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.     

An Inquiry-led Personalised Navigation System (IPNS) using multi-dimensional linkbases

The simplicity of the hypertext model behind the World Wide Web is a factor in its success, but this simplicity brings limitations. One of these limitations is embedding links in documents. Open Hypermedia addresses this by instead storing them in separate link databases. Meanwhile, the Adaptive Hypermedia approach seeks to enhance a user's experience by inserting personalised additional content and links on the web page. However, these techniques do not offer the user any control over the adaptation. In this paper, we propose the concept of a multi-dimensional linkbase for adaptive links presentation. Links are created and stored in a single, multi-dimensional, linkbase that provides presentation links based on the user's preferences and profile. We present a web-based system Inquiry-led Personalised Navigation System that implements this multi-dimensional concept for controlling its personalisation of hyperlinks. We give the results of our evaluation, which confirm that user-controlled adaptation is a satisfactory approach to providing users with control over personalisation, and can alleviate the link overload problem.     

User profiles and fuzzy logic for web retrieval issues

 We present a study of the role of user profiles using fuzzy logic in web retrieval processes. Flexibility for user interaction and for adaptation in profile construction becomes an important issue. We focus our study on user profiles, including creation, modification, storage, clustering and interpretation. We also consider the role of fuzzy logic and other soft computing techniques to improve user profiles. Extended profiles contain additional information related to the user that can be used to personalize and customize the retrieval process as well as the web site. Web mining processes can be carried out by means of fuzzy clustering of these extended profiles and fuzzy rule construction. Fuzzy inference can be used in order to modify queries and extract knowledge from profiles with marketing purposes within a web framework. An architecture of a portal that could support web mining technology is also presented.     

Semantic enhancement for media asset management systems

The socio-economic development of the World Wide Web gathered a large momentum through Web 2.0 and currently, the Web of Data is adding a further technological driver to this. The tremendous growth of media data combined with structured (linked) data promises further opportunities for digital market places. Although the integration of media content with linked data is only beginning there are already working groups and projects addressing this issue. We show how media and existing data sets can be seamlessly integrated and thus give possibilities for an extended user experience while interacting with media content on the web. We focus on automatic semantic enhancement services that can link arbitrary and open accessible data and introduce opportunities for media annotation, fragmentation and presentation. Our use case scenario is based on the Red Bull Content Pool, a media management system for videos, images and articles about Red Bull related content covering a multitude of sports events.     

A web content manipulation technique based on page Fragmentation

Web portals today offer a variety of content and services to their users. This content can be split into various categories and usually content semantically related is placed in the same area. In this paper, a software technique is presented that allows the viewers of web sites to build their own personalized portals, using specific areas of their preferred sites. This technique saves users’ time and reduces the cost of browsing the web by minimizing the volume of data that has to be downloaded. It is based on an algorithm, which fragments a web page in discrete fragments using the page's internal structure. Users utilize a web interface to define which parts of selected web pages they desire to appear in their personalized portal. No additional software needs to be installed on the users’ personal computers, since this technique is designed to function centrally as a data source for a Web Server. In addition, usage of this technique reduces user perceived latency during browsing sessions, since less data must be transferred to users’ personal computers.     

Personalising web page presentation for older people

This paper looks at different ways of personalising web page presentation to alleviate functional impairments in older people. The paper considers how impairments may be addressed by web design and through various personalisation instruments: accessibility features of standard browsers, proxy servers, assistive technology, application adaptors, and special purpose browsers. A pilot study of five older web users indicated that the most favoured personalisation technique was overriding the CSS (cascading style sheet) with a readily available one using a standard browser. The least favoured one was using assistive technology. In a follow-up study with 16 older web users, performing goal-directed browsing tasks, overriding CSS remains the most favoured. Assistive technology remains the least favoured and the slowest. Based on user comments, one-take-home message for web personalisation instrument developer is that the best instrument for older persons is one that most faithfully preserves the original layout while requiring the least effort.     

Web personalization for user acceptance of technology: An empirical investigation of E-government services

E-Commerce firms have adopted Web Personalization techniques extensively in the form of recommender systems for influencing user behavior for customer retention. Although there are numerous studies in this area, academic research addressing the role of Web Personalization in user acceptance of technology is very scant. Further, owing to the potential of recommender systems to attract and retain customers, most studies in web personalization have been done in E-Commerce setting. In this research, the ‘Consumer Acceptance and Use of Information Technology’ theory proposed in previous research has been extended to include web personalization as a moderator and has been tested in an E-Government context. Data collection involved conducting a laboratory experiment with the treatment group receiving personalized web forms for requesting an E-Government service. Our analyses show that personalizing the Web by self-reference and content relevance has a significant moderator role in influencing the relationship between determinants of intention to use and behavioral intention in certain cases.     

