Title: From Graph Snippets to Summaries : Can We Read Knowledge Graphs?

Speaker: Srikanta Bedathur, IIIT Delhi

Abstract: With the growth in size and coverage of automatically constructed knowledge graphs, they are increasingly being used to derive deeper understanding of how real-world entities are connected with each other. One such application that has gathered lot of steam is that of relationship mining -- identify long-range, multi-faceted relationships between a pair or a group of entities. Typical solutions generate a snippet of graph that ``best'' connects the queried entities in the knowledge graph.
However, the non-trivial challenge of actually interpreting these results rests with the user. Due to the lack of context (time, text and space) of the presented relationships, and the size of resulting snippets, users often struggle to make sense of these results. In order to overcome this, we are working towards automatically generating an interpretable presentation of these results in the form of text summaries. In this talk, I plan outline our recent work and further challenges in this direction.

Relevant paper: Towards Generating Text Summaries for Entity Chains. Shruti Chhabra and Srikanta Bedathur. ECIR 2014.