The Partial Evaluation Approach to Information Personalization

Information personalization refers to the automatic adjustment of information content, structure, and presentation tailored to an individual user. By reducing information overload and customizing information access, personalization systems have emerged as an important segment of the Internet economy. This paper presents a systematic modeling methodology - PIPE (`Personalization is Partial Evaluation') - for personalization. Personalization systems are designed and implemented in PIPE by modeling an information-seeking interaction in a programmatic representation. The representation supports the description of information-seeking activities as partial information and their subsequent realization by partial evaluation, a technique for specializing programs. We describe the modeling methodology at a conceptual level and outline representational choices. We present two application case studies that use PIPE for personalizing web sites and describe how PIPE suggests a novel evaluation criterion for information system designs. Finally, we mention several fundamental implications of adopting the PIPE model for personalization and when it is (and is not) applicable.Comment: Comprehensive overview of the PIPE model for personalizatio

Personalizing Interactions with Information Systems

Personalization constitutes the mechanisms and technologies necessary to customize information access to the end-user. It can be defined as the automatic adjustment of information content, structure, and presentation tailored to the individual. In this chapter, we study personalization from the viewpoint of personalizing interaction. The survey covers mechanisms for information-finding on the web, advanced information retrieval systems, dialog-based applications, and mobile access paradigms. Specific emphasis is placed on studying how users interact with an information system and how the system can encourage and foster interaction. This helps bring out the role of the personalization system as a facilitator which reconciles the user’s mental model with the underlying information system’s organization. Three tiers of personalization systems are presented, paying careful attention to interaction considerations. These tiers show how progressive levels of sophistication in interaction can be achieved. The chapter also surveys systems support technologies and niche application domains

Harvesting Multiple Views for Marker-less 3D Human Pose Annotations

Recent advances with Convolutional Networks (ConvNets) have shifted the bottleneck for many computer vision tasks to annotated data collection. In this paper, we present a geometry-driven approach to automatically collect annotations for human pose prediction tasks. Starting from a generic ConvNet for 2D human pose, and assuming a multi-view setup, we describe an automatic way to collect accurate 3D human pose annotations. We capitalize on constraints offered by the 3D geometry of the camera setup and the 3D structure of the human body to probabilistically combine per view 2D ConvNet predictions into a globally optimal 3D pose. This 3D pose is used as the basis for harvesting annotations. The benefit of the annotations produced automatically with our approach is demonstrated in two challenging settings: (i) fine-tuning a generic ConvNet-based 2D pose predictor to capture the discriminative aspects of a subject's appearance (i.e.,"personalization"), and (ii) training a ConvNet from scratch for single view 3D human pose prediction without leveraging 3D pose groundtruth. The proposed multi-view pose estimator achieves state-of-the-art results on standard benchmarks, demonstrating the effectiveness of our method in exploiting the available multi-view information.Comment: CVPR 2017 Camera Read

User's Privacy in Recommendation Systems Applying Online Social Network Data, A Survey and Taxonomy

Recommender systems have become an integral part of many social networks and extract knowledge from a user's personal and sensitive data both explicitly, with the user's knowledge, and implicitly. This trend has created major privacy concerns as users are mostly unaware of what data and how much data is being used and how securely it is used. In this context, several works have been done to address privacy concerns for usage in online social network data and by recommender systems. This paper surveys the main privacy concerns, measurements and privacy-preserving techniques used in large-scale online social networks and recommender systems. It is based on historical works on security, privacy-preserving, statistical modeling, and datasets to provide an overview of the technical difficulties and problems associated with privacy preserving in online social networks.Comment: 26 pages, IET book chapter on big data recommender system

Using Interactive Maps in Community Applications

Interactive maps provide unique ways to support community applications. In particular, they enable new collaborative activities. Map-based navigation supports a community environment as well as virtual tours. Interactive maps can also function as a tool in collecting historical information and discussing new spatial layouts. These examples indicate the numerous opportunities for interactive maps to support collaboration

