Fostering serendipitous knowledge discovery using an adaptive multigraph-based faceted browser

Ali Khalili*, Pek Van Andel, Peter Van Den Besselaar, Klaas Andries De Graaf

*Corresponding author for this work

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Abstract

Serendipity, the art of making an unsought finding plays also an important role in the emerging field of data science, allowing the discovery of interesting and valuable facts not initially sought for. Previous research has extracted many serendipity-fostering patterns applicable to digital data-driven systems. Linked Open Data (LOD) on the Web which is powered by the Follow-Your-Nose effect, provides already a rich source for serendipity. The serendipity most often takes place when browsing data. Therefore, flexible and intuitive browsing user interfaces which support serendipity triggers such as enigmas, anomalies and novelties, can increase the likelihood of serendipity on LOD. In this work, we propose a set of serendipity-fostering design features supported by an adaptive multigraph-based faceted browsing interface to catalyze serendipity on Semantic Web and LOD environments.

Original languageEnglish
Title of host publicationProceedings of the Knowledge Capture Conference, K-CAP 2017
PublisherAssociation for Computing Machinery, Inc
Pages1-4
Number of pages4
ISBN (Electronic)9781450355537
DOIs
Publication statusPublished - 4 Dec 2017
Event9th International Conference on Knowledge Capture, K-CAP 2017 - Austin, United States
Duration: 4 Dec 20176 Dec 2017

Conference

Conference9th International Conference on Knowledge Capture, K-CAP 2017
CountryUnited States
CityAustin
Period4/12/176/12/17

Bibliographical note

Alternative title of the host publication: K-CAP 2017 : proceedings of the 9th International Conference on Knowledge Capture, December 4-6, 2017, Austin, TX, USA

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