Improving Knowledge Retrieval in Digital Libraries Applying Intelligent Techniques

Nowadays an enormous quantity of heterogeneous and distributed information is stored in the digital University. Exploring online collections to find knowledge relevant to a user’s interests is a challenging work. The artificial intelligence and Semantic Web provide a common framework that allows knowledge to be shared and reused in an efficient way. In this work we propose a comprehensive approach for discovering E-learning objects in large digital collections based on analysis of recorded semantic metadata in those objects and the application of expert system technologies. We have used Case Based-Reasoning methodology to develop a prototype for supporting efficient retrieval knowledge from online repositories. We suggest a conceptual architecture for a semantic search engine. OntoUS is a collaborative effort that proposes a new form of interaction between users and digital libraries, where the latter are adapted to users and their surroundings

Human computer interaction for international development: past present and future

Recent years have seen a burgeoning interest in research into the use of information and communication technologies (ICTs) in the context of developing regions, particularly into how such ICTs might be appropriately designed to meet the unique user and infrastructural requirements that we encounter in these cross-cultural environments. This emerging field, known to some as HCI4D, is the product of a diverse set of origins. As such, it can often be difficult to navigate prior work, and/or to piece together a broad picture of what the field looks like as a whole. In this paper, we aim to contextualize HCI4D—to give it some historical background, to review its existing literature spanning a number of research traditions, to discuss some of its key issues arising from the work done so far, and to suggest some major research objectives for the future

Enterprise engineering using semantic technologies

Modern Enterprises are facing unprecedented challenges in every aspect of their businesses: from marketing research, invention of products, prototyping, production, sales to billing. Innovation is the key to enhancing enterprise performances and knowledge is the main driving force in creating innovation. The identification and effective management of valuable knowledge, however, remains an illusive topic. Knowledge management (KM) techniques, such as enterprise process modelling, have long been recognised for their value and practiced as part of normal business. There are plentiful of KM techniques. However, what is still lacking is a holistic KM approach that enables one to fully connect KM efforts with existing business knowledge and practices already in IT systems, such as organisational memories. To address this problem, we present an integrated three-dimensional KM approach that supports innovative semantics technologies. Its automated formal methods allow us to tap into modern business practices and capitalise on existing knowledge. It closes the knowledge management cycle with user feedback loops. Since we are making use of reliable existing knowledge and methods, new knowledge can be extracted with less effort comparing with another method where new information has to be created from scratch