I am not familiar with logseq. The sort of connection you want to made can often be made automatically using some embeddings. Because [[Project1/Computer Science]] and [[Project2/Computer Science]] likely have similar content, their semantic embedding are probably close, and a neighborhood search can help find them easily.
Communication is kind of the game of transmitting the information in such a way that your interlocutor internal representation of things ends up mapping to yours. Low dimensional embeddings are often very useful, but sometimes graph are not planar. Symmetry is usually useful, and a symmetric higher dimensional embedding is often better, because the symmetry constrain it more making it easier to be sure it was transmitted correctly.
When people ends up with different concept maps, in one of which some concepts are located near each other and in the other the same concepts are located far apart, interesting things usually happen when they communicate, ranging from culture enlightenment to culture war.
Some of these mapping are sometimes constrained to 3d, by things like memory palaces, (method of loci), but this is somewhat arbitrary, and staying more abstract and working in higher dimension until you "feel" everything fall into the right place intuitively is often preferable, (aka the Feynman method).
Yes I think embeddings using some sort of analysis is the correct answer.
I have a basic natural language processing system implemented in Neo4J (what I tried to use before Logseq). But to take notes I like plain text more than a database. Less dependencies.
The problem with embeddings, is I don't know how I would wire that into my workflow yet. Plain text notes have links, I would need a separate interface or mode to browse and analyze the connections.
Communication is kind of the game of transmitting the information in such a way that your interlocutor internal representation of things ends up mapping to yours. Low dimensional embeddings are often very useful, but sometimes graph are not planar. Symmetry is usually useful, and a symmetric higher dimensional embedding is often better, because the symmetry constrain it more making it easier to be sure it was transmitted correctly.
When people ends up with different concept maps, in one of which some concepts are located near each other and in the other the same concepts are located far apart, interesting things usually happen when they communicate, ranging from culture enlightenment to culture war.
Some of these mapping are sometimes constrained to 3d, by things like memory palaces, (method of loci), but this is somewhat arbitrary, and staying more abstract and working in higher dimension until you "feel" everything fall into the right place intuitively is often preferable, (aka the Feynman method).