In this paper Legal statute related to dowry acts has been processed to obtain a distinct set of legal keywords which don't have a common occurrence in day to day dowry case judgments. This effort coupled with the knowledge of legal expert would give a very much broadened scope for the BoW. These keywords are very rich in concept and well connected to the domain of dowry acts. The earlier work [22] constructed BoW for dowry case notes of judgments. Current work tries to improve the BoW by widening the scope of dowry related cases. This enriches the Bag-of-Words with high probability legal terms taking precedence over low probability non-legal terms. The enriched BoW set when put through any of the similarity measures or machine learning techniques is bound to give better results when compared to earlier BoW[22].

The Indian legal domain maintains largest heterogeneous multi domain based text corpora. In order to document specific search domain specific dictionaries are widely acceptable compared to whole legal dictionary. Many domain specific dictionary extractions proposed by various authors for business and scientific domains. In this paper we proposed a two stage domain specific dictionary for legal domain. The approach helps to construct Restricted Legal Dictionary which is domain specific in nature. The dictionary constructed supports text mining mechanisms over specific crime (dowry) based legal documents and improves the BoW construction with higher domain specific terminology. The Restricted Legal Dictionary constructed in this paper improves the efficiency of similarity measures during document comparison techniques .