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Prediction Algorithms for User Actions

dc.contributor.authorHartmann, Melaniede_DE
dc.contributor.authorSchreiber, Danielde_DE
dc.contributor.editorBrunkhorst, Ingode_DE
dc.contributor.editorKrause, Danielde_DE
dc.contributor.editorSitou, Wassioude_DE
dc.date.accessioned2017-11-15T15:00:00Z
dc.date.available2017-11-15T15:00:00Z
dc.date.issued2007
dc.description.abstractProactive User Interfaces (PUIs) aim at facilitating the interaction with a user interface, e.g., by highlighting fields or adapting the interface. For that purpose, they need to be able to predict the next user action from the interaction history. In this paper, we give an overview of sequence prediction algorithms (SPAs) that are applied in this domain, and build upon them to develop two new algorithms that base on combining different order Markov models. We identify the special requirements that PUIs pose on these algorithms, and evaluate the performance of the SPAs in this regard. For that purpose, we use three datasets with real usage-data and synthesize further data with specific characteristics. Our relatively simple yet efficient algorithm FxL performs extremely well in the domain of SPAs which make it a prime candidate for integration in a PUI. To facilitate further research in this field, we provide a Perl library that contains all presented algorithms and tools for the evaluation.
dc.identifier.urihttp://abis.l3s.uni-hannover.de/images/proceedings/abis2007/abis2007_hartmann.pdfde_DE
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/5043
dc.language.isoende_DE
dc.relation.ispartof15th Workshop on Adaptivity and User Modeling in Interactive Systemsde_DE
dc.titlePrediction Algorithms for User Actionsde_DE
dc.typeText/Conference Paper
gi.document.qualitydigidoc

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