Knowledge Management as a New Strategy of Innovative Development

Theoretical framework:  The relevance of studying the growing role of knowledge management in the context of ensuring the innovative activity of enterprises is increasing. The results demonstrate a number of important conclusions that have made it possible to expand the existing theoretical and practical aspects of the knowledge management concept.   Design/methodology/approach:  The conducted study in service companies has revealed a low culture of using this concept in the Ukrainian context. In the course of the research, it has been established similar and different features of the influence of knowledge management on innovation of service companies, direct and indirect relationship between variables, complex structure and indirect impact of production, integration, application of information on the speed, quality and number of innovations in enterprises.   Findings:  The complex structure of the relationship between knowledge and innovative activity can be a consequence of insufficient level of personnel competencies, available information and data management technologies, methods and practices of production, integration and application. Therefore, the low innovativeness of the service companies under study in the context of system orientation and technological capabilities of the companies, in particular, in the practice of knowledge management, and the low impact of knowledge and information on the innovation of services and processes on the market of Ukraine have been revealed.   Research, Practical & Social implications:  This is precisely why the strategy of personalization significantly prevails in its use in knowledge management compared to the codification strategy, which is manifested in the limited practice of using systems and technologies for the generation, accumulation, storage, use, dissemination of knowledge.   Originality/value:  In addition, the use of the personalization strategy is explained by the fact that the service companies under consideration focus more on processes, the optimization of which significantly affects interaction with customers and the efficiency of operations

Management consulting.

Including a lengthy, comprehensive introduction, this important collection brings together some of the most influential papers that have contributed to our understanding of management consultancy work. The two-volume set encompasses the breadth of conceptual and empirical perspectives and explores those key ideas that have helped to advance our knowledge of this intriguing area. The volumes are divided into a series of thematic sections, affording the reader easy access to a great resource of information. Professors Clark and Avakian have written an original introduction which provides a comprehensive overview of the literature

Science of Digital Libraries(SciDL)

Our purpose is to ensure that people and institutions better manage information through digital libraries (DLs). Thus we address a fundamental human and social need, which is particularly urgent in the modern Information (and Knowledge) Age. Our goal is to significantly advance both the theory and state-of-theart of DLs (and other advanced information systems) - thoroughly validating our approach using highly visible testbeds. Our research objective is to leverage our formal, theory-based approach to the problems of defining, understanding, modeling, building, personalizing, and evaluating DLs. We will construct models and tools based on that theory so organizations and individuals can easily create and maintain fully functional DLs, whose components can interoperate with corresponding components of related DLs. This research should be highly meritorious intellectually. We bring together a team of senior researchers with expertise in information retrieval, human-computer interaction, scenario-based design, personalization, and componentized system development and expect to make important contributions in each of those areas. Of crucial import, however, is that we will integrate our prior research and experience to achieve breakthrough advances in the field of DLs, regarding theory, methodology, systems, and evaluation. We will extend the 5S theory, which has identified five key dimensions or onstructs underlying effective DLs: Streams, Structures, Spaces, Scenarios, and Societies. We will use that theory to describe and develop metamodels, models, and systems, which can be tailored to disciplines and/or groups, as well as personalized. We will disseminate our findings as well as provide toolkits as open source software, encouraging wide use. We will validate our work using testbeds, ensuring broad impact. We will put powerful tools into the hands of digital librarians so they may easily plan and configure tailored systems, to support an extensible set of services, including publishing, discovery, searching, browsing, recommending, and access control, handling diverse types of collections, and varied genres and classes of digital objects. With these tools, end-users will for be able to design personal DLs. Testbeds are crucial to validate scientific theories and will be thoroughly integrated into SciDL research and evaluation. We will focus on two application domains, which together should allow comprehensive validation and increase the significance of SciDL's impact on scholarly communities. One is education (through CITIDEL); the other is libraries (through DLA and OCKHAM). CITIDEL deals with content from publishers (e.g, ACM Digital Library), corporate research efforts e.g., CiteSeer), volunteer initiatives (e.g., DBLP, based on the database and logic rogramming literature), CS departments (e.g., NCSTRL, mostly technical reports), educational initiatives (e.g., Computer Science Teaching Center), and universities (e.g., theses and dissertations). DLA is a unit of the Virginia Tech library that virtually publishes scholarly communication such as faculty-edited journals and rare and unique resources including image collections and finding aids from Special Collections. The OCKHAM initiative, calling for simplicity in the library world, emphasizes a three-part solution: lightweightprotocols, component-based development, and open reference models. It provides a framework to research the deployment of the SciDL approach in libraries. Thus our choice of testbeds also will nsure that our research will have additional benefit to and impact on the fields of computing and library and information science, supporting transformations in how we learn and deal with information