Association Rule Sharing Model for Privacy Preservation and Collaborative Data Mining Efficiency

The disclosure of information and its misuse in Privacy Preserving Data Mining (PPDM) systems is a concern to the parties involved. In PPDM systems data is available amongst multiple parties collaborating to achieve cumulative mining accuracy. The vertically partitioned data available with the parties involved cannot provide accurate mining results when compared to the collaborative mining results. To overcome the privacy issue in data disclosure this paper describes a Key Distribution-Less Privacy Preserving Data Mining (KDLPPDM) system in which the publication of local association rules generated by the parties is published. The association rules are securely combined to form the combined rule set using the Commutative RSA algorithm. The combined rule sets established are used to classify or mine the data. The results discussed in this paper compare the accuracy of the rules generated using the C4. 5 based KDLPPDM system and the CS. 0 based KDLPPDM system using receiver operating characteristics curves (ROC).

PIB: Profiling Influential Blogger in Online Social Networks, A Knowledge Driven Data Mining Approach

Online Social Networks (OSNs) facilitate to create and spread information easily and rapidly, influencing others to participate and propagandize. This work proposes a novel method of profiling Influential Blogger (IB) based on the activities performed on one's blog documents who influences various other bloggers in Social Blog Network (SBN). After constructing a social blogging site, a SBN is analyzed with appropriate parameters to get the Influential Blog Power (IBP) of each blogger in the network and demonstrate that profiling IB is adequate and accurate. The proposed Profiling Influential Blogger (PIB) Algorithm survival rate of IB is high and stable. (C) 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Fiscal Policy and Economic Stability: Does PIGS stand for Procyclicality In Government Spending?

The Financial Crisis has hit particularly hard countries like Ireland or Spain. Procyclical fiscal policy has contributed to a boom-bust cycle that undermined fiscal positions and deepened current account deficits during the boom. We set up an RBC model of a small open economy, following Mendoza (1991), and introduce the effect of fiscal policy decisions that change over the cycle. We calibrate the model on data for Ireland, and simulate the effect of different spending policies in response to supply shocks. Procyclical fiscal policy distorts intertemporal allocation decisions. Temporary spending boosts in booms spur investment, and hence the need for external finance, and so generates very volatile cycles in investment and the current account. This economic instability is also harmful for the steady state level of output. Our model is able to replicate the relation between the degree of cyclicality of fiscal policy, and the volatility of consumption, investment and the current account observed in OECD countries.

On the Informational Role of Term Structure in the U.S. Monetary Policy Rule

This paper uses a structural approach based on the indirect inference principle to estimate a standard version of the new Keynesian monetary (NKM) model augmented with term structure using both revised and real-time data. The estimation results show that the term spread and policy inertia are both important determinants of the U.S. estimated monetary policy rule whereas the persistence of shocks plays a small but significant role when revised and real-time data of output and inflation are both considered. More importantly, the relative importance of term spread and persistent shocks in the policy rule and the shock transmission mechanism drastically change when it is taken into account that real-time data are not well behaved.

The Importance of Stock Market Returns in Estimated Monetary Policy Rules: a Structural Approach

This paper estimates a standard version of the New Keynesian Monetary (NKM) model augmented with financial variables in order to analyze the relative importance of stock market returns and term spread in the estimated U.S. monetary policy rule. The estimation procedure implemented is a classical structural method based on the indirect inference principle. The empirical results show that the Fed seems to respond to the macroeconomic outlook and to the stock market return but does not seem to respond to the term spread. Moreover, policy inertia and persistent policy shocks are also significant features of the estimated policy rule.

Term Structure and the Estimated Monetary Policy Rule in the Eurozone

Published as an article in: Spanish Economic Review, 2008, vol. 10, issue 4, pages 251-277.