Facilitating discovery on the private web using dataset digests

Whereas strategies for discovering content on the surface web are commonplace, similar strategies for the private web are nonexistent. In this paper we first establish a formal framework for advertising the existence of private web resources that subsumes many existing summarization strategies based on succinct statistical summaries (which we call digests). We then investigate the tradeoff between the data owners' desires to minimize disclosure and the searchers' desires to minimize query error, demonstrating that our techniques are superior to k-anonymity. Finally, we show that our techniques for summarization do, in fact, make it possible to discover private web data resources.