Knowledge Graph Induction enabling Recommending and Trend Analysis: A
Corporate Research Community Use Case
- URL: http://arxiv.org/abs/2207.05188v1
- Date: Mon, 11 Jul 2022 20:51:28 GMT
- Title: Knowledge Graph Induction enabling Recommending and Trend Analysis: A
Corporate Research Community Use Case
- Authors: Nandana Mihindukulasooriya, Mike Sava, Gaetano Rossiello, Md Faisal
Mahbub Chowdhury, Irene Yachbes, Aditya Gidh, Jillian Duckwitz, Kovit Nisar,
Michael Santos, Alfio Gliozzo
- Abstract summary: We present a use case of how a corporate research community, IBM Research, utilizes Semantic Web technologies to induce a unified Knowledge Graph.
We identify a set of common patterns for exploiting the induced knowledge and exposed them as APIs.
Those patterns were born out of user research which identified the most valuable use cases or user pain points to be alleviated.
- Score: 11.907821975089064
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: A research division plays an important role of driving innovation in an
organization. Drawing insights, following trends, keeping abreast of new
research, and formulating strategies are increasingly becoming more challenging
for both researchers and executives as the amount of information grows in both
velocity and volume. In this paper we present a use case of how a corporate
research community, IBM Research, utilizes Semantic Web technologies to induce
a unified Knowledge Graph from both structured and textual data obtained by
integrating various applications used by the community related to research
projects, academic papers, datasets, achievements and recognition. In order to
make the Knowledge Graph more accessible to application developers, we
identified a set of common patterns for exploiting the induced knowledge and
exposed them as APIs. Those patterns were born out of user research which
identified the most valuable use cases or user pain points to be alleviated. We
outline two distinct scenarios: recommendation and analytics for business use.
We will discuss these scenarios in detail and provide an empirical evaluation
on entity recommendation specifically. The methodology used and the lessons
learned from this work can be applied to other organizations facing similar
challenges.
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