Keyword search over relational databases has been widely studied for the exploration of structured data in a userfriendly way. However, users typically have limited domain knowledge or are unable to precisely specify their search intention. Existing methods find the minimal units that contain all the query keywords, and largely ignore the interpretation of possible users' search intentions. As a result, users are often overwhelmed with a lot of irrelevant answers. Moreover, without a visually pleasing way to present the answers, users often have difficulty understanding the answers because of their complex structures. Therefore, we design an interactive yet visually pleasing search paradigm called ExpressQ. ExpressQ extends the keyword query language to include keywords that match meta -data, e.g., names of relations and attributes. These keywords are utilized to infer users' search intention. Each possible search intention is represented as a query pattern, whose meaning is described in human natural language. Through a series of user interactions, ExpressQ can determine the search intention of the user, and translate the corresponding query patterns into SQLs to retrieve answers to the query. The ExpressQ prototype is available at http://expressq. comp.nus. edu.sg.