Survey of data mining approaches to user modeling for adaptive hypermedia

The ability of an adaptive hypermedia system to create tailored environments depends mainly on the amount and accuracy of information stored in each user model. Some of the difficulties that user modeling faces are the amount of data available to create user models, the adequacy of the data, the noise within that data, and the necessity of capturing the imprecise nature of human behavior. Data mining and machine learning techniques have the ability to handle large amounts of data and to process uncertainty. These characteristics make these techniques suitable for automatic generation of user models that simulate human decision making. This paper surveys different data mining techniques that can be used to efficiently and accurately capture user behavior. The paper also presents guidelines that show which techniques may be used more efficiently according to the task implemented by the applicatio

A Process to Implement an Artificial Neural Network and Association Rules Techniques to Improve Asset Performance and Energy Efficiency

In this paper, we address the problem of asset performance monitoring, with the intention of both detecting any potential reliability problem and predicting any loss of energy consumption e ciency. This is an important concern for many industries and utilities with very intensive capitalization in very long-lasting assets. To overcome this problem, in this paper we propose an approach to combine an Artificial Neural Network (ANN) with Data Mining (DM) tools, specifically with Association Rule (AR) Mining. The combination of these two techniques can now be done using software which can handle large volumes of data (big data), but the process still needs to ensure that the required amount of data will be available during the assets’ life cycle and that its quality is acceptable. The combination of these two techniques in the proposed sequence di ers from previous works found in the literature, giving researchers new options to face the problem. Practical implementation of the proposed approach may lead to novel predictive maintenance models (emerging predictive analytics) that may detect with unprecedented precision any asset’s lack of performance and help manage assets’ O&M accordingly. The approach is illustrated using specific examples where asset performance monitoring is rather complex under normal operational conditions.Ministerio de Economía y Competitividad DPI2015-70842-

How is Convergence Best Achieved in International Project Finance?

This Essay will first review and then analyze the characteristics of each of three possible routes of convergence in light of three features. The first is stability and predictability of the legal environment. It is the main benefit that private investors look for before investing in a country. The second is the scope of influence and lobbying of interest groups. This feature is extracted from an analysis of the adoption of uniform laws proposed by the National Conference of Commissioners on Uniform State Laws ( NCCUSL ) by Professors Ribstein and Kobayashi. These authors find evidence of enactment by states of NCCUSL\u27s proposals despite a cost-benefit analysis suggesting that these proposals are not efficient. This inefficiency results from the influence of interest groups and NCCUSL\u27s reliance on ill-informed generalists. The third feature is the respect for, or promotion of, public interest considerations. This analysis may reveal a tension between the economic efficiency and the social desirability of these routes, between market-driven policy and public interest concerns. This tension plays out in different ways. The more commonly addressed conflicts of interests are between public players and private investors; between (1) the interests of the host country in obtaining adequate financial and technical safeguards and assurances from the private participants that the project will be carried out safely, on time, and in the public interest and (2) the interests of private participants in limiting the type and number of guarantees that they give. The less explored tension addresses the respect for standards, such as human rights standards, that the host country itself may be reluctant to promote, but that affect private investment in terms of reputation or expense. This Essay disregards the tension between economic efficiency and social desirability, and rather focuses on the goal of reconciling private and public interest concerns. It will seek to determine whether one of these routes is better than the others, or whether a combination of the three is the best way to achieve convergence in international project finance. In conclusion, this Essay will show that all three routes to convergence are necessary to both foster and control international project finance. The twin goals of balancing private and public interests are best fulfilled at the international level, since this level can generate clear, balanced, and uniform rules by promulgating a suitable model law yet to be prepared. State initiative is then required to enact these rules and adapt them to domestic specificities. The establishment of a legal framework at the state level should be general and flexible enough not to suffocate private initiative since the latter brings innovation and evolution of norms in project finance. No one route can therefore be preferred over any other. If one is used alone, it is more likely to be inefficient

Using Data Mining in Educational Administration - A Case Study on Improving School Attendance

open access articlePupil absenteeism remains a significant problem for schools across the globe with its negative impacts on overall pupil performance being well-documented. Whilst all schools continue to emphasize good attendance, some schools still find it difficult to reach the required average attendance, which in the UK is 96\%. A novel approach is proposed to help schools improve attendance that leverages the market target model, which is built on association rule mining and probability theory, to target sessions that are most impactful to overall poor attendance. Tests conducted at Willen Primary School, in Milton Keynes, UK, show that significant improvements can be made to overall attendance, attendance in the target session, and persistent (chronic) absenteeism, through the use of this approach. The paper concludes by discussing school leadership, research implications, and highlights future work which includes the development of a software program that can be rolled-out to other schools

Making Women's Voices Count in Community Decision-Making on Land Investments

The adverse impacts of commercialization and largescale land acquisitions in the global South are often disproportionately borne by women. The loss of access to farmland and common areas hit women harder than men in many communities, and women are often excluded from compensation and benefit schemes. Women's social disadvantages, including their lack of formal land rights and generally subordinate position, make it difficult for them to voice their interests in the management and proposed allocation of community land to investors. While the development community and civil society have pushed for standards and safeguard policies that promote the meaningful involvement of rural communities generally in land acquisitions and investments, strengthening the participation of women as a distinct stakeholder group requires specific attention.This working paper examines options for strengthening women's participatory rights in the face of increasing commercial pressures on land in three countries: Mozambique, Tanzania, and the Philippines. It focuses on how regulatory reform—reforms in the rules, regulations, guidelines, and procedures that implement national land acquisition and investment laws—can promote gender equity and allow women to realize the rights afforded by national legal frameworks and international standards. The paper stems from a collaborative project between World Resources Institute and partner organizations in the three countries studied

Automated user modeling for personalized digital libraries

Digital libraries (DL) have become one of the most typical ways of accessing any kind of digitalized information. Due to this key role, users welcome any improvements on the services they receive from digital libraries. One trend used to improve digital services is through personalization. Up to now, the most common approach for personalization in digital libraries has been user-driven. Nevertheless, the design of efficient personalized services has to be done, at least in part, in an automatic way. In this context, machine learning techniques automate the process of constructing user models. This paper proposes a new approach to construct digital libraries that satisfy user’s necessity for information: Adaptive Digital Libraries, libraries that automatically learn user preferences and goals and personalize their interaction using this information