This paper focuses on domain-specific senses and presents a method for assigning category/domain label to each sense of words in a dictionary. The method first identifies each sense of a word in the dictionary to its corresponding category. We used a text classification technique to select appropriate senses for each domain. Then, senses were scored by computing the rank scores. We used Markov Random Walk (MRW) model. The method was tested on English and Japanese resources, WordNet 3.0 and EDR Japanese dictionary. For evaluation of the method, we compared English results with the Subject Field Codes (SFC) resources. We also compared each English and Japanese results to the first sense heuristics in the WSD task. These results suggest that identification of domain-specific senses (IDSS) may actually be of benefit.