Association for Computing Machinery
The deep web contains over 25 millions of online data sources whose contents are typically only accessible through their form-based query interfaces. This paper proposes Deep2Q, a novel search engine that proactively transforms query forms of deep web sources into phrase queries, constructs query evaluation plans, and caches results for popular queries offline. Then at query time, keyword queries are simply matched with phrase queries to retrieve results. Deep2Q embodies a novel dual-ranking framework for query answering and novel solutions for discovering frequent attributes and queries. Preliminary experiments show the great potentials of Deep2Q.