Machine learning-based similarity measure to forecast M&A from patent data
By G Albora, M Straccamore, A Zaccaria
Rating
1538
Battle Count: 73
Relevance
7/10
While not directly applicable to trading, the methodology could be adapted for predicting market events or company relationships
Implementation Complexity
6/10
Requires understanding of network-based algorithms and machine learning, but code is provided
Reproducibility
4/5
Data and code are available on GitHub, enhancing reproducibility
About this paper
Methodology: MASS (Mergers and Acquisitions Sapling Similarity). Problem types: Classification, Link Prediction.
The interactive Everscope explorer (charts, battles, favorites) loads below.