PivotE: revealing and visualizing the underlying entity structures for exploration

A Web-scale knowledge graph (KG) typically contains millions of entities and thousands of entity types. Due to the lack of a pre-defined data schema such as the ER model, entities in KGs are loosely coupled based on their relationships, which brings challenges for effective accesses of the KGs in a structured manner like SPARQL. This demonstration presents an entity-oriented exploratory search prototype system that is able to support search and explore KGs in a exploratory search manner, where local structures of KGs can be dynamically discovered and utilized for guiding users. The system applies a path-based ranking method for recommending similar entities and their relevant information as exploration pointers. The interface is designed to assist users to investigate a domain (particular type) of entities, as well as to explore the knowledge graphs in various relevant domains. The queries are dynamically formulated by tracing the users' dynamic clicking (exploration) behaviors.

In this demonstration, we will show how our system visualize the underlying entity structures, as well as explain the semantic correlations among them in a unified interface, which not only assist users to learn about the properties of entities in many aspects but also guide them to further explore the information space.