Prof. Dr. Emmanuel Müller

Notable Characteristics Search

Davide Mottin, Bastian Grasnick , Axel Kroschk , Patrick Siegler , Emmanuel Müller

Query answering routinely employs knowledge graphs to assist the user in the search process. Given a knowledge graph that represents entities and relationships among them, one aims at complementing the search  with intuitive but effective mechanisms.
In particular, we focus on the comparison of two or more entities and the detection of unexpected, surprising properties, called notable characteristics
Such characteristics provide intuitive explanations of the peculiarities of the selected entities with respect to similar entities.
We propose a solid probabilistic approach that first retrieves entity nodes similar to the query nodes provided by the user, and then exploits distributional properties to understand whether a certain attribute is interesting or not. 
Our preliminary experiments demonstrate the solidity of our approach and show that we are able to discover notable characteristics that are indeed interesting and relevant for the user. 


Davide Mottin, Bastian Grasnick , Axel Kroschk , Patrick Siegler , Emmanuel Müller. 
Notable Characteristics Search through Knowledge Graphs. 
Proc. of the conference on Exdending DataBase Technology 2018 (PDF)

Corresponding author: Davide Mottin

Technical Report (pdf)

Cite us

    title={Notable Characteristics Search through Knowledge Graphs},
    author={Mottin, Davide and Grasnick, Bastian and Kroschk, Axel and Siegler, Patrick and Müller, Emmanuel},