publication . Article . 2015

An overview of the BIOASQ large-scale biomedical semantic indexing and question answering competition

George Tsatsaronis; Georgios Balikas; Prodromos Malakasiotis; Ioannis Partalas; Matthias Zschunke; Michael R. Alvers; Dirk Weissenborn; Anastasia Krithara; Sergios Petridis; Dimitris Polychronopoulos; ...
Open Access English
  • Published: 30 Apr 2015
  • Publisher: HAL CCSD
  • Country: France
Abstract
Background This article provides an overview of the first BioASQ challenge, a competition on large-scale biomedical semantic indexing and question answering (QA), which took place between March and September 2013. BioASQ assesses the ability of systems to semantically index very large numbers of biomedical scientific articles, and to return concise and user-understandable answers to given natural language questions by combining information from biomedical articles and ontologies. Results The 2013 BioASQ competition comprised two tasks, Task 1a and Task 1b. In Task 1a participants were asked to automatically annotate new PubMed documents with MeSH headings. Twelv...
Persistent Identifiers
Subjects
free text keywords: Passage retrieval, Information retrieval, Question answering, BIOASQ Competition, Hierarchical Text Classification, Semantic indexing, Multi-document text summarization, ClassY, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], Biochemistry, Molecular Biology, Computer Science Applications, Research Article, [ INFO.INFO-BI ] Computer Science [cs]/Bioinformatics [q-bio.QM], Information retrieval, Natural language, Automatic summarization, Computer science, Artificial intelligence, business.industry, business, Ontology (information science), Indexer, Question answering, Information needs, Natural language processing, computer.software_genre, computer, Semantics, Search engine indexing
Funded by
EC| BIOASQ
Project
BIOASQ
A challenge on large-scale biomedical semantic indexing and question answering
  • Funder: European Commission (EC)
  • Project Code: 318652
  • Funding stream: FP7 | SP1 | ICT
,
NSF| SGER: Semantic Technologies for Automatic Indexing and Tagging
Project
  • Funder: National Science Foundation (NSF)
  • Project Code: 9711407
  • Funding stream: Directorate for Computer & Information Science & Engineering | Division of Information and Intelligent Systems
Communities
Digital Humanities and Cultural Heritage
61 references, page 1 of 5

1. The BioASQ Challenge. http://www.bioasq.org/.

2. Doms A, Schroeder M. GoPubMed: exploring PubMed with the Gene Ontology. Nucleic Acids Res. 2005;33:783-6. [OpenAIRE]

3. Silla Jr CN, Freitas AA. A survey of hierarchical classification across different application domains. Data Mining Knowledge Discovery. 2011;22:31-72.

4. Athenikos SJ, Han H. Biomedical question answering: A survey. Computer Methods and Programs in Biomedicine. 2010;99:1-24.

5. Mangold C. A survey and classification of semantic search approaches. IJMSO. 2007;2(1):23-34.

6. Abacha AB, Zweigenbaum P. Medical question answering: translating medical questions into sparql queries. In: ACM International Health Informatics Symposium, IHI '12, Miami, FL, USA, January 28-30, 2012; 2012. p. 41-50. http://doi.acm.org/10.1145/2110363.2110372.

7. TREC Question Answering Track. http://trec.nist.gov/data/qamain.html.

8. Voorhees EM. The TREC question answering track. Natural Language Eng. 2001;7:361-378.

9. Hersh W, Voorhees E. TREC genomics special issue overview. Inf Retrieval. 2009;12:1-15.

10. Text Analysis Conference. http://www.nist.gov/tac/.

11. The NTCIR project. http://research.nii.ac.jp/ntcir/index-en.html.

12. Forner P, Giampiccolo D, Magnini B, Penas A, Rodrigo A, Sutcliffe RFE. Evaluating multilingual question answering systems at CLEF. In: Proceedings of the International Conference on Language Resources and Evaluation; 2010. Paris, France: European Language Resources Association.

