Nudging to Expand User’s Domain Knowledge while Exploring Linked Data

1. Nudging to Expand User’s Domain Knowledge while Exploring Linked Data Marwan Al-Tawil, Dhavalkumar Thakker, Vania Dimitrova School of Computing FACULTY OF ENGINEERING

2. Nudging to Expand User’s Domain Knowledge while Exploring Linked Data Problem & Focus • Aiding users’ exploration over Linked Data is important • Users explore Linked Data to gain domain knowledge. • Serendipitous learning while moving between individual nodes. • Some nodes and paths will have higher knowledge utility. How to assist ‘Nudge’ the user and maximize the learning effect of exploration? • Al-Tawil et al. Nudging to Expand User’s Domain Knowledge while Exploring Linked Data IESD2014 2

3. Nudging to Expand User’s Domain Knowledge while Exploring Linked Data Overall Approach • The stage which represents this paper work • The overall approach of my PhD • Al-Tawil et al. Nudging to Expand User’s Domain Knowledge while Exploring Linked Data IESD2014 3

4. Three nudging strategies are suggested: Density exploration strategy (D-Strategy). Familiarity exploration strategy (F-Strategy). Unfamiliarity exploration strategy (U-Strategy). Nudging to Expand User’s Domain Knowledge while Exploring Linked Data User Study • Initial dimensions and strategies What are the possible dimensions that affect knowledge utility ? • Al-Tawil et al. Nudging to Expand User’s Domain Knowledge while Exploring Linked Data IESD2014 4

5. Nudging to Expand User’s Domain Knowledge while Exploring Linked Data Study Goal • What are the likely benefits and drawbacks of each of the suggested exploration ‘nudging’ strategies, and how they can be combined and improved? • MusicPinta:876 Instruments, 71k performances(albums, tracks), 188k artists.2.4M entities and 38M triples We need a use-case dataset which is heterogeneous and large enough. • Al-Tawil et al. Nudging to Expand User’s Domain Knowledge while Exploring Linked Data IESD2014 5

6. Nudging to Expand User’s Domain Knowledge while Exploring Linked Data Study Design The main steps of the phases study • Al-Tawil et al. Nudging to Expand User’s Domain Knowledge while Exploring Linked Data IESD2014 6

7. Nudging to Expand User’s Domain Knowledge while Exploring Linked Data Study Design • Examples of the three exploration strategies • Al-Tawil et al. Nudging to Expand User’s Domain Knowledge while Exploring Linked Data IESD2014 7

8. We follow a well-known classification for measuring knowledge by Bloom. Remember and understand are directly related to browsing/exploration activities. Nudging to Expand User’s Domain Knowledge while Exploring Linked Data Study Design • We need a way to measure the knowledge utility of an exploration path • Q1-remember:What comes in your mind when you hear the musical instrument X? • Q2-categorise:What musical instrument categories does X belong to? • Q3-compare:What musical instruments are similar to X? • Al-Tawil et al. Nudging to Expand User’s Domain Knowledge while Exploring Linked Data IESD2014 8

9. Nudging to Expand User’s Domain Knowledge while Exploring Linked Data Study Results • User Knowledge Expansion(Pre and Post) knowledge tests • Median values of the knowledge increment for the three strategies • D-strategyhas higher effect than the F-strategy and the U-strategy. • The deference of D-strategy is highly significant when compared to the Familiar and Unfamiliar strategies. (Mann-Whitney, 1-tail, Na=Nb=12) • Al-Tawil et al. Nudging to Expand User’s Domain Knowledge while Exploring Linked Data IESD2014 9

10. Nudging to Expand User’s Domain Knowledge while Exploring Linked Data Study Results • Usability and exploration strategies • Al-Tawil et al. Nudging to Expand User’s Domain Knowledge while Exploring Linked Data IESD2014 11

11. Exploring familiar entities in a familiar domain Exploring familiar entities in an unfamiliar domain Exploring unfamiliar entities in an unfamiliar domain Exploring dense entities in a familiar domain Nudging to Expand User’s Domain Knowledge while Exploring Linked Data Study Results • Cases with lowest knowledge utility. These are situations that should be avoided duringthe exploration. These situations show that familiarity is important anddensity is not always good. • Al-Tawil et al. Nudging to Expand User’s Domain Knowledge while Exploring Linked Data IESD2014 10

12. When the exploration goes too familiar, direct the users to something new.Newness could be associated with unfamiliar entities, not seen during the exploration. When the exploration goes through too unfamiliar spaces which can cause frustration and confusion, the user should be helped to make a connectionbetween new things and what they are familiar with. Nudging to Expand User’s Domain Knowledge while Exploring Linked Data Post-study questionnaire • Summary of what the users wanted during the exploration • Al-Tawil et al. Nudging to Expand User’s Domain Knowledge while Exploring Linked Data IESD2014 12

13. D-Strategy used as the underpinning strategy. Provide new things when the exploration goes too familiar. Diversification to encourage connections. User profile to detect user’s domain familiarity. Nudging to Expand User’s Domain Knowledge while Exploring Linked Data Conclusion and Future Work • Conclusion • Future work • The immediate future work is to design and implement our first nudging algorithm that can measure newness to provide new things for the users when their exploration goes too familiar. • In the long run, we intend to also extend the user profiling to include also implicit methods. • Al-Tawil et al. Nudging to Expand User’s Domain Knowledge while Exploring Linked Data IESD2014 13

14. Thank you, Questions ? Marwan Al-TawilPhD student, University of Leeds, UK Contact: scmata@leeds.ac.uk Nudging to Expand User’s Domain Knowledge while Exploring Linked Data

15. Further analysis why D-strategy was better: We considered number of entities recognized during each user’s exploration. Nudging to Expand User’s Domain Knowledge while Exploring Linked Data Study Results • Median values of recognized entities along the users’ exploration paths • Strong correlation between recognition and effect of exploration on the compare cognitive process (Spearman;R=0.67;p<0.0001). • Weak correlation between the recognition and the effect of the exploration on the categorize and remember (Spearman;0<R<0.3;p>0.5 in both cases).