bioCADDIE 2016 Dataset Retrieval Challenge
title_fullStr Elsevier’s approach to the bioCADDIE 2016 Dataset Retrieval Challenge
title_full_unstemmed Elsevier’s approach to the bioCADDIE 2016 Dataset Retrieval Challenge
title_short Elsevier’s approach to the bioCADDIE 2016 Dataset Retrieval Challenge
title_sort elsevier’s approach to the biocaddie 2016 dataset retrieval challenge
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5737073/
https://www.ncbi.nlm.nih.gov/pubmed/29220454
http://dx.doi.org/10.1093/database/bax056
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