Without access to high-level details of commercialized integrated circuits (IC), it might be impossible to find potential design flaws or limiting use cases. To assist in high-level recovery, many IC reverse engineering solutions have been proposed. This paper focuses on a hard problem facing reverse engineering researchers, that of netlist partitioning. To assist in this endeavor, we propose our own methods that focus on signal matching by analyzing fan-in trees. This analysis extends to representing signal’s fan-ins numerically by their structural properties. These values go through certain common dimension reducing algorithms; clustering practices are also leveraged to assist in our proposed partitioning process. Adversely researchers have almost never agreed on the metric for evaluating such netlist partitioning methods. To keep our results unbiased, we leverage the Normalize Mutual Information (NMI) to evaluate our proposed partitioning method and compare its results with other techniques that aim to solve the same problem. Lastly, we show how our proposed methods are capable of effectively partition netlists of larger scale than previously proposed schemes.