Logo des Repositoriums
 

Improving search results in life science by recommendations based on semantic information

dc.contributor.authorColmsee, Christian
dc.contributor.authorChen, Jinbo
dc.contributor.authorSchneider, Kerstin
dc.contributor.authorScholz, Uwe
dc.contributor.authorLange, Matthias
dc.contributor.editorRitter, Norbert
dc.contributor.editorHenrich, Andreas
dc.contributor.editorLehner, Wolfgang
dc.contributor.editorThor, Andreas
dc.contributor.editorFriedrich, Steffen
dc.contributor.editorWingerath, Wolfram
dc.date.accessioned2017-06-30T11:39:34Z
dc.date.available2017-06-30T11:39:34Z
dc.date.issued2015
dc.description.abstractThe management and handling of big data is a major challenge in the area of life science. Beside the data storage, information retrieval methods have to be adapted to huge data amounts as well. Therefore we present an approach to improve search results in life science by recommendations based on semantic information. In detail we determine relationships between documents by searching for shared database IDs as well as ontology identifiers. We have established a pipeline based on Hadoop allowing a distributed computation of large amounts of textual data. A comparison with the widely used cosine similarity has been performed. Its results are presented in this work as well.en
dc.identifier.isbn978-3-88579-636-7
dc.identifier.pissn1617-5468
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofDatenbanksysteme für Business, Technologie und Web (BTW 2015) - Workshopband
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-242
dc.titleImproving search results in life science by recommendations based on semantic informationen
dc.typeText/Conference Paper
gi.citation.endPage120
gi.citation.publisherPlaceBonn
gi.citation.startPage115
gi.conference.date2.-3. März 2015
gi.conference.locationHamburg

Dateien

Originalbündel
1 - 1 von 1
Lade...
Vorschaubild
Name:
115.pdf
Größe:
149.71 KB
Format:
Adobe Portable Document Format