Folksonomy-based personalized search and ranking in social media services

In recent years, social Web users have been overwhelmed by the huge numbers of social media available. Consequentially, users have trouble finding social media suited to their needs. To help such users retrieve useful social media content, we propose a new model of tag-based personalized searches to enhance not only retrieval accuracy but also retrieval coverage. By leveraging social tagging as a preference indicator, we build two models: (i) a latent tag preference model that reflects how a certain user has assigned tags similar to a given tag and (ii) a latent tag annotation model that captures how users have tagged a certain tag to resources similar to a given resource. We then seamlessly map the tags onto items, depending on an individual user's query, to find the most desirable content relevant to the user's needs. Experimental results demonstrate that the proposed method significantly outperforms the state-of-the art algorithms and show our method's feasibility for personalized searches in social media services.     

A framework for human-centered provisioning of ambient media services

The provisioning of ambient media in the user’s environment requires that a system handles the different aspects related to the media selection process. For example, ambient media is delivered to the user depending on their context and hence, the system needs to dynamically determine the context and provide media that are relevant therein. To set the premise of ambient media, a system may also need to customize the physical environment, for example, by dimming the lighting level or by lowering the volume. Besides, users’ need for media services changes over time and space that requires mechanisms to continually update their preferences based on their mobility in the environment. In this paper, we propose an ambient media service provisioning framework that incorporates the above requirements while keeping the user at the center of the media selection loop. To demonstrate the usefulness of this framework, we show experimental results by considering real-life scenario in a smart home environment.

Context-driven personalized service discovery in pervasive environments

Pervasive environments are characterized by a large number of embedded devices offering their services to the user. Which of the available services are of most interest to the user considerably depends on the user’s current context. User context is often rich and very dynamic; making an explicit, user-driven discovery of services impractical. Users in such environments would instead like to be continuously informed about services relevant to them. Implicit discovery requests triggered by changes in the context are therefore prevalent. This paper proposes a proactive service discovery approach for pervasive environments addressing these implicit requests. Services and user preferences are described by a formal context model called Hyperspace Analogue to Context, which effectively captures the dynamics of context and the relationship between services and context. Based on the model, we propose a set of algorithms that can continuously present the most relevant services to the user in response to changes of context, services or user preferences. Numeric coding methods are applied to improve the algorithms’ performance. The algorithms are grounded in a context-driven service discovery system that automatically reacts to changes in the environment. New context sources and services can be dynamically integrated into the system. A client for smart phones continuously informs users about the discovery results. Experiments show, that the system can efficiently provide the user with continuous, up-to-date information about the most useful services in real time.     

On coordinating personalized composite web services

This paper presents a research project on the coordination of personalized composite web services. By coordination, it is meant the mechanisms that specify the orchestration of the component web services of a composite web service. The orchestration is about the execution chronology of the component web services, the data that the component web services exchange, the states that the component web services take, and the actions that the component web services perform. By personalization, it is meant the integration of user preferences into the specification that orchestrates the component web services. These preferences concern when the component web services are to be executed. In this research project, the operations of coordination and personalization are entrusted to software agents, which, for instance, monitor the context surrounding users and trigger as a result the appropriate component web services. In addition, software agents engage in conversations with their peers when it comes to tracking the personalized component web services.     

Deploying personalized mobile services in an agent-based environment

The mobile Internet allows users to obtain digitized contents and services from wired and wireless networks virtually anywhere at any time via different handheld mobile devices. However, due to the distinct features of mobile users, mobile devices and wireless networks, deploying mobile services is not as straightforward as generally expected. To ensure the success of mobile services, this paper presents a multi-agent framework that considers different contexts to support personalized services on wireless networks. In the proposed approach, client users, content providers, and service providers are all considered as software agents. They interoperate on the same platform to request and deliver mobile services. The most important issues related to agent operations and context awareness in an agent world are also discussed and analyzed. To verify our framework, different application services are developed accordingly on a publicly available middleware platform. Experiments are conducted for both services to evaluate their corresponding performance. The preliminary results show that our multi-agent approach to personalization is promising and efficient in the deployment of mobile services.     

基于上下文的个性化Web services组合研究

Webservices组合是一个新的研究领域,它的个性化组合是研究的重点。在个性化Webservices组合规范下,提出了一种基于上下文的组合方法,使得组合流程更加有效。该方法考虑了用户的上下文、需求、偏好以及Webservices上下文,并把它们集成在组合中。而且为了保证规范的重用,在组合中基于上下文和BPEL扩展了一种规范语言C-BPEL。     

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.     

