NOUS: Construction and Querying of Dynamic Knowledge Graphs

TL;DR

This paper introduces NOUS, an end-to-end framework for constructing and querying dynamic, domain-specific knowledge graphs that integrate curated data and unstructured text for advanced analytics and multi-source query answering.

Contribution

It presents a novel system combining curated and extracted knowledge, supporting complex questions and multi-source answers in a dynamic knowledge graph setting.

Findings

Supports advanced trending and explanatory questions

Enables answering queries across multiple data sources

Integrates curated knowledge with extracted information

Abstract

The ability to construct domain specific knowledge graphs (KG) and perform question-answering or hypothesis generation is a transformative capability. Despite their value, automated construction of knowledge graphs remains an expensive technical challenge that is beyond the reach for most enterprises and academic institutions. We propose an end-to-end framework for developing custom knowledge graph driven analytics for arbitrary application domains. The uniqueness of our system lies A) in its combination of curated KGs along with knowledge extracted from unstructured text, B) support for advanced trending and explanatory questions on a dynamic KG, and C) the ability to answer queries where the answer is embedded across multiple data sources.