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On the use of knowledge graph embeddings for business expansion

Tid: On 2022-12-21 kl 10.00 - 11.00

Plats: Just zoom

Videolänk: https://kth-se.zoom.us/j/66108429875

Språk: English

Respondent: Niklas Rydberg , DCS/Reglerteknik

Opponent: Gordon Gidófalvy

Handledare: Bo Wahlberg

Examinator: Cristian Rojas

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Title: On the use of knowledge graph embeddings for business expansion

Abstract: The area of Knowledge Graphs has grown significantly during recent time and
has found many different applications both in industrial and academic settings.
Despite this, many large Knowledge Graphs are in fact incomplete, which leads
to the problem of finding the missing facts in the graphs using Link Prediction.
There are several ways of performing Link prediction, the most common one
that has emerged recently being using Machine learning techniques to learn
low-dimensional representations of the Knowledge Graph called Knowledge
Graph embeddings.

This project attempts to explore whether or not this is a viable method
to use in order to give suggestions for companies that want to expand their
businesses. In order to test this hypothesis, a Knowledge Graph was built
using real company data from open sources. Then different Knowledge
Graph embedding models were trained on the data in order to predict missing
elements in the Knowledge Graph. The models were then compared to see
which one is most suitable for this task and data set. The geometric based
models were found to perform the best for the specific data set used in this
project. In this category there are models such as TransE, TransR and RotatE.
The results point to the method being a valid option for giving expansion
suggestions to companies using a Knowledge Graph of other companies and
their products. However, to be certain of this, further research needs to be
done where the method needs to be implemented on a larger scale using more
diverse data.

Opponent: Gordon Gidófalvy

Supervisor: Bo Wahlberg

Company Supervisor (Findwise AB): Fredric Landqvist

Examiner: Cristian Rojas