Articulation of information requirements for personalised knowledge construction

The quality of information provision influences considerably knowledge construction driven by individual users’ needs. In the design of information systems for e-learning, personal information requirements should be incorporated to determine a selection of suitable learning content, instructive sequencing for learning content, and effective presentation of learning content. This is considered as an important part of instructional design for a personalised information package. The current research reveals that there is a lack of means by which individual users’ information requirements can be effectively incorporated to support personal knowledge construction. This paper presents a method which enables an articulation of users’ requirements based on the rooted learning theories and requirements engineering paradigms. The user’s information requirements can be systematically encapsulated in a user profile (i.e. user requirements space), and further transformed onto instructional design specifications (i.e. information space). These two spaces allow the discovering of information requirements patterns for self-maintaining and self-adapting personalisation that enhance experience in the knowledge construction process.     

An ontological process modelling framework for stochastic systems

Most process modelling techniques exist without any firm theoretical foundation. This results in a lack of model validation, which can be in-terms of model consistency, feasibility and goal compliance. Moreover, these techniques are mostly deterministic in nature and not applicable to stochastic systems. In this paper, we propose an ontology-based stochastic process modelling framework that further provides a specialization to failure and reliability issues. The framework is notation independent, and is primarily rooted in Bunge’s ontology. The well-established theory of reliability constructs are also mapped to facilitate the modelling of failure prone systems.     

Case-based analysis in user requirements modelling for knowledge construction

ContextLearning can be regarded as knowledge construction in which prior knowledge and experience serve as basis for the learners to expand their knowledge base. Such a process of knowledge construction has to take place continuously in order to enhance the learners’ competence in a competitive working environment. As the information consumers, the individual users demand personalised information provision which meets their own specific purposes, goals, and expectations.ObjectivesThe current methods in requirements engineering are capable of modelling the common user’s behaviour in the domain of knowledge construction. The users’ requirements can be represented as a case in the defined structure which can be reasoned to enable the requirements analysis. Such analysis needs to be enhanced so that personalised information provision can be tackled and modelled. However, there is a lack of suitable modelling methods to achieve this end. This paper presents a new ontological method for capturing individual user’s requirements and transforming the requirements onto personalised information provision specifications. Hence the right information can be provided to the right user for the right purpose.MethodAn experiment was conducted based on the qualitative method. A medium size of group of users participated to validate the method and its techniques, i.e. articulates, maps, configures, and learning content. The results were used as the feedback for the improvement.ResultThe research work has produced an ontology model with a set of techniques which support the functions for profiling user’s requirements, reasoning requirements patterns, generating workflow from norms, and formulating information provision specifications.ConclusionThe current requirements engineering approaches provide the methodical capability for developing solutions. Our research outcome, i.e. the ontology model with the techniques, can further enhance the RE approaches for modelling the individual user’s needs and discovering the user’s requirements.     

An analysis of specialist and non-specialist user requirements for geographic climate change information

The EU EuroClim project developed a system to monitor and record climate change indicator data based on satellite observations of snow cover, sea ice and glaciers in Northern Europe and the Arctic. It also contained projection data for temperature, rainfall and average wind speed for Europe. These were all stored as data sets in a GIS database for users to download. The process of gathering requirements for a user population including scientists, researchers, policy makers, educationalists and the general public is described. Using an iterative design methodology, a user survey was administered to obtain initial feedback on the system concept followed by panel sessions where users were presented with the system concept and a demonstrator to interact with it. The requirements of both specialist and non-specialist users is summarised together with strategies for the effective communication of geographic climate change information.     

