We present an improved method of compactly organizing the decoding network for a semi-dynamic network decoder. In the previous work [1], the network management units called subnetworks were made compact by self-structuring themselves. We improve this subnetwork representation in two aspects by employing the shared-tail topology [2]. Firstly, we localize the decoding algorithm so that it works with a set of subnetworks rather than with the whole decoding network. Secondly, we align unshared suffixes of pronunciations into a shared tail to reduce redundancies. Experimental results on a 20k-word Korean dictation task show that our algorithm significantly reduces the memory requirement and produces additional gains in word accuracy by using aligned shared tails.