0
$\begingroup$

I am interested in solving the following problem using a learning to hash algorithm:

I've got several attibuted graphs (a graph with node and edge labels - you can think about that as a description logic query) and I want to perform similarity search between a query and a document (both represented as an attributed graph).

After googling a lot, I found only a Kernelized Locality-Sensitive Hashing algorithm (KLSH) solution, the following one: Kernelized Hashcode Representations for Relation Extraction.

Locality-Sensitive Hashing demands more bits than a learning algorithm to represent data. It's not an ideal solution.

Question:

Is there a learning to hash algorithm to perform similarity search for description logic queries?

$\endgroup$

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Browse other questions tagged or ask your own question.