Modern populations rely heavily on the world-wide web in searching information because it is the largest human repository of knowledge. However, finding relevant information on the web is often challenging. In the current work, we review analyses and optimize the performance of exploratory and faceted search techniques. Search behavior that is characterized by a large amount of uncertainty about the goals of the search is common in exploratory search. On the other hand, faceted search technique refines search results by a faceted taxonomy in an iterative manner. In addition, facets provide an efficient way to analyze and navigate the search result space. However, we believe that facet selection has been guided by the properties of suboptimal facet and facet term. As a consequence, users may need technical support while searching information. Thus, this paper suggests a natural way of extending the current paradigm employed by traditional search systems, the exploratory search. Our main objective is to provide a framework or a platform which is extensible with plugins and able to provide instances tunable to a particular document collection of choice. In addition, this paper presents a research model based on the prototype that will be developed.