Ontological user modelling and semantic rule-based reasoning for personalisation of Help-On-Demand services in pervasive environments

Existing context-aware applications are limited in their support of user personalisation. Nevertheless, the increase in the use of context-aware technologies has sparked the growth in assistive applications resulting in a need to enable adaptation to reflect the changes in user behaviours. This paper introduces a systematic approach to service personalisation for mobile users in pervasive environments and presents a service-oriented distributed system architecture. The developed approach makes use of semantic technologies for user modelling and personalisation reasoning. In the paper we characterise user behaviours and needs in pervasive environments upon which ontological user models are created with special emphasis being placed on ontological modelling of dynamic and adaptive user profiles. We develop a rule-based personalisation mechanism that exploits semantic web rule mark-up language for rule design and a combination of semantic and rule-based reasoning for personalisation. We use two case studies focusing on providing personalised travel assistance for people using Help-on-Demand services deployed on a smart-phone to contextualise the discussions within the paper. The proposed approach is implemented in a prototype system, which includes Help-on-Demand services, content management services, user models and personalisation mechanisms in addition to application specific rules. Experiments have been designed and conducted to test and evaluate the approach with initial results demonstrating the functionality of the approach.     

Behavior monitoring for assistive environments using multiple views

This work presents an approach to behavior understanding using multiple cameras. This approach is appropriate for monitoring people in an assistive environment for the purpose of issuing alerts in cases of abnormal behavior. The output of multiple classifiers is used to model and extract abnormal behavior from both the target trajectory and the target short-term activity (i.e., walking, running, abrupt motion, etc.). Spatial information is obtained after an offline camera registration using homography information. The proposed approach is verified experimentally in an indoor environment. The experiments are performed with a single moving target; however, the method can be generalized to multiple moving targets, which may occlude each other, due to the use of multiple cameras.     

Cognitive and context-aware assistive environments using future internet technologies

Future Internet (FI) technologies are introducing new ways of networking and cognitive data delivery. In this paper, the potential of FI-based architectures for enabling the context-aware content adaptation and specialized delivery of health related information in assistive environments is investigated. The proposed system utilizes the publish/subscribe internetworking (PSI) architecture, an information-oriented architecture built for the FI using the so-called publish/subscribe paradigm. Information is brought at the center of the approach, providing several advantages: flexibility, seamless information morphing and exploitation of context, access control, and security in general. In addition to an overview of the approach and its characteristics, this work also presents the implementation of a subset of an assistive environment, using Blackadder, PSI’s prototype, and illustrates its potential with an emergency service scenario for the assistive healthcare domain.     

语义网服务中的本体综述

作为实现下一代Web的集成方案,语义网服务将语义Web技术和Web服务技术相结合,以支持Web服务的自动发现、选择、合成和执行.本体是语义网服务的理论基础.介绍了Web资源描述本体OWL和Web服务描述本体的概况,并对3种主流的Web服务语义描述框架进行对比分析,为语义网服务中本体的创建提供基础知识.研究了语义网服务中存在的各层次的本体异构问题,明确了语义网服务中本体集成的主要研究方向.     

A semantic framework for textual data enrichment

In this work we present a semantic framework suitable of being used as support tool for recommender systems. Our purpose is to use the semantic information provided by a set of integrated resources to enrich texts by conducting different NLP tasks: WSD, domain classification, semantic similarities and sentiment analysis. After obtaining the textual semantic enrichment we would be able to recommend similar content or even to rate texts according to different dimensions. First of all, we describe the main characteristics of the semantic integrated resources with an exhaustive evaluation. Next, we demonstrate the usefulness of our resource in different NLP tasks and campaigns. Moreover, we present a combination of different NLP approaches that provide enough knowledge for being used as support tool for recommender systems. Finally, we illustrate a case of study with information related to movies and TV series to demonstrate that our framework works properly.     

A semantic Web services architecture

The semantic Web services initiative architecture (SWSA) committee has created a set of architectural and protocol abstractions that serve as a foundation for semantic Web service technologies. This article summarizes the committee's findings, emphasizing its review of requirements gathered from several different environments. We also identify the scope and potential requirements for a semantic Web services architecture.     

Versioned linking of semantic enrichment of legal documents

Regulations affect every aspect of our lives. Compliance with the regulations impacts citizens and businesses similarly: they have to find their rights and obligations in the complex legal environment. The situation is more complex when languages and time versions of regulations should be considered. To propose a solution to these demands, we present a semantic enrichment approach which aims at (1) decreasing the ambiguousness of legal texts, (2) increasing the probability of finding the relevant legal materials, and (3) utilizing the application of legal reasoners. Our approach is also implemented both as a service for citizens and businesses and as a modeling environment for legal drafters. To evaluate the usefulness of the approach, a case study was carried out in a large organization and applied to corporate regulations and Hungarian laws. The results suggest this approach can support the previous aims.     