基于有界限模型检验的服务建模与自动组合

针对面向服务架构(SOA)体系的Web服务数量快速增长现状,为实现大规模服务场景下高效自动组合Web服务来满足用户复杂需求问题,提出一种基于有界模型检验的Web服务组合方法.其中,Web服务被建模为有限状态自动机,众多Web服务构成服务社区,Web服务组合需求由线性时态逻辑公式描述,通过有界模型检验器的系统化搜索,该方...     

Preference-driven personalization for flexible digital item adaptation

The delivery of multimedia content often needs the adaptation of the content in order to satisfy user constraints. With the Digital Item Adaptation part, the MPEG-21 standard already defines a useful frame-work to handle this task. However, in modern service-oriented architectures the functionality of adaptation is split over several services. Hence, the central instantiation of a suitable service chain needs to tackle a complex multi-objective optimization problem. In this problem between content choice and possible adaptations the current preference model in the MPEG-7/21 standard still lacks expressiveness. In the course of this paper we demonstrate this shortcoming and how the integration of more powerful models can ease the instantiation problem. Furthermore we explain how to efficiently evaluate preference trade-offs by evaluating skyline queries as currently investigated in the field of information systems. As a running example we use preference-based content adaptation in a typical media streaming application with Web services as basic modules. The contribution of our framework is to enable a central coordinator to instantiate an executable service composition chain by integrating all needed Web services to adapt the multimedia content in the best possible fashion in the sense of Pareto optimality. This work was supported in part by the German Research Foundation (DFG) within the Emmy-Noether Program of Exellence.     

Device independence and the Web

Device manufacturers, users, and authors have differing needs and expectations when it comes to Web content. Web software and hardware manufacturers naturally try to differentiate their products by supporting a special combination of capabilities, but few can expect Web authors to create content for their product alone. Users, however, do expect to access the same content from any device with similar capabilities. Even when device capabilities differ, users might still want access to an adapted version of the content. Due to device differences, the adaptation might not produce an identical presentation, but device-independence principles suggest it should be sufficiently functional to let users interact with it successfully. Web application authors cannot afford to create multiple content versions for each of the growing range of device types. Authors would rather create their content once, and adapt it to different devices-but they also want to retain control of presentation quality. Device independence is about trying to satisfy these differing needs, spanning the delivery path between author and user by way of diverse manufacturers' devices. The field's continued evolution within the broader Web standards framework aims to find solutions that are beneficial for all.     

A Hierarchical Fuzzy Clustering-based System to Create User Profiles

The rapid development of the World Wide Web as a medium of commerce and information dissemination has generated a growing interest of web portal managers in systems able to identify user profiles from the web access logs. The interpretation of these profiles can help re-organize the web portal, e.g., by restructuring the site’s content more efficiently, or even to build adaptive web portals, i.e., portals whose organization and presentation change depending on the specific visitor’s needs. In this paper, we assume that the pages of the web portal have been prearranged in a number of different categories. We introduce a systematic approach to determine a hierarchy of user profiles from the history of users’ accesses to the categories. First, we filter the access log by removing both occasional users and categories of poor interest. Then, we apply an Unsupervised Fuzzy Divisive Hierarchical Clustering (UFDHC) algorithm to cluster the users of the web portal into a hierarchy of fuzzy groups characterized by a set of common interests and each represented by a prototype, which defines the profile of the group typical member. To identify the profile a specific user belongs to, we propose a novel classification method which completely exploits the information contained in the hierarchy. To prove the effectiveness of our approach, we apply the UFDHC algorithm to access log data collected over a period of 15 days and use the classification method to associate a profile with the users defined by access log data collected during subsequent 60 days. Finally, we highlight the good characteristics of our system by comparing our results with the ones obtained by applying a profiling system based on a modified version of the fuzzy C-means.     

