4:20 PM - 4:40 PM
[1E2-04] Targets Recommendation Considering After M\&A Performance by Content based Neural Collaborative Filtering
Keywords:Recommendation
In this paper, we tackled the recommendation of the M\&A candidate considering the change in business performance after M\&A.
By incorporating the multitask learning framework into the Neural Collaborative Filtering method which is one of recommendation method using Deep Learning, we aimed to propose recommendation method considering the post-conversion change.
Experimental results show the similar accuracy as the simple logistic regression method.
By using this method, it will be possible to not only recommend M\&A targets but also to show to acquirers what kind of benefits they can obtain by acquiring.
By incorporating the multitask learning framework into the Neural Collaborative Filtering method which is one of recommendation method using Deep Learning, we aimed to propose recommendation method considering the post-conversion change.
Experimental results show the similar accuracy as the simple logistic regression method.
By using this method, it will be possible to not only recommend M\&A targets but also to show to acquirers what kind of benefits they can obtain by acquiring.