Heart sound screening in real-time assistive environments through MCMC Bayesian data mining

Emerging pervasive assistive environment applications for remote home healthcare monitoring of the elderly, disabled and also patients with various chronic diseases generate massive amounts of sensor signal data, which are transmitted from numerous homes to local health centers or hospitals. While it is critical to process this data efficiently (in a fast and accurate manner) and cost-effectively, in a large-scale application of the above technologies, it is not possible to do so manually by specialized human resources. This paper proposes a methodology for automatic real-time screening of heart sound signals (one of the most widely acquired signals from the human body for diagnostic purposes) and identification of those that are abnormal and require some action to be taken, which can be applied to many other similar types of bio-signals generated in assistive environments. It is based on a novel Markov Chain Monte Carlo Bayesian Inference approach, which estimates conditional probability distributions in structures obtained from a Tree-Augmented Naïve Bayes algorithm. It has been applied and validated in a highly ‘difficult’ heterogeneous dataset of 198 heart sound signals, which comes from both healthy medical cases and unhealthy ones having aortic stenosis, mitral regurgitation, aortic regurgitation or mitral stenosis. The proposed methodology achieved high classification performance in this difficult screening problem. It performs higher than other widely used classifiers, showing great potential for contributing to a cost-effective large-scale application of ICT-based assistive environment technologies.     

Location-based services in ubiquitous computing environments

This paper presents a framework for providing dynamically deployable services in ubiquitous computing settings. The goal of the framework is to provide people, places, and objects with computational functionalities to support and annotate them. Using RFID-based tracking systems, the framework detects the locations of physical entities, such as people or things, and deploys services bound to the entities at proper computing devices near where they are located. It enables location-based and personalized information services to be implemented as mobile agents and operated at stationary or mobile computing devices, which are at appropriate locations, even if the services do not have any location-information. This paper presents the rationale, design, implementation, and applications of our prototype infrastructure.     

Composing semantic Web services under constraints

Web service composition is an inevitable aspect of Web services technology, which solves complex problems by combining available basic services and ordering them to best suit the problem requirements. Automatic composition gives us flexibility of selecting best candidate services at composition time satisfying QoS requirements; this would require the user to define constraints for selecting and composing candidate Web services. In this work, a Web service composition approach is presented in which a rich set of constraints can be defined on the composite service. The output of the framework is the schedule of Web service composition in which how and when services are executed is defined. The basic properties of the proposed approach is converting Web service composition problem into a constraint satisfaction problem in order to find the best solution that meets all criteria defined by user and providing semantic compatibility and composability during composition.     

语义Web服务发现研究现状与发展

从不同方面对语义Web服务发现相关技术进行综述。阐述了语义Web服务的基本概念和特点,总结和分析了语义服务发现的基础——语义服务描述语言,重点从单服务匹配和服务组合匹配两个方面对语义Web服务发现的关键问题——语义Web服务匹配近年来的研究,进行了全面的总结和讨论,并指出了语义Web服务发现研究领域的挑战和未来的研究方向。     

Extensible soft semantic web services agent

Web services technology is critical for the success of business integration and other application fields such as bioinformatics. However, there are two challenges facing the practicality of Web services: (a) efficient location of the Web service registries that contain the requested Web services and (b) efficient retrieval of the requested services from these registries with high quality of service (QoS). The main reason for this problem is that current Web services technology is not semantic-oriented. Several proposals have been made to add semantics to Web services to facilitate discovery and composition of relevant Web services. Such proposals are being referred to as semantic Web services (SWS). However, most of these proposals do not address the second problem of retrieval of web services with high QoS. In this paper, we propose a framework called soft semantic Web services agent (soft SWS agent) for providing high QoS Semantic Web services using soft computing methodology. Since different application domains have different requirement for QoS, it is impractical to use classical mathematical modeling methods to evaluate the QoS of semantic Web services. We use fuzzy neural networks with Genetic Algorithms (GA) as our study case. Simulation results show that the soft computing methodology is practicable to handle fuzzy and uncertain QoS metrics effectively.     

Leveraging social semantic components in executable environments for learning

Learning can benefit from the modern Web structure through the convergence of top‐down encyclopedic institutional knowledge and bottom‐up user‐generated annotations. A promising approach to such convergence consists in leveraging the social functionalities in 3.0 executable environments through the recommendation of tags with the mediation of lexical and semantic resources. This paper addresses such issues through the design and evaluation of a tag recommendation system in a Web 3.0 Web portal, ‘150 Digit’. Designed for schools, 150 Digit encourages students and teachers to interact with a set of four exhibitions on the historical and social aspects of the Italian unification process in a virtual environment. The website displays the exhibits and their related documents promoting the users' active participation through tagging, voting and commenting on the exhibits. Tags become a way for students to create and explore new relations among the site contents, orthogonal to the institutional viewpoint. In this paper, we illustrate the recommendation strategy incorporated in 150 Digit, which relies on a semantic middleware to mediate between the input expressed by the users through tags and the top‐down institutional classification provided by the curators of the exhibitions. Following this, we describe the evaluation process conducted in a real experimental setting and discuss the evaluation results and their implications for learning environments.     

Multimedia and semantic technologies for future computing environments

Research progresses in multimedia computing and systems using semantic technologies have been recently and widely explored. This special issue on multimedia and semantic technologies for future computing environments provides high quality contributions addressing related theoretical and practical aspects of semantic multimedia. We have selected fourteen research papers whose topics are strongly related to the multimedia and semantic technology.     

Creating explorable extended reality environments with semantic annotations

Multimedia Tools and Applications - The main element of extended reality (XR) environments is behavior-rich 3D content consisting of objects that act and interact with one another as well as with...