Semantic ambient media: From ambient advertising to ambient-assisted living

The term ambient media was in its beginning used only for ambient advertising. Nowadays it denotes the media environment and the communication of information in ubiquitous and pervasive environments. With the addition of intelligence, the new field of semantic ambient media was established. In recent years, the field of semantic ambient media has spread its span from only a few sub-areas, such as ambient advertising, to new ones, such as ambient-assisted living (AAL) and health-monitoring media, significantly supported by intelligence. The study presented in this paper provides an advanced introduction to the field of semantic ambient media including the solutions for threat issues and illustration of success stories of the field. It conducts a survey of the related work and presents a thorough discussion of it. The related work is grouped according to the coverage of the principles of semantic ambient media. Based on the state-of-the-art research, the future possibilities of the field are demonstrated, especially for the ambient-assisted living, audio-visual rendering of media objects, user design principles and the society impact of the field. The paper provides ideas for impacting ambient media and directions and questions for further research. It also discusses the potential of the combination of several research studies.     

Learning patterns in ambient intelligence environments: a survey

It is essential for environments that aim at helping people in their daily life that they have some sort of Ambient Intelligence. Learning the preferences and habits of users then becomes an important step in allowing a system to provide such personalized services. Thus far, the exploration of these issues by the scientific community has not been extensive, but interest in the area is growing. Ambient Intelligence environments have special characteristics that have to be taken into account during the learning process. We identify these characteristics and use them to highlight the strengths and weaknesses of developments so far, providing direction to encourage further development in this specific area of Ambient Intelligence.     

A survey of service composition in ambient intelligence environments

This article presents a comparative review of systems performing service composition in Ambient Intelligence Environments. Such environments should comply to ubiquitous or pervasive computing guidelines by sensing the user needs or wishes and offering intuitive human-computer interaction and a comfortable non-intrusive experience. To achieve this goal service orientation is widely used and tightly linked with AmI systems. Some of these employ the Web Service technology, which involves well-defined web technologies and standards that facilitate interoperable machine to machine interaction. Other systems regard services of different technologies (e.g. UPnP, OSGi etc) or generally as abstractions of various actions. Service operations are sometimes implemented as software based functions or actions over hardware equipment (e.g. UPnP players). However, a single service satisfies an atomic only user need, so services need to be composed (i.e. combined), in order to provide the usually requested complex tasks. Since manual service composition is obviously a hassle for the user, ambient systems struggle to automate this process by applying various methods. The approaches that have been adopted during the last years vary widely in many aspects, like domain of application, modeling of services, composition method, knowledge representation and interfaces. This work presents a comparative view of these approaches revealing similarities and differences, while providing additional information.     

PRISMATICA: toward ambient intelligence in public transport environments

On-line surveillance to improve safety and security is a major requirement for the management of public transport networks and other public places. The surveillance task is a complex one involving people, management procedures, and technology. This work describes an architecture that takes into account the distributed nature of the detection processes and the need to allow for different types of devices and actuators. This was part of a major European initiative on intelligent transport systems. Because of the dominant nature of closed circuit television in surveillance, This work describes in detail a computer-vision module used in the system and its particular ability to detect situations of interest in busy conditions. The system components have been implemented, integrated, and tested in real metropolitan railway environments and are considered to be the first step toward providing ambient intelligence in such complex scenarios. Results are presented that not only deal with detection performance, but also on the perception of people who used the system on its effectiveness and potential impact.     

CoWSAMI: Interface-aware context gathering in ambient intelligence environments

In this paper we present CoWSAMI, a middleware infrastructure that enables context awareness in open ambient intelligence environments, consisting of mobile users and context sources that become dynamically available as the users move from one location to another. A central requirement in such dynamic scenarios is to be able to integrate new context sources and users at run-time. CoWSAMI exploits a novel approach towards this goal. The proposed approach is based on utilizing Web services as interfaces to context sources and dynamically updatable relational views for storing, aggregating and interpreting context. Context rules are employed to provide mappings that specify how to populate context relations, with respect to the different context sources that become dynamically available. An underlying context sources discovery mechanism is utilized to maintain context information up to date as context sources, and users get dynamically involved.     

