1. ZHAW digitalcollection
  2. Life Sciences und Facility Management
  3. Publikationen
  4. Publikationen Life Sciences und Facility Management
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dc.contributor.authorKoroleva, Anna-
dc.contributor.authorAnisimova, Maria-
dc.contributor.authorGil, Manuel-
dc.date.accessioned2021-02-08T13:52:36Z-
dc.date.available2021-02-08T13:52:36Z-
dc.date.issued2020-10-15-
dc.identifier.isbn978-3-030-60469-1de_CH
dc.identifier.isbn978-3-030-60470-7de_CH
dc.identifier.issn0302-9743de_CH
dc.identifier.issn1611-3349de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/21572-
dc.description.abstractLiterature-based discovery (LBD) is a field of research aiming at discovering new knowledge by mining scientific literature. Knowledge bases are commonly used by LBD systems. SemMedDB, created with the use of SemRep information extraction system, is the most frequently used database in LBD. However, new applications of LBD are emerging that go beyond the scope of SemMedDB. In this work, we propose some new discovery patterns that lie in the domain of Natural Products and that are not covered by the existing databases and tools. Our goal thus is to create a new, extended knowledge base, addressing limitations of SemMedDB. Our proposed contribution is three-fold: 1) we add types of entities and relations that are of interest for LBD but are not covered by SemMedDB; 2) we plan to leverage full texts of scientific publications, instead of titles and abstracts only; 3) we envisage using the RDF model for our database, in accordance with Semantic Web standards. To create a new database, we plan to build a distantly supervised entity and relation extraction system, employing a neural networks/deep learning architecture. We describe the methods and tools we plan to employ.de_CH
dc.language.isoende_CH
dc.publisherSpringerde_CH
dc.relation.ispartofseriesLecture Notes in Computer Sciencede_CH
dc.rightsLicence according to publishing contractde_CH
dc.subjectLiterature-based discoveryde_CH
dc.subjectTriple storede_CH
dc.subjectSemantic webde_CH
dc.subjectInformation extractionde_CH
dc.subject.ddc006: Spezielle Computerverfahrende_CH
dc.titleTowards creating a new triple store for literature-based discoveryde_CH
dc.typeKonferenz: Paperde_CH
dcterms.typeTextde_CH
zhaw.departementLife Sciences und Facility Managementde_CH
zhaw.organisationalunitInstitut für Computational Life Sciences (ICLS)de_CH
zhaw.publisher.placeChamde_CH
dc.identifier.doi10.1007/978-3-030-60470-7_5de_CH
zhaw.conference.detailsPAKDD 2020 Workshops, DSFN, GII, BDM, LDRC and LBD, Singapore, 11-14 May 2020de_CH
zhaw.funding.euNode_CH
zhaw.originated.zhawYesde_CH
zhaw.pages.end50de_CH
zhaw.pages.start41de_CH
zhaw.parentwork.editorLu, Wei-
zhaw.parentwork.editorZhu, Kenny Q.-
zhaw.publication.statuspublishedVersionde_CH
zhaw.series.number12237de_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
zhaw.title.proceedingsTrends and Applications in Knowledge Discovery and Data Mining. PAKDD 2020de_CH
zhaw.webfeedBiomedical String Analysisde_CH
zhaw.webfeedComputational Genomicsde_CH
zhaw.webfeedDigital Health Labde_CH
zhaw.funding.zhawComputational literature-based natural product drug discoveryde_CH
zhaw.author.additionalNode_CH
zhaw.display.portraitYesde_CH
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Koroleva, A., Anisimova, M., & Gil, M. (2020). Towards creating a new triple store for literature-based discovery [Conference paper]. In W. Lu & K. Q. Zhu (Eds.), Trends and Applications in Knowledge Discovery and Data Mining. PAKDD 2020 (pp. 41–50). Springer. https://doi.org/10.1007/978-3-030-60470-7_5
Koroleva, A., Anisimova, M. and Gil, M. (2020) ‘Towards creating a new triple store for literature-based discovery’, in W. Lu and K.Q. Zhu (eds) Trends and Applications in Knowledge Discovery and Data Mining. PAKDD 2020. Cham: Springer, pp. 41–50. Available at: https://doi.org/10.1007/978-3-030-60470-7_5.
A. Koroleva, M. Anisimova, and M. Gil, “Towards creating a new triple store for literature-based discovery,” in Trends and Applications in Knowledge Discovery and Data Mining. PAKDD 2020, Oct. 2020, pp. 41–50. doi: 10.1007/978-3-030-60470-7_5.
KOROLEVA, Anna, Maria ANISIMOVA und Manuel GIL, 2020. Towards creating a new triple store for literature-based discovery. In: Wei LU und Kenny Q. ZHU (Hrsg.), Trends and Applications in Knowledge Discovery and Data Mining. PAKDD 2020. Conference paper. Cham: Springer. 15 Oktober 2020. S. 41–50. ISBN 978-3-030-60469-1
Koroleva, Anna, Maria Anisimova, and Manuel Gil. 2020. “Towards Creating a New Triple Store for Literature-Based Discovery.” Conference paper. In Trends and Applications in Knowledge Discovery and Data Mining. PAKDD 2020, edited by Wei Lu and Kenny Q. Zhu, 41–50. Cham: Springer. https://doi.org/10.1007/978-3-030-60470-7_5.
Koroleva, Anna, et al. “Towards Creating a New Triple Store for Literature-Based Discovery.” Trends and Applications in Knowledge Discovery and Data Mining. PAKDD 2020, edited by Wei Lu and Kenny Q. Zhu, Springer, 2020, pp. 41–50, https://doi.org/10.1007/978-3-030-60470-7_5.


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