Hello, can someone kindly suggest me books/paper/benchmark report which mentions regarding:
Problem: suppose we have dataset S={r1, r2, r3,r4,r5} and we want to find node similarity such as {cos(r1,r2), cos(r1, r3), cos(r1, r4), Cos(r2, r3), Cos(r2,r4), cos(r3,r4)} where, each records consists of d attributes and cos stands for cosine similarity.

Is graph modeling efficient as opposed to row/column modeling for such kind of node similarity query?

how efficient is Neo4j’s index free adjacency as opposed to join operation+indexing in relational database for such kind of node similarity computation?