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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.

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Showing 1 to 2 of 2 (0.129 seconds)

Spelling suggestions: "subject:"multidocument text summarized"" "subject:"multidocument text summarize""

1

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

Tsatsaronis, George 10 October 2017 (has links) (PDF)
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.
BioASQ-Wettbewerb
hierarchische Textsystematik
semantische Indizierung
Informationsbeschaffung
Passage Retrieval
Fragebeantwortung
Mehrfachdokumentation
Technsiche Universität Dresden
Publikationsfonds
BioASQ Competition
Hierarchical Text Classification
Semantic indexing
Information retrieval
Passage retrieval
Question answering
Multi-document text summarization
Technische Universität Dresden
Publishing Fund
ddc:570
rvk:WA 15000
2

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

Tsatsaronis, George 10 October 2017 (has links)
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.
info:eu-repo/classification/ddc/570
ddc:570

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