Adapting Web content to mobile user agents

In this article, we describe an adaptation proxy we developed as a part of a Kontti research project at VTT Information Technology that lets mobile users access Web content that's not directly targeted to mobile user agents. More and more content is now available on the Internet, and there's a growing need for mobile users to be able to access it. Thus the authors describe the adaptation proxy, which lets mobile users access Web content that's not directly targeted to user agents of mobile devices. The adaptation proxy can adapt Extensible Hypertext Markup Language (XHTML) documents into XHTML mobile profile (XHTML MP) and Wireless Markup Language (WML), and can perform media adaptation. At the system's core is an adaptation framework to which new source and target XML languages can be introduced with relatively little effort.     

Toward location-aware Web: extraction method,applications and evaluation

Location-based services (LBS) belong to one of the most popular types of services today. However, a recurring issue is that most of the content in LBS has to be created from scratch and needs to be explicitly tagged to locations, which makes existing Web content not directly usable for LBS. In this paper, we aim at making Web sites location-aware and feed this information to LBS. Our approach toward location-aware Web is threefold: First, we present a location extraction method: SALT. It receives Web sites as input and equips them with location tags. Compared to other approaches, SALT is capable of extracting locations with a precision up to the street level. Performance evaluations further show high applicability for practice. Second, we present three applications for SALT: Webnear.me, Local Browsing and Local Facebook. Webnear.me offers location-aware Web surfing through a mobile Web site and a smartphone app. Local Browsing adds the feature to browse by nearby tags, extracted from Web sites delivered by SALT. Local Facebook extends location tagging to social networks, allowing to run SALT on one’s own and one’s friends’ timeline. Finally, we evaluate SALT for technology acceptance of Webnear.me through a formative user study. Through real user data, collected during a 3 months pilot field deployment of Webnear.me, we assess whether SALT is a proper instance of “location of a Web site”.     

Efficient and Secure Content Processing and Distribution by Cooperative Intermediaries

Content services such as content filtering and transcoding adapt contents to meet system requirements, display capacities, or user preferences. Data security in such a framework is an important problem and crucial for many Web applications. In this paper, we propose an approach that addresses data integrity and confidentiality in content adaptation and caching by intermediaries. Our approach permits multiple intermediaries to simultaneously perform content services on different portions of the data. Our protocol supports decentralized proxy and key management and flexible delegation of services. Our experimental results show that our approach is efficient and minimizes the amount of data transmitted across the network.     

应用模糊分析层次法可靠评测Web资源质量

建立了一个Web资源质量评测系统.该系统将AHP算法与模糊逻辑相结合,以解决Web资源质量评测中模糊和不确定问题.另外,模糊AHP算法中集成了评测置信度和风险指标,以增强评测精度和提高Web资源质量评测的可靠性.     

Web user profiles with time-decay and prototyping

User profiling represents an important initial step in personalizing web services and in building recommendation systems. Non-invasive profiling methods monitor users’ behavior and infer interest profiles from their past actions. Most existing profiling methods, which relate the users’ interests to a given ontology, consider only the user’s past actions when calculating his/her profile. The profiling algorithms use a time-decay function for users’ past actions to adapt the profile to shifts in the user’s interests over time. In our work, we propose a hybrid method that combines time-decay and profile correction using prototype profiles. The additional profile correction step considers the interests of similar users and expands the interest scores beyond the concepts detected in the user’s past actions, which facilitates faster profile adaptation to the user’s new interests. In our experimental work, we experimented extensively with two real data sets: data of an online advertising network and student data in an online e-learning environment. We measured the quality of the computed user profiles by correlating them to users’ future actions. Experiments revealed that it is crucial to build the user’s profile using a large number of events from his/her past and to update the profile regularly. When we are unable to do so, the profile correction can be used to keep the quality of the profile from dropping too low. The results show that our method significantly outperforms existing ontological profiling methods.     

A cognitive approach for agent-based personalized recommendation

There is an increasing need for various e-service, e-commerce and e-business sites to provide personalized recommendations to on-line customers. This paper proposes a new type of personalized recommendation agents called fuzzy cognitive agents. Fuzzy cognitive agents are designed to give personalized suggestions based on the user’s current personal preferences, other user’s common preferences, and expert’s domain knowledge. Fuzzy cognitive agents are able to represent knowledge via extended fuzzy cognitive maps, to learn users’ preferences from most recent cases and to help customers make inferences and decisions through numeric computation instead of symbolic and logic deduction. A case study is included to illustrate how personalized recommendations are made by fuzzy cognitive agents in e-commerce sites. The case study demonstrates that the fuzzy cognitive agent is both flexible and effective in supporting e-commerce applications.