PERSONAF: framework for personalised ontological reasoning in pervasive computing

Pervasive computing creates possibilities for presenting highly personalised information about the people, places and things in a building. One of the challenges for such personalisation is the creation of the system that can support ontological reasoning for several key tasks: reasoning about location; personalisation of information about location at the right level of detail; and personalisation to match each person’s conceptions of the building based on their own use of it and their relationship to other people in the building. From pragmatic perspectives, it should be inexpensive to create the ontology for each new building. It is also critical that users should be able to understand and control pervasive applications. We created the PERSONAF (personalised pervasive scrutable ontological framework) to address these challenges. PERSONAF is a new abstract framework for pervasive ontological reasoning. We report its evaluation at three levels. First, we assessed the power of the ontology for reasoning about noisy and uncertain location information, showing that PERSONAF can improve location modelling. Notably, the best ontological reasoner varies across users. Second, we demonstrate the use of the PERSONAF framework in Adaptive Locator, an application built upon it, using our low cost mechanisms for non-generic layers of the ontology. Finally, we report a user study, which evaluated the PERSONAF approach as seen by users in the Adaptive Locator. We assessed both the personalisation performance and the understandability of explanations of the system reasoning. Together, these three evaluations show that the PERSONAF approach supports building of low cost ontologies, that can achieve flexible ontological reasoning about smart buildings and the people in them, and that this can be used to build applications which give personalised information that can provide understandable explanations of the reasoning underlying the personalisation.     

An ontological model of an information system

An ontological model of an information system that provides precise definitions of fundamental concepts like system, subsystem, and coupling is proposed. This model is used to analyze some static and dynamic properties of an information system and to examine the question of what constitutes a good decomposition of an information system. Some of the major types of information system formalisms that bear on the authors' goals and their respective strengths and weaknesses relative to the model are briefly reviewed. Also articulated are some of the fundamental notions that underlie the model. Those basic notions are then used to examine the nature and some dynamics of system decomposition. The model's predictive power is discussed     

Semantic user profiling techniques for personalised multimedia recommendation

Due to the explosion of news materials available through broadcast and other channels, there is an increasing need for personalised news video retrieval. In this work, we introduce a semantic-based user modelling technique to capture users’ evolving information needs. Our approach exploits implicit user interaction to capture long-term user interests in a profile. The organised interests are used to retrieve and recommend news stories to the users. In this paper, we exploit the Linked Open Data Cloud to identify similar news stories that match the users’ interest. We evaluate various recommendation parameters by introducing a simulation-based evaluation scheme.     

Utilizing contextual ontological user profiles for personalized recommendations

As users may have different needs in different situations and contexts, it is increasingly important to consider user context data when filtering information. In the field of web personalization and recommender systems, most of the studies have focused on the process of modelling user profiles and the personalization process in order to provide personalized services to the user, but not on contextualized services. Rather limited attention has been paid to investigate how to discover, model, exploit and integrate context information in personalization systems in a generic way. In this paper, we aim at providing a novel model to build, exploit and integrate context information with a web personalization system. A context-aware personalization system (CAPS) is developed which is able to model and build contextual and personalized ontological user profiles based on the user’s interests and context information. These profiles are then exploited in order to infer and provide contextual recommendations to users. The methods and system developed are evaluated through a user study which shows that considering context information in web personalization systems can provide more effective personalization services and offer better recommendations to users.     

An ontological approach to support legal information modeling

Support for information, knowledge exchange and share is a key issue in the information society. Coming into contact with global sharing of resources, mutual well-understood knowledge of intellectual property is worthy of attention. However, there is a lack of systematic information-modeling methodology for the issue; closely connected to this problem is that most of the intelligent legal systems are undesirable and ineffective for multinational semantic mapping of article information. We propose an ontology-guided approach that provides semantic primitive representation of legal information with intention perspective. The domain ontology we developed is used as a fundamental conceptual framework to maintain the consistency among diverse legal representation.     

An ambient software monitoring system for unsupervised user modelling

This paper describes a means of unsupervised learning of recurring patterns in user activity through patterns in system level events generated by a graphical user interface. Earlier work has shown that using this distillation of the more complex behavioural interaction between the user and the application provides a symbolic representation of knowledge and goals that could be used to imply preference. Although prior research has explored the possibilities of removing this information acquisition bottleneck in such an expert system using ambient monitoring approaches, some have experienced difficulty in dealing with the varying length training sequences and segmentation of the continuous event stream. Unlike previous work the approach documented here handles interactions of varying sizes and is able to recall recurrent patterns in real time irrespective of the number of interactions learned. In addition to describing the proposed approach we also describe the shortcomings of various previously applied machine learning techniques on the same type of data. We also demonstrate a practical implementation of our approach applied to web browser usage.     

