We live in a connected world and generate a vast amount of connected data.
Social networks, financial transaction systems, biological networks, transportation systems and a telecommunication nexus are all examples.
Node classification, also known as node attribute inference, is the problem of inferring missing or incomplete attribute values of some nodes, given attribute values of other nodes in the network. The advantage over other machine learning methods is that node attribute inference gives you the ability to bring in context and neighborhood information into your predictions.
For example, in an online social network we might be interested in predicting the music preferences of a user’s friendship network .
Credits: https://lnkd.in/dEMg_N4:
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