13. The Cross Language Evaluation Forum. http://www.clef-campaign.org/.

14. Kosmopoulos A, Gaussier E, Paliouras G, Aseervaatham S. The ECIR 2010 large scale hierarchical classification workshop. SIGIR Forum. 2010;44: 23-32. [OpenAIRE]

15. The Large Scale Hierarchical Text Classification Challenge. http://lshtc.iit. demokritos.gr/.

61 references, page 1 of 5
Abstract
Background This article provides an overview of the first BioASQ challenge, a competition on large-scale biomedical semantic indexing and question answering (QA), which took place between March and September 2013. BioASQ assesses the ability of systems to semantically index very large numbers of biomedical scientific articles, and to return concise and user-understandable answers to given natural language questions by combining information from biomedical articles and ontologies. Results The 2013 BioASQ competition comprised two tasks, Task 1a and Task 1b. In Task 1a participants were asked to automatically annotate new PubMed documents with MeSH headings. Twelv...
Persistent Identifiers
Subjects
free text keywords: Passage retrieval, Information retrieval, Question answering, BIOASQ Competition, Hierarchical Text Classification, Semantic indexing, Multi-document text summarization, ClassY, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], Biochemistry, Molecular Biology, Computer Science Applications, Research Article, [ INFO.INFO-BI ] Computer Science [cs]/Bioinformatics [q-bio.QM], Information retrieval, Natural language, Automatic summarization, Computer science, Artificial intelligence, business.industry, business, Ontology (information science), Indexer, Question answering, Information needs, Natural language processing, computer.software_genre, computer, Semantics, Search engine indexing
Funded by
EC| BIOASQ
Project
BIOASQ
A challenge on large-scale biomedical semantic indexing and question answering
  • Funder: European Commission (EC)
  • Project Code: 318652
  • Funding stream: FP7 | SP1 | ICT
,
NSF| SGER: Semantic Technologies for Automatic Indexing and Tagging
Project
  • Funder: National Science Foundation (NSF)
  • Project Code: 9711407
  • Funding stream: Directorate for Computer & Information Science & Engineering | Division of Information and Intelligent Systems
Communities
Digital Humanities and Cultural Heritage
61 references, page 1 of 5

1. The BioASQ Challenge. http://www.bioasq.org/.

2. Doms A, Schroeder M. GoPubMed: exploring PubMed with the Gene Ontology. Nucleic Acids Res. 2005;33:783-6. [OpenAIRE]

3. Silla Jr CN, Freitas AA. A survey of hierarchical classification across different application domains. Data Mining Knowledge Discovery. 2011;22:31-72.

4. Athenikos SJ, Han H. Biomedical question answering: A survey. Computer Methods and Programs in Biomedicine. 2010;99:1-24.

5. Mangold C. A survey and classification of semantic search approaches. IJMSO. 2007;2(1):23-34.

6. Abacha AB, Zweigenbaum P. Medical question answering: translating medical questions into sparql queries. In: ACM International Health Informatics Symposium, IHI '12, Miami, FL, USA, January 28-30, 2012; 2012. p. 41-50. http://doi.acm.org/10.1145/2110363.2110372.

7. TREC Question Answering Track. http://trec.nist.gov/data/qamain.html.

8. Voorhees EM. The TREC question answering track. Natural Language Eng. 2001;7:361-378.

9. Hersh W, Voorhees E. TREC genomics special issue overview. Inf Retrieval. 2009;12:1-15.

10. Text Analysis Conference. http://www.nist.gov/tac/.

11. The NTCIR project. http://research.nii.ac.jp/ntcir/index-en.html.

12. Forner P, Giampiccolo D, Magnini B, Penas A, Rodrigo A, Sutcliffe RFE. Evaluating multilingual question answering systems at CLEF. In: Proceedings of the International Conference on Language Resources and Evaluation; 2010. Paris, France: European Language Resources Association.

13. The Cross Language Evaluation Forum. http://www.clef-campaign.org/.

14. Kosmopoulos A, Gaussier E, Paliouras G, Aseervaatham S. The ECIR 2010 large scale hierarchical classification workshop. SIGIR Forum. 2010;44: 23-32. [OpenAIRE]

15. The Large Scale Hierarchical Text Classification Challenge. http://lshtc.iit. demokritos.gr/.

61 references, page 1 of 5
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