Hello Lev I finally got time for reading the paper (� what is a structural representation in chemistry � you referred to in a discussion 2 or 3 months ago. You are perfectly right to notice that existing methods suffer from their stiffness at changing distance measure, but you do not suggest attacking this problem which could be a general classification problem. Instead, you attack a peculiar � if interesting sub problem � the one a block building domain, where the building rules are fairly well-known.
I have two specific critiques you might answer. 1. Your definition 23 leaves little room for noisy data. The curse of noise-brittleness is on others too, such as ILP, but many are attacking this issue. The relations defined in ILP look strangely similar to your structures. 2. The main problem, besides noise, is the one of the existence of both - structure and numerical uncertain values. I would think that Bayesian networks are more able to take them into account than your approach. The relational net you propose could a base for such a BN. Best cheers Yves
