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Project: Show me the path: do people only care about paths?


Paths in graphs are natural, arising in domains as diverse as social networks (e.g., which people are in the same community?), communication networks (e.g., how does information spread via SMS messages?), and literary networks (e.g., which scientific papers are the most influential, in terms of direct and indirect citations?).  While such paths are ubiquitous and consequently are a core feature of graph analytics, very little is known on how to explain paths to non-technical users of graph systems. 

In this study we will look at methods to make paths informative and useful in the context of a user’s intent and the graph itself, and the algorithmic and empirical study of our methods.  This will involve both a bit of formal work (e.g., defining graph properties), bridging graph analytics, HCI, and cognitive psychology,  and experimental work (e.g., implementing algorithms and doing user studies to determine usefulness).  Consequently, this project is most appropriate for you if you are interested in both the algorithmic and the human aspects of data analytics.


  • Jiebing Ma, Sourav S Bhowmick, Byron Choi, and Lester Tay. 2023. Theories and Principles Matter: Towards Visually Appealing and Effective Abstraction of Property Graph Queries. Proc. ACM Manag. Data.
  • Renzo Angles, Marcelo Arenas, Pablo Barceló, Aidan Hogan, Juan Reutter, and Domagoj Vrgoč. 2017. Foundations of Modern Query Languages for Graph Databases. ACM Comput. Surv.
George Fletcher
Secondary supervisor
Sourav Bhowmick (NTU Singapore)
External location
Collaboration with NTU Singapore
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