Towards personalization in digital libraries through ontologies

In this paper we describe a browsing and searching personalization system for digital libraries based on the use of ontologies for describing the relationships between all the elements which take part in a digital library scenario of use. The main goal of this project is to help the users of a digital library to improve their experience of use by means of two complementary strategies: first, by maintaining a complete history record of his or her browsing and searching activities, which is part of a navigational user profile which includes preferences and all the aspects related to community involvement; and second, by reusing all the knowledge which has been extracted from previous usage from other users with similar profiles. This can be accomplished in terms of narrowing and focusing the search results and browsing options through the use of a recommendation system which organizes such results in the most appropriate manner, using ontologies and concepts drawn from the semantic web field. The complete integration of the experience of use of a digital library in the learning process is also pursued. Both the usage and information organization can be also exploited to extract useful knowledge from the way users interact with a digital library, knowledge that can be used to improve several design aspects of the library, ranging from internal organization aspects to human factors and user interfaces. Although this project is still on an early development stage, it is possible to identify all the desired functionalities and requirements that are necessary to fully integrate the use of a digital library in an e-learning environment

The Role of the Mangement Sciences in Research on Personalization

We present a review of research studies that deal with personalization. We synthesize current knowledge about these areas, and identify issues that we envision will be of interest to researchers working in the management sciences. We take an interdisciplinary approach that spans the areas of economics, marketing, information technology, and operations. We present an overarching framework for personalization that allows us to identify key players in the personalization process, as well as, the key stages of personalization. The framework enables us to examine the strategic role of personalization in the interactions between a firm and other key players in the firm's value system. We review extant literature in the strategic behavior of firms, and discuss opportunities for analytical and empirical research in this regard. Next, we examine how a firm can learn a customer's preferences, which is one of the key components of the personalization process. We use a utility-based approach to formalize such preference functions, and to understand how these preference functions could be learnt based on a customer's interactions with a firm. We identify well-established techniques in management sciences that can be gainfully employed in future research on personalization.CRM, Persoanlization, Marketing, e-commerce,

Stochastic Privacy

Online services such as web search and e-commerce applications typically rely on the collection of data about users, including details of their activities on the web. Such personal data is used to enhance the quality of service via personalization of content and to maximize revenues via better targeting of advertisements and deeper engagement of users on sites. To date, service providers have largely followed the approach of either requiring or requesting consent for opting-in to share their data. Users may be willing to share private information in return for better quality of service or for incentives, or in return for assurances about the nature and extend of the logging of data. We introduce \emph{stochastic privacy}, a new approach to privacy centering on a simple concept: A guarantee is provided to users about the upper-bound on the probability that their personal data will be used. Such a probability, which we refer to as \emph{privacy risk}, can be assessed by users as a preference or communicated as a policy by a service provider. Service providers can work to personalize and to optimize revenues in accordance with preferences about privacy risk. We present procedures, proofs, and an overall system for maximizing the quality of services, while respecting bounds on allowable or communicated privacy risk. We demonstrate the methodology with a case study and evaluation of the procedures applied to web search personalization. We show how we can achieve near-optimal utility of accessing information with provable guarantees on the probability of sharing data

Blending Learning: The Evolution of Online and Face-to-Face Education from 20082015

In 2008, iNACOL produced a series of papers documenting promising practices identified throughout the field of K–12 online learning. Since then, we have witnessed a tremendous acceleration of transformative policy and practice driving personalized learning in the K–12 education space. State, district, school, and classroom leaders recognize that the ultimate potential for blended and online learning lies in the opportunity to transform the education system and enable higher levels of learning through competency-based approaches.iNACOL's core work adds significant value to the field by providing a powerful practitioner voice in policy advocacy, communications, and in the creation of resources and best practices to enable transformational change in K–12 education.We worked with leaders throughout the field to update these resources for a new generation of pioneers working towards the creation of student-centered learning environments.This refreshed series, Promising Practices in Blended and Online Learning, explores some of the approaches developed by practitioners and policymakers in response to key issues in K–12 education, including:Blended Learning: The Evolution of Online and Face-to-Face Education from 2008-2015;Using Blended and Online Learning for Credit Recovery and At-Risk Students;Oversight and Management of Blended and Online Programs: Ensuring Quality and Accountability; andFunding and Legislation for Blended and Online Education.Personalized learning environments provide the very best educational opportunities and personalized pathways for all students, with highly qualified teachers delivering world-class instruction using innovative digital resources and content. Through this series of white papers, we are pleased to share the promising practices in K–12 blended, online, and competency education transforming teaching and learning today