DYNAMIC HETER-LP: HETER-LP ALGORITHM DEVELOPMENT AS A LINK PREDICTION SOLUTION FOR DYNAMIC HETEROGENEOUS GRAPH USING DTLPLP INTEGRATION
Various real-world phenomena such as recommendation systems, social networks, and protein structures can be well represented by graphs, particularly dynamic heterogeneous graphs. Link prediction is an important task in graphs as it can predict new or missing interactions within a graph. However,...
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| Format: | Theses |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/77862 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | Various real-world phenomena such as recommendation systems, social networks,
and protein structures can be well represented by graphs, particularly dynamic
heterogeneous graphs. Link prediction is an important task in graphs as it can
predict new or missing interactions within a graph. However, research on link
prediction for dynamic heterogeneous graphs is still very limited. Heter-LP and
DTLPLP are two link prediction algorithms that respectively focus on
heterogeneous and dynamic graphs. Both algorithms use label propagation, which
has been proven to be a simple and computationally efficient method. Additionally,
they include a pre-processing phase to handle the dynamic or heterogeneous nature
of the graph before label propagation is performed.
In this thesis, the Dynamic Heter-LP algorithm is proposed as a solution for link
prediction in dynamic heterogeneous graphs based on label propagation. The
contribution of this thesis lies in the development of the Heter-LP algorithm by
incorporating dynamic components from the DTLPLP algorithm, resulting in the
creation of Dynamic Heter-LP as a new link prediction method specifically
designed for dynamic heterogeneous graphs.
The evaluation in this thesis uses data from users, businesses, and reviews from the
Yelp Dataset over a duration of seven days, based on the time the reviews were
conducted. The evaluation metrics used are AUROC score and processing time.
Dynamic-Heter-LP achieved a AUROC score of 0.5 in predicting new reviews.
In conclusion, Dynamic Heter-LP fulfills its functionality as a link prediction
algorithm for dynamic heterogeneous graphs. However, it still has a drawback in
terms of relatively long processing time. For future research, extending the
duration and interval time in experiments and focusing on optimizing processing
time can be considered. |
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