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A portfolio theory approach to ease navigation task of users

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dc.date.accessioned 2015-05-25T11:30:56Z und
dc.date.accessioned 2017-10-24T12:23:58Z
dc.date.available 2015-05-25T11:30:56Z und
dc.date.available 2017-10-24T12:23:58Z
dc.date.issued 2015-05-25T11:30:56Z
dc.identifier.uri http://radr.hulib.helsinki.fi/handle/10138.1/4740 und
dc.identifier.uri http://hdl.handle.net/10138.1/4740
dc.title A portfolio theory approach to ease navigation task of users en
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 Bandyopadhyay, Payel
dct.issued 2015
dct.language.ISO639-2 eng
dct.abstract The way the users interact with Information Retrieval (IR) systems is an interesting topic of interest in the field of Human Computer Interaction (HCI) and IR. With the ever increasing information in the web, users are often lost in the vast information space. Navigating in the complex information space to find the required information, is often an abstruse task by users. One of the reasons is the difficulty in designing systems that would present the user with an optimal set of navigation options to support varying information needs. As a solution to the navigation problem, in this thesis we propose a method referred as interaction portfolio theory, based on Markowitz's 'Modern Portfolio theory', a theory of finance. It provides the users with N optimal interaction options in each iteration, by taking into account user's goal expressed via interaction during the task, but also the risk related to a potentially suboptimal choice made by the user. In each iteration, the proposed method learns the relevant interaction options from user behaviour interactively and optimizes relevance and diversity to allow the user to accomplish the task in a shorter interaction sequence. This theory can be applied to any IR system to help users to retrieve the required information efficiently. 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
ethesis.degreeprogram Networking and Service en
dct.identifier.urn URN:NBN:fi-fe2017112252179
dc.type.dcmitype Text

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