Information extraction from multimedia web documents: an open-source platform and testbed

The LivingKnowledge project aimed to enhance the current state of the art in search, retrieval and knowledge management on the web by advancing the use of sentiment and opinion analysis within multimedia applications. To achieve this aim, a diverse set of novel and complementary analysis techniques have been integrated into a single, but extensible software platform on which such applications can be built. The platform combines state-of-the-art techniques for extracting facts, opinions and sentiment from multimedia documents, and unlike earlier platforms, it exploits both visual and textual techniques to support multimedia information retrieval. Foreseeing the usefulness of this software in the wider community, the platform has been made generally available as an open-source project. This paper describes the platform design, gives an overview of the analysis algorithms integrated into the system and describes two applications that utilise the system for multimedia information retrieval

Web-based knowledge elicitation and application to planned experiments for product development

When planning experiments to examine how product performance depends on the design, manufacture and environment of use, there are invariably too few resources to enable a complete investigation of all possible variables (factors). Here we describe a web-based system for eliciting company knowledge into an efficient two-stage group screening method. The method investigates the effect of a large number of factors by grouping them in a first stage experiment whose results identify factors to be further investigated in a second stage. Central to the success of the procedure is ensuring that the factors considered, and their grouping, are based on the best available knowledge of the product. We present a web-based softwared system that allows information and ideas to be contributed by engineers at different sites and uses these expert opinions to guide decisions on the planning of group screening experiments. The software includes elements that predict the total resource needed for the experiment. It also simulates the results of the experiment and estimates the likely percentage of important or active factors that fail to be detected. The approach is illustrated through the planning of an experiment on engine cold start optimization at Jaguar Cars

Hyperdoc: An Adaptive Narrative System for Dynamic Multimedia Presentations

Previous approaches to adaptive presentation have highlighted conflicts of interest between adapting the content, media type or quality and structure of a presentation. By using the three level model of narrative as a starting point, we can gain a greater understanding of the relationship between these. In this paper we present the prototype Hyperdoc system, which applies adaptive techniques at the separate levels of narrative in order to achieve a tailored web presentation within a certain domain

HealthAgents: distributed multi-agent brain tumor diagnosis and prognosis

We present an agent-based distributed decision support system for the diagnosis and prognosis of brain tumors developed by the HEALTHAGENTS project. HEALTHAGENTS is a European Union funded research project, which aims to enhance the classification of brain tumours using such a decision support system based on intelligent agents to securely connect a network of clinical centres. The HEALTHAGENTS system is implementing novel pattern recognition discrimination methods, in order to analyse in vivo Magnetic Resonance Spectroscopy (MRS) and ex vivo/in vitro High Resolution Magic Angle Spinning Nuclear Magnetic Resonance (HR-MAS) and DNA micro-array data. HEALTHAGENTS intends not only to apply forefront agent technology to the biomedical field, but also develop the HEALTHAGENTS network, a globally distributed information and knowledge repository for brain tumour diagnosis and prognosis

PROFESSIONAL POWERS - FREIDSON,E

A distributed decision support system involving multiple clinical centres is crucial to the diagnosis of rare diseases. Although sharing of valid diagnosed cases can facilitate later decision making, possibly from geographically different centres, the released information could reveal patient privacy if it is not properly protected. Clinical centres may have to impose their distinct regulations and rules that govern the use of their data externally. The collaboration of centres, therefore, must respect the collective policies and ideally, serve users the most appropriate and useful resources possible in the system according to the past experience. In this way, the system’s value is entrusted and even elevated through continuous collaboration. We present in this paper a link-anonymised data scheme and in addition to that, a security model that together enforce privacy data security and secure resource access for distributed clinical centres. Our illustration of the approach involves a prototype medical decision support system, HealthAgents, for brain tumour diagnosis

A distributed, service-based framework for knowledge applications with multimedia

The current trend in distributed systems is towards service-based integration. This article describes an ontology-driven framework implemented to provide knowledge management for data of different modalities, with multimedia processing, annotation, and reasoning provided by remote services. The framework was developed in, and is presented in the context of, the Medical Imaging and Advanced Knowledge Technologies (MIAKT) project that sought to support the Multidisciplinary Meetings (MDMs) that take place during breast cancer screening for diagnosing the patient. However, the architecture is entirely independent of the specific application domain and can be quickly prototyped into new domains. An Enterprise server provides resource access to a client-side presentation application which, in turn, provides knowledge visualization and markup of any supported media, as defined by a domain-dependent ontology-supported language

Open Knowledge: coordinating knowledge sharing through peer-to-peer interaction

The drive to extend the Web by taking advantage of automated symbolic reasoning (the so-called semantic Web) has been dominated by a traditional model of knowledge sharing, in which the focus is on task-independent standardisation of knowledge. It appears to be difficult, in practice, to standardise in this way because the way in which we represent knowledge is strongly influenced by the ways in which we expect to use it. We present a form of knowledge sharing that is based not on direct sharing of "true" statements about the world but, instead, is based on sharing descriptions of interactions. By making interaction specifications the currency of knowledge sharing we gain a context to interpreting knowledge that can be transmitted between peers, in a manner analogous to the use of electronic institutions in multi-agent systems. The narrower notion of semantic commitment we thus obtain requires peers only to commit to meanings of terms for the purposes and duration of the interactions in which they appear. This lightweight semantics allows networks of interaction to be formed between peers using comparatively simple means of tackling the perennial issues of query routing, service composition and ontology matching. A basic version of the system described in this paper has been built (via the OpenKnowledge project); all its components use established methods; many of these have been deployed in substantial applications; and we summarise a simple means of integration using the interaction specification language itself