The proliferation of database-driven web sites has made user pay more effort for selecting the best satisfying results. Therefore, we propose a searching system named as DeepSearcher to meet user’s need, which includes offline processing (e.g. pre-processing) and online processing. The latter consists of Query Processor, Result Integrator, Cache Subsystem and Service Portal. To implement the system, key techniques such as subject-based classification, clustering-based result extraction and schema recognition, dominant attribute-based data sources ranking, query relaxation, duplicate identification and result top-k are adopted to support the searching system. The demonstration shows the feasibility and the promise of DeepSearcher.
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