The contribution of data mining to information science

The information explosion is a serious challenge for current information institutions. On the other hand, data mining, which is the search for valuable information in large volumes of data, is one of the solutions to face this challenge. In the past several years, data mining has made a significant contribution to the field of information science. This paper examines the impact of data mining by reviewing existing applications, including personalized environments, electronic commerce, and search engines. For these three types of application, how data mining can enhance their functions is discussed. The reader of this paper is expected to get an overview of the state of the art research associated with these applications. Furthermore, we identify the limitations of current work and raise several directions for future research

An MPEG-7 scheme for semantic content modelling and filtering of digital video

Abstract Part 5 of the MPEG-7 standard specifies Multimedia Description Schemes (MDS); that is, the format multimedia content models should conform to in order to ensure interoperability across multiple platforms and applications. However, the standard does not specify how the content or the associated model may be filtered. This paper proposes an MPEG-7 scheme which can be deployed for digital video content modelling and filtering. The proposed scheme, COSMOS-7, produces rich and multi-faceted semantic content models and supports a content-based filtering approach that only analyses content relating directly to the preferred content requirements of the user. We present details of the scheme, front-end systems used for content modelling and filtering and experiences with a number of users

Enriching MPEG-7 user models with content metadata

MPEG-7 is an XML-based standard that provides tools for creating rich and structured multimedia content metadata. However, only an extremely limited range of preferences can be specified for user models and multimedia content metadata created by other parts of the standard cannot be fully exploited. This results in a very incomplete mapping of user models to content models. We present an approach to address the problem by representing user models by means of existing MPEG-7 content description tools

Personalized content retrieval in context using ontological knowledge

Personalized content retrieval aims at improving the retrieval process by taking into account the particular interests of individual users. However, not all user preferences are relevant in all situations. It is well known that human preferences are complex, multiple, heterogeneous, changing, even contradictory, and should be understood in context with the user goals and tasks at hand. In this paper, we propose a method to build a dynamic representation of the semantic context of ongoing retrieval tasks, which is used to activate different subsets of user interests at runtime, in a way that out-of-context preferences are discarded. Our approach is based on an ontology-driven representation of the domain of discourse, providing enriched descriptions of the semantics involved in retrieval actions and preferences, and enabling the definition of effective means to relate preferences and context

TELMA: technology enhanced learning environment for Minimally Invasive Surgery

One of the most important revolutions in the past few decades in clinical practice has been motivated by the introduction of Minimally Invasive Surgery (MIS) techniques, which have spread amongst almost all surgical specialities. MIS training is a principal component of the education of new surgical residents, with an increasing demand for knowledge and skills for medical students and surgeons. Technology enhanced learning (TEL) solutions can deal with the growing need for MIS learning. This research work aims to develop a MIS learning environment based on web technologies, named TELMA, which will respond to the growing amount of information and multimedia surgical contents available (mainly intervention’s video recording libraries), in compliance with specific learning needs of surgical students and professionals, enhancing their competence on MIS cognitive skills. Furthermore, TELMA will support knowledge capturing, sharing and reuse, and effective management of didactic contents through personalised and collaborative services