Graph Exploration: Graph Search Made Easy

Lecture / Panel
For NYU Community

Speaker: Davide Mottin, Hasso Plattner Institute and GFZ Center


The increasing interest in social networks, knowledge graphs, protein-interaction, and many other types of networks has raised the question how users can explore such large and complex graph structures easily. In this regard, graph exploration has emerged as a complementary toolbox for graph management, graph mining, or graph visualization in which the user is a first class citizen.

The talk first identifies the main research in graph exploration by providing a taxonomy of algorithms, and then shows a novel application that supports multifidelity active search in graphs.  Active search involves the user in a series of interactions by asking the evaluation of some nodes with the purpose of learning the user's tacit interests. As opposed to traditional active search which tiresomely request the user feedback, we propose a multifidelity framework. Our multifidelity framework relies on an additional source of information (low-fidelity) which approximate the user interests, substantially reducing the number of interactions with the user.


Davide Mottin is a postdoctoral researcher at Hasso Plattner Institute and GFZ center in Potsdam. Previously, he received his PhD in 2015 from the University of Trento. His research interests include graph mining, novel query paradigms, and interactive methods. He published in distinguished conferences like VLDB, SIGMOD and KDD and is actively actively engaged in teaching database, big data analytics, and graph mining for Bachelor and Master courses as well as projects involving companies and students. He is the proponent of exemplar queries paradigm for exploratory analysis.