A distributed platform for personalized advertising in digital interactive TV environments

Advertising plays an important role in modern free markets. Furthermore, advertising is moving towards the establishment of one-to-one marketing relationships. Thus, personalized advertisement is currently considered as a hot topic in product promotion as it can be proved beneficial for all the key players, such as the advertisers, the advertised companies, as well as the consumers. Interactive TV and WWW can provide the means for personalized advertising. But of course, special systems and platforms for personalization must be first developed. This paper proposes a prototype system which efficiently achieves the personalization of the advertisements in the environment of digital interactive TV. Thus, the environment for the exploitation of the proposed system are examined, the details in design and implementation are given, while extensive operation testing and evaluation are provided proving its high applicability in real business environments.     

Semantic-based framework for personalised ambient media

The paper proposes a semantic-based metadata framework for personalised interaction with TV media in a connected home context. Our approach allows the current home media centres to go beyond the simple concept of electronic programme guides and to offer the users a personalised media experience in an ambient home environment. The user’s characteristics, preferences and context are used to personalise the user’s experience of viewing and interacting with multimedia content on different heterogeneous devices. The TV-Anytime specification provides the basis for the metadata framework for handling content from IP, digital broadcast, and Blu-ray disc sources.     

以个性化服务抢占竞争制高点

台州电信贯彻中国电信“用户至上，用户服务”的服务理念，提出了二十四字服务工作原则，在三个方面进行服务创新。（1）尊重个性，体现差异，以服务的模式化，标准化为基础，融入灵活的个性化。（2）创新管理，支撑服务，健全服务链。（3）加强监督，严格考核，完善服务质量内外监督检查机制，台州电信在创新中取得了良好的业绩。     

Task-driven automated component deployment for ambient intelligence environments

This article presents a strategy for deploying component-based applications gradually in order to match the functionality of pervasive computing applications onto the current needs of the user. We establish this deployment strategy by linking component composition models with task models at design-time, from which a run-time deployment plan is deduced. Enhanced with a Markov model, this deployment plan is able to drive a component life cycle manager to anticipate future deployments. The result is a seamless integration of pervasive computing applications with the user’s tasks, guaranteeing the availability of the required functionality without wasting computing resources on components that are not currently needed.     

Computational organization of didactic contents for personalized virtual learning environments

This paper presents an organization model for personalized didactic contents used in individual study environments. For many students the availability of contents in a general form might not be effective. A multilevel structure of concepts is proposed to provide different presentation combinations of the same content. Our work shows that it is possible to personalize the didactic content in order to encourage students, by using proximal learning patterns. These patterns are obtained from the analysis of the actions of students with positive results in the individual content organization. The system uses artificial intelligence techniques to reactively organize and personalize content. Personalization is made possible by means of an artificial neural network that classifies the student's profile and assigns it a proximal learning pattern. Expert rules are used to mediate and adjust the contents reactively. Experimental results indicate that the approach is efficient and provides the student a better use of the content with adaptive and reactive personalized presentation.     

An ambient intelligence approach for learning in smart robotic environments

Smart robotic environments combine traditional (ambient) sensing devices and mobile robots. This combination extends the type of applications that can be considered, reduces their complexity, and enhances the individual values of the devices involved by enabling new services that cannot be performed by a single device. To reduce the amount of preparation and preprogramming required for their deployment in real‐world applications, it is important to make these systems self‐adapting. The solution presented in this paper is based upon a type of compositional adaptation where (possibly multiple) plans of actions are created through planning and involve the activation of pre‐existing capabilities. All the devices in the smart environment participate in a pervasive learning infrastructure, which is exploited to recognize which plans of actions are most suited to the current situation. The system is evaluated in experiments run in a real domestic environment, showing its ability to proactively and smoothly adapt to subtle changes in the environment and in the habits and preferences of their user(s), in presence of appropriately defined performance measuring functions.     

Automating identification of services and their variability for product lines using NSGA-II

Architecture-level business services are identified based on business processes; and likewise, in service-oriented product lines, identifying the domain architecture-level business services and their variability is preferred to be based on business processes and their variability. Identification of business services for a product line satisfying a set of given design metrics (such as cohesion and coupling) is extremely difficult for a domain architect, since there are many product configurations for which the services must be proper at the same time. This means that the identified services must have proper values for n metrics in m different configurations at the same time. The problem becomes more serious when there are high degrees of variability and complexity embedded in the business processes that are the basis for service identification.We contribute to solve the multi-objective optimization problem of identifying business services for a product line by partitioning the graph of a business process variability model utilizing Non-dominated Sorting Genetic Algorithm-II. The service specification is achieved based on the results of the partitioning. The variability of the services is then determined in terms of mandatory and optional services as well as variability relationships, which are all represented in a Service Variability Model. The method was empirically evaluated through experimentation, and showed proper levels of reusability and variability. Furthermore, the resulting models were fully consistent.