Towards Query Pricing on Incomplete Data

摘要: Data have significant economic or social value in many application fields including science, business, governance, etc. This naturally leads to the emergence of data markets such as GBDEx and YoueData. As a result, trade through has started receive attentions from both industry academia. During buying selling, how price is an indispensable problem. However, pricing incomplete more challenging, even though exist pervasively vast lot real-life scenarios. In this paper, we attempt explore problem for queries over data. We propose sophisticated mechanism, termed iDBPricer, which takes series essential factors into consideration, contribution/usage, completeness, query quality. present two novel functions, namely, usage, completeness-aware function (UCA short) quality, (QUCA short). Moreover, develop efficient algorithms deriving prices. Extensive experiments using real benchmark datasets demonstrate iDBPricer excellent performance terms effectiveness scalability, compared with state-of-the-art functions.