User-adaptive (or "personalized") systems take individual character istics of their current users into account and adapt their behavior ac cordingly. Several empirical studies demonstrate their benefits in areas like education and training, online help for complex software, dynamic information delivery, provision of computer access to people with dis abilities, and to some extent information retrieval. Recently, personal ized systems have also started to appear on the World Wide Web where they are primarily used for customer relationship management. The aim hereby is to provide value to customers by serving them as individuals and by offering them a unique personal relationship with the business. Studies show that web visitors indeed spend considerably more time at personalized than at regular portals and view considerably more web pages. Personalized sites in general also draw more visitors and turn more visitors into buyers. Personalization therefore would look like a win-win technology for both consumers and online businesses. However, it has a major down side: in order to be able to exhibit personalized behavior, user-adaptive systems have to collect considerable amounts of personal data and "lay them in stock" for possible future usage. Moreover, the collection of information about the user is often performed in a relatively inconspic uous manner (such as by monitoring users' web navigation behavior), in order not to distract users from their tasks.

This book constitutes the refereed proceedings of the 8th International Conference on User Modeling, UM 2001, held in Sonthofen, Germany in July 2001.The 19 revised full papers and 20 poster summaries presented together with summaries of 12 selected student presentations were carefully reviewed and selected from 79 submissions. The book offers topical sections on acquiring user models from multi-modal user input; learning interaction models; user models for natural language interpretation, processing, and generation; adaptive interviewing for acquiring user preferences and product customization; supporting user collaboration through adaptive agents; student modeling; and adaptive information filtering, retrieval, and browsing.

User modeling researchers look for ways of enabling interactive software systems to adapt to their users-by constructing, maintaining, and exploiting user models, which are representations of properties of individual users. User modeling has been found to enhance the effectiveness and/or usability of software systems in a wide variety of situations. Techniques for user modeling have been developed and evaluated by researchers in a number of fields, including artificial intelligence, education, psychology, linguistics, human-computer interaction, and information science. The biennial series of International Conferences on User Modeling provides a forum in which academic and industrial researchers from all of these fields can exchange their complementary insights on user modeling issues. The published proceedings of these conferences represent a major source of information about developments in this area.

Insider threat system development requires granular details about the behaviors of the individuals on its local ecosystem in order to discern anomalous patterns or behaviors. Deep Neural Networks (DNNs) have allowed researchers to discover patterns that were never before seen, but mandate large datasets. Thus, systematic data generation through techniques such as Generative Adversarial Networks (GANs) has become ubiquitous in the face of increased data needs for scientific research as was employed in part for BUBA. Through the first legal analysis of its kind, we test the legality of synthetic data for sharing given privacy requirements. An analysis of statutes through different lens helps us determine that synthetic data may be the next, best step for research advancement. We conclude that realistic yet artificially generated data offers a tangible path forward for academic and broader research endeavors, but policy must meet technological advance before general adoption can take place.

Software systems that adapt their services to characteristics of individual users have already proven to be more effective and/or usable than non-adaptive systems. User-adaptive systems rely on user modeling systems for exhibiting personalized behavior. Quite a few user modeling systems have been developed during the past fifteen years. The decisions as to what useful services/functionalities of these systems are were mostly based on intuition and/or experience gained from studying the literature of a few user-adaptive applications. Results from neighboring disciplines and commercial developments have been largely ignored. Empirical evaluations of the practical applicability of user modeling systems were hardly ever carried out. This book is different: the author takes an interdisciplinary and application-oriented approach, defines meaningful requirements on user modeling servers, gives an overview of existing systems, pinpoints their deficiencies, develops a very novel architecture for user modeling servers, implements it, and tests its utility both within an application project and in empirically founded performance experiments. His excellent synthesis of scientific and industrial concerns (which rests on research in data bases, distributed systems, human-computer interaction, user modeling, statistics, and e-commerce) and his very convincing solutions make this book a worthwhile reading both for researchers and for industrial practitioners.

The refereed proceedings of the 9th International Conference on User Modeling, UM 2003, held in Johnstown, PA, USA in June 2003. The 20 revised full papers and 28 revised poster papers presented together with 12 abstracts were carefully reviewed and selected from 106 submissions. The papers are organized in topical sections on adaptive hypermedia, adaptive Web, natural language and dialogue, plan recognition, evaluation, emerging issues of user modeling, group modeling and cooperation, applications, student modeling, learning environments - natural language and paedagogy, and mobile and ubiquitous computing.

This book constitutes the thoroughly refereed proceedings of the 22nd International Conference on User Modeling, Adaption and Personalization, held in Aalborg, Denmark, in July 2014. The 23 long and 19 short papers of the research paper track were carefully reviewed and selected from 146 submissions. The papers cover the following topics: large scale personalization, adaptation and recommendation; Personalization for individuals, groups and populations; modeling individuals, groups and communities; Web dynamics and personalization; adaptive web-based systems; context awareness; social recommendations; user experience; user awareness and control; Affective aspects; UMAP underpinning by psychology models; privacy; perceived security and trust; behavior change and persuasion.