A Visual Exploratory Search Engine Solution Based on Cloud Computing

This paper proposed a Visual Exploratory Search Engine solution based on cloud computing environment. We focus on improving the traditional search engine by providing a novel framework for people to obtain reliable, personalization and graphical representation search results. The novel strategy is composed of three major parts: 1) Raw information Collect: using novel meta-search engine to quick obtain vast amounts of raw information, 2) Raw information Analysis and Indexing: automatic semantic similarity calculation and semantic link construction based on cloud computing environment, 3) User Interfaces: breakthrough the traditional result use list to represent, we use graphic to display the search result. In comparison with traditional lookup search methodologies, the proposed method is characterized with three main advantages. 1) It infers rich semantic relationships between the query and other related concepts from large-scale meta-search results from Google and Baidu search engines, and representing semantic relationships via graphs, 2) The exploratory search approach enables users to naturally and effectively explore adventure and discover knowledge in a rich information world, 3) And the novel search engine is based on a personalized model, and will provide different user with different search experience. We envision the above method, technology and tools have practical merit in some specific and appropriate application scenario.