An Accuracy-Assured Privacy-Preserving Recommender System for Internet Commerce

Recommender systems, tool for predicting users' potential preferences by computing history data and users' interests, show an increasing importance in various Internet applications such as online shopping. As a well-known recommendation method, neighbourhood-based collaborative filtering has attracted considerable attention recently. The risk of revealing users' private information during the process of filtering has attracted noticeable research interests. Among the current solutions, the probabilistic techniques have shown a powerful privacy preserving effect. When facing $k$ Nearest Neighbour attack, all the existing methods provide no data utility guarantee, for the introduction of global randomness. In this paper, to overcome the problem of recommendation accuracy loss, we propose a novel approach, Partitioned Probabilistic Neighbour Selection, to ensure a required prediction accuracy while maintaining high security against $k$NN attack. We define the sum of $k$ neighbours' similarity as the accuracy metric alpha, the number of user partitions, across which we select the $k$ neighbours, as the security metric beta. We generalise the $k$ Nearest Neighbour attack to beta k Nearest Neighbours attack. Differing from the existing approach that selects neighbours across the entire candidate list randomly, our method selects neighbours from each exclusive partition of size $k$ with a decreasing probability. Theoretical and experimental analysis show that to provide an accuracy-assured recommendation, our Partitioned Probabilistic Neighbour Selection method yields a better trade-off between the recommendation accuracy and system security.Comment: replacement for the previous versio

Global Progress Toward Implementing the United Nations Fish Stocks Agreement

This brief examines the progress made in implementing the Fish Stocks Agreement, based on a review of the status of certain highly migratory stocks and the effectiveness of regional fishery management organization (RFMO) measures in meeting specific mandates. It also looks at whether recommendations made in prior reviews have been implemented

Value-oriented process modeling - towards a financial perspective on business process redesign

To date, typical process modeling approaches put a strong emphasis on describing behavioral aspects of business operations. However, they often neglect value-related information. Yet, such information is of key importance to strategic decisionmaking, for instance in the context of process improvement or business engineering. In this paper we propose a valueoriented approach to business process modeling based on key concepts and metrics from operations and financial management. A simple case study suggests that our approach facilitates managerial decision-making in the context of process re-design

Solving multiple-criteria R&D project selection problems with a data-driven evidential reasoning rule

In this paper, a likelihood based evidence acquisition approach is proposed to acquire evidence from experts'assessments as recorded in historical datasets. Then a data-driven evidential reasoning rule based model is introduced to R&D project selection process by combining multiple pieces of evidence with different weights and reliabilities. As a result, the total belief degrees and the overall performance can be generated for ranking and selecting projects. Finally, a case study on the R&D project selection for the National Science Foundation of China is conducted to show the effectiveness of the proposed model. The data-driven evidential reasoning rule based model for project evaluation and selection (1) utilizes experimental data to represent experts' assessments by using belief distributions over the set of final funding outcomes, and through this historic statistics it helps experts and applicants to understand the funding probability to a given assessment grade, (2) implies the mapping relationships between the evaluation grades and the final funding outcomes by using historical data, and (3) provides a way to make fair decisions by taking experts' reliabilities into account. In the data-driven evidential reasoning rule based model, experts play different roles in accordance with their reliabilities which are determined by their previous review track records, and the selection process is made interpretable and fairer. The newly proposed model reduces the time-consuming panel review work for both managers and experts, and significantly improves the efficiency and quality of project selection process. Although the model is demonstrated for project selection in the NSFC, it can be generalized to other funding agencies or industries.Comment: 20 pages, forthcoming in International Journal of Project Management (2019

A National Dialogue on Health Information Technology and Privacy

Increasingly, government leaders recognize that solving the complex problems facing America today will require more than simply keeping citizens informed. Meeting challenges like rising health care costs, climate change and energy independence requires increased level of collaboration. Traditionally, government agencies have operated in silos -- separated not only from citizens, but from each other, as well. Nevertheless, some have begun to reach across and outside of government to access the collective brainpower of organizations, stakeholders and individuals.The National Dialogue on Health Information Technology and Privacy was one such initiative. It was conceived by leaders in government who sought to demonstrate that it is not only possible, but beneficial and economical, to engage openly and broadly on an issue that is both national in scope and deeply relevant to the everyday lives of citizens. The results of this first-of-its-kind online event are captured in this report, together with important lessons learned along the way.This report served as a call to action. On his first full day in office, President Obama put government on notice that this new, more collaborative model can no longer be confined to the efforts of early adopters. He called upon every executive department and agency to "harness new technology" and make government "transparent, participatory, and collaborative." Government is quickly transitioning to a new generation of managers and leaders, for whom online collaboration is not a new frontier but a fact of everyday life. We owe it to them -- and the citizens we serve -- to recognize and embrace the myriad tools available to fulfill the promise of good government in the 21st Century.Key FindingsThe Panel recommended that the Administration give stakeholders the opportunity to further participate in the discussion of heath IT and privacy through broader outreach and by helping the public to understand the value of a person-centered view of healthcare information technology

Aggregating Impact: A Funder's Guide to Mission Investment Intermediaries

This report provides a guide to mission investment intermediaries, organizations that collect capital from multiple sources and reinvest it in people and enterprises, whether nonprofit or for-profit, that deliver both social impact and financial returns. A growing number of foundations and other funders are beginning to use such intermediaries versus making mission investments directly. This is due to a number of advantages that intermediaries can provide, such as ease of investment, reduced risk, lower transaction costs, specialized expertise, performance reporting, and an expanded deal flow. Yet research disclosed that many funders are unaware of the wide range of mission investment intermediaries that are available and of the advantages they can offer. The authors provide an overview of mission investment intermediaries and how foundations use them, the benefits and challenges of investing in intermediaries, and an analysis of available intermediaries that address economic development, housing and the environment