Web search engines help user‟s to identify the useful information from multiple domain websites. Traditionally, search engines have focused on verification technique using k-nearest neighbor from single domain. However, multiple domain based query verification process requires a larger area to be covered. In designing user driven queries, user query collaboration to deal user friendly format are important and often crucial. User driven queries often involves intuitive interaction with datum of multiple domains and thus obtaining user friendly format is often difficult. To extend the work for effective collaboration of user queries, Distributed Multiple Domain Information Clustering (DMDIC) method is proposed in this paper. DMDIC method provides effective collaborative querying by initially measuring the similarity between user queries. The similarity features of two types are evaluated using DMDIC method to improve the collaboration between the queried results. These two types are referred to as the Prior Query Content based similarity measure and Prior Answer Content based similarity measure on multiple domains. These two similarity features are integrated in the second part of DMDIC method, and then an algorithm called as the Distributed clustering algorithm is employed. The Distributed clustering in DMDIC method chooses the titles as the cluster head. Distributed clustering algorithm clusters the similar user queries and develop a user friendly format for effective collaborative querying on multiple domains. Experiment is performed on factors such as collaborative querying efficiency, cluster processing time and precision ratio. © Research India Publications.