Evaluating usability and precision of visual search engine

In this paper, we evaluate a visual search engine that is designed to solve the real problem of browsing and searching for documents in a vast repository of colleges/courses located at Western Kentucky University (WKU). The architectural design of this interface combines Formal Concept Analysis (FCA) with Semantic Factoring to decompose complex, vast concepts into their primitives in order to develop knowledge representation for the HyperManyMedia plat-form. The main objective of this study is to test: (a) the efficiency of ranking the documents using precision, and (b) the usability of the visual search engine. This approach has been implemented and used by online students at WKU.