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Exploratory scientific literature search using probabilistic topic models

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dc.date.accessioned 2016-08-17T10:00:39Z und
dc.date.accessioned 2017-10-24T12:24:12Z
dc.date.available 2016-08-17T10:00:39Z und
dc.date.available 2017-10-24T12:24:12Z
dc.date.issued 2016-08-17T10:00:39Z
dc.identifier.uri http://radr.hulib.helsinki.fi/handle/10138.1/5711 und
dc.identifier.uri http://hdl.handle.net/10138.1/5711
dc.title Exploratory scientific literature search using probabilistic topic models en
ethesis.discipline Computer science en
ethesis.discipline Tietojenkäsittelytiede fi
ethesis.discipline Datavetenskap sv
ethesis.discipline.URI http://data.hulib.helsinki.fi/id/1dcabbeb-f422-4eec-aaff-bb11d7501348
ethesis.department.URI http://data.hulib.helsinki.fi/id/225405e8-3362-4197-a7fd-6e7b79e52d14
ethesis.department Institutionen för datavetenskap sv
ethesis.department Department of Computer Science en
ethesis.department Tietojenkäsittelytieteen laitos fi
ethesis.faculty Matematisk-naturvetenskapliga fakulteten sv
ethesis.faculty Matemaattis-luonnontieteellinen tiedekunta fi
ethesis.faculty Faculty of Science en
ethesis.faculty.URI http://data.hulib.helsinki.fi/id/8d59209f-6614-4edd-9744-1ebdaf1d13ca
ethesis.university.URI http://data.hulib.helsinki.fi/id/50ae46d8-7ba9-4821-877c-c994c78b0d97
ethesis.university Helsingfors universitet sv
ethesis.university University of Helsinki en
ethesis.university Helsingin yliopisto fi
dct.creator Sorkhei, Amin
dct.issued 2016
dct.language.ISO639-2 eng
dct.abstract With the fast growing number of scientific papers produced every year, browsing through scientific literature can be a difficult task: formulating a precise query is not often possible if one is a novice in a given research field or different terms are often used to describe the same concept. To tackle some of these issues, we build a system based on topic models for browsing the arXiv repository. Through visualizing the relationship between keyphrases, documents and authors, the system allows the user to better explore the document search space compared to traditional systems based solely on query search. In this paper, we describe the design principles and the functionality supported by this system as well as report on a short user study. en
dct.language en
ethesis.language.URI http://data.hulib.helsinki.fi/id/languages/eng
ethesis.language English en
ethesis.language englanti fi
ethesis.language engelska sv
ethesis.thesistype pro gradu-avhandlingar sv
ethesis.thesistype pro gradu -tutkielmat fi
ethesis.thesistype master's thesis en
ethesis.thesistype.URI http://data.hulib.helsinki.fi/id/thesistypes/mastersthesis
dct.identifier.urn URN:NBN:fi-fe2017112251757
dc.type.dcmitype Text

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