We describe the needs for data provenance in a large-scale analytic environment to support financial systemic risk analysis. Government financial regulators need to make sense of the outputs of thousands to tens of thousands of simulation runs invoked by a large analytic staff; automatic capture of data provenance (dataset sources and processing steps) supports analysts without adding to their ...

This study proposes design concepts for a comprehensive home financial learning environment that individual investors can use as a reference in establishing web-based learning and investment platforms. This study also introduces a hybrid approach that demonstrates a data mining function of the financial learning environment. Known as Fuzzy BPN, this approach is comprised of backpropagation neur...

This paper discusses the approach to curation of the MuMe Weekend (held in Sydney, Australia, 2013) and the experience the authors gained from hosting the event. We identify open challenges arising from this applied demonstration of musically metacreative systems. Identified challenges are not technical, but rather methodological, concerning pragmatic aspects of presenting and collaboratively i...

aim: universities can overcome unstable funds as a result of changes or diminished governmental financial resources by relying on benevolent funding. however, the optimal use of this depends on recognition of their probable requirements and potential deviations that despite its evident nature is usually unnoticed. methodology: due to the relatively successful experience of imam sadiq (a.s.) uni...

We present Midas, a system that uses complex data processing to extract and aggregate facts from a large collection of structured and unstructured documents into a set of unified, clean entities and relationships. Midas focuses on data for financial companies and is based on periodic filings with the U.S. Securities and Exchange Commission (SEC) and Federal Deposit Insurance Corporation (FDIC)....

To appear in G.S. Maddala and C.R. Rao ed., Handbook of Statistics: Statistical Methods in Finance, NorthHolland. In some financial studies the dependent variable is a count, taking nonnegative integer values. Examples include the number of takeover bids received by a target firm, the number of unpaid credit installments (useful in credit scoring), the number of accidents or accident claims (us...