FUSION
FUnctionality Sharing In Open eNvironments
Heinz Nixdorf Chair for Distributed Information Systems
 

Automatic Facet Generation and Selection over Knowledge Graphs

Title: Automatic Facet Generation and Selection over Knowledge Graphs
Presenter(s): Leila Feddoul
Event: SAP Innovation Sessions (internal)
Date: 2019-11-06 11:00
Website: Link
Slides: 06-11-2019_SAP_InnovationSessions_Leila_Feddoul_Slides
Description:

With the continuous growth of the Linked Data Cloud, adequate methods to efficiently explore semantic data are increasingly required. Faceted Browsing is a wide-spread approach for exploratory search. Without requiring an in-depth knowledge of the domain and the underlying technologies, users can narrow down a resource set until it fits their need.

However, manual facet predefinition is often inappropriate for at least three reasons:

  • Heterogeneous and large-scale knowledge graphs offer a huge number of possible facets.
  • Knowledge graphs are often constantly changing, hence, predefinitions need to be redone or adapted.
  • Facets are generally applied to only a subset of resources (e.g., search query results). Thus, they have to match this subset and not the knowledge graph as a whole.

We present our approach for automatic facet generation and selection over knowledge graphs. We propose methods for (1) candidate facet generation and (2) facet ranking, based on metrics that both judge a facet in isolation as well as in relation to others. We integrate those methods in an overall system workflow that also explores indirect facets.

You will get:

  • How facets are generated from knowledge graphs?
  • Which metrics are used to automatically rank facets?
  • Overview of the system workflow.
  • Results of initial performance and user evaluation.