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

Evaluation of a personalized digital library based on cognitive styles: Adaptivity vs. adaptability

Personalization can be addressed by adaptability and adaptivity, which have different advantages and disadvantages. This study investigates how digital library users react to these two techniques. More specifically, we develop a personalized digital library to suit the needs of different cognitive styles based on the findings of our previous work (Frias-Martinez, et al., in press). The personalized digital library includes two versions: adaptive version and adaptable version. The results showed that users not only performed better in the adaptive version, but also they perceived more positively to the adaptive version. In addition, cognitive styles have great effects on users’ responses to adaptability and adaptivity. These results provide guidance for designers to select suitable techniques to develop personalized digital libraries

Adaptive Information Visualization for Personalized Access to Educational Digital Libraries

Personalization is one of the emerging ways to increase the power of modern Digital Libraries. The Knowledge Sea II system presented in this paper explores social navigation support, an approach for providing personalized guidance within the open corpus of educational resources. Following the concepts of social navigation we have attempted to organize a personalized navigation support that is based on past learners’ interaction with the system. The study indicates that Knowledge Sea II became the students' primary tool for accessing the open corpus documents used in a programming course. The social navigation support implemented in this system was considered useful by students participating in the study of Knowledge Sea II. At the same time, some user comments indicated the need to provide more powerful navigational support, such as the ability to rank the usefulness of a page

Managing access to the internet in public libraries in the UK: the findings of the MAIPLE project

One of the key purposes of the public library is to provide access to information (UNESCO, 1994). In the UK, information is provided in printed formats and for the last decade via public access Internet workstations installed as part of the People’s Network initiative. Recent figures reveal that UK public libraries provide approximately 40,000 computer terminals offering users around 80,000 hours across more than 4,000 service points (CIPFA, 2012). In addition, increasing numbers of public libraries allow users to connect devices such as tablets or smart phones to the Internet via a wireless network access point (Wi-Fi). How do public library staff manage this? What about users viewing harmful or illegal content? And what are the implications for a profession committed to freedom of access to information and opposition to censorship? MAIPLE, a two-year project funded by the Arts and Humanities Research Council has been investigating this issue as little was known about how UK public libraries manage Internet content control including illegal material. MAIPLE has drawn on an extensive review of the literature, an online survey to which all UK public library services were invited to participate (39 per cent response rate) and case studies with five services (two in England, one in Scotland, one in Wales and one in Northern Ireland) to examine the ways these issues are managed and their implications for staff. This presentation will explore the prevalence of tools such as filtering software, Acceptable Use Policies, user authentication, booking software and visual monitoring by staff and consider their efficacy and desirability in the provision of public Internet access. It will consider the professional dilemmas inherent within managing content and access. Finally, it will highlight some of the more important themes emerging from the findings and their implications for practitioners and policy makers

Issues in usability studies for alerting in digital libraries

Alerting Services inform users of Digital Libraries about new or changed content of their favorite Digital Library collection, or about new documents discussing a topic they are interested in. The users define their interest in form of subscriptions; the alerting service filters new or changed documents against all user subscriptions and notifies the users about matches found. To define their subscriptions, users may, e.g., select a journal from a list, or a topic from a classification. Few services support the definition of IR type queries, or advanced combinations of queries and metadata selections

The state-of-the-art in personalized recommender systems for social networking

With the explosion of Web 2.0 application such as blogs, social and professional networks, and various other types of social media, the rich online information and various new sources of knowledge flood users and hence pose a great challenge in terms of information overload. It is critical to use intelligent agent software systems to assist users in finding the right information from an abundance of Web data. Recommender systems can help users deal with information overload problem efficiently by suggesting items (e.g., information and products) that match users’ personal interests. The recommender technology has been successfully employed in many applications such as recommending films, music, books, etc. The purpose of this report is to give an overview of existing technologies for building personalized recommender systems in social networking environment, to propose a research direction for addressing user profiling and cold start problems by exploiting user-generated content newly available in Web 2.0

The role of human factors in stereotyping behavior and perception of digital library users: A robust clustering approach

To deliver effective personalization for digital library users, it is necessary to identify which human factors are most relevant in determining the behavior and perception of these users. This paper examines three key human factors: cognitive styles, levels of expertise and gender differences, and utilizes three individual clustering techniques: k-means, hierarchical clustering and fuzzy clustering to understand user behavior and perception. Moreover, robust clustering, capable of correcting the bias of individual clustering techniques, is used to obtain a deeper understanding. The robust clustering approach produced results that highlighted the relevance of cognitive style for user behavior, i.e., cognitive style dominates and justifies each of the robust clusters created. We also found that perception was mainly determined by the level of expertise of a user. We conclude that robust clustering is an effective technique to analyze user behavior and perception

Bill & Melinda Gates Foundation - 2001 Annual Report

Contains President's message, program information, grants list, and financial statements