On web user tracking of browsing patterns for personalised advertising

On today’s Web, users trade access to their private data for content and services. App and service providers want to know everything they can about their users, in order to improve their product experience. Also, advertising sustains the business model of many websites and applications. Efficient and successful advertising relies on predicting users’ actions and tastes to suggest a range of products to buy. Both service providers and advertisers try to track users’ behaviour across their product network. For application providers this means tracking users’ actions within their platform. For third-party services following users, means being able to track them across different websites and applications. It is well known how, while surfing the Web, users leave traces regarding their identity in the form of activity patterns and unstructured data. These data constitute what is called the user’s online footprint. We analyse how advertising networks build and collect users footprints and how the suggested advertising reacts to changes in the user behaviour.     

User viewpoint modelling: understanding and representing user viewpoints during requirements definition

There has been increasing awareness of the impact of the early stages of systems development on the quality of information systems. A critical early activity is requirements definition, when the requirements for an information system are determined. Traditional requirements capture techniques do not support the collaborative nature of requirements definition or the emergent nature of requirements themselves. This paper focuses on viewpoint development as a means of resolving some of the difficulties of requirements definition. It proposes a user viewpoint model for capturing and representing the viewpoints of users during requirements acquisition. The model can facilitate communication and interaction between analysts and users and help build a shared understanding of requirements. It can be used to structure the requirements acquisition process. The model provides for evaluation of requirements acquisition techniques to guide the selection of appropriate techniques for developing user viewpoint models. The paper reports a multiple-case study of requirements definition efforts that examined user viewpoint development in practice and used the cases to validate empirically the concepts of the user viewpoint model. The implications of the case study findings for requirements definition practice are discussed, and some areas for future research are identified.     

Reusable tools for user modelling

This paper refines the notion of reusability of tools for user modelling by defining three layers of reusable tools. It then reviews several research projects that have developed such reusable tools, GUMS, GUMAC, BGP-MS, um and UMT. Finally it summarises the current state of research into reusable tools in terms of these systems.This work is supported by Telecom (Australia) Grant Reference Y05/04/34 and BLO/02/02/89.     

Functional and user requirements for IMACS.

An Image Management, Archiving and Communication System (IMACS) should integrate all imaging modalities in a diagnostic radiology department. In order to obtain this integration, manufacturers of diagnostic imaging modalities must follow the established standards for communication protocols and image formats. To gain acceptance, IMACS must result in one or more of the following: cost savings, improved efficiency or added diagnostic information. The increased possibilities for image processing should result in a reduced number of rejects and an improved and more uniform image quality. The IMACS should be interconnectable with a range of different Hospital Information Systems (HIS) and Radiological Information Systems (RIS). Interconnections with the HIS and the RIS are mandatory in order to fulfil the specified requirements with regard to access times and functionality.     

The um toolkit for cooperative user modelling

This paper gives an overview of the um toolkit: the philosophy underlying its design, examples of its use and discussion of the way it deals with some major issues in creating user modelling shells. The um toolkit has been developed to provide support for a variety of cooperative agents. An important element of its cooperativeness is due to its capacity to give users an understanding of their own user models. This paper describes two substantial but very different uses of the toolkit. The first involves a collection of coaching systems that help users learn more about their text editor. Experimental results suggest that the user model is associated with users learning more. The second is a movie advisor that uses a range of tools to construct and refine the user model and to filter a database of movies. Both these systems are built from combining tools in um. The paper describes several of the tools for constructing and refining user models. In addition it describes the user-model viewing tools and the way that these help users ensure their user models are correct. The paper also discusses the two central themes of the um work, the application of a tools approach to the design of a user modelling toolkit and the implications of making the user model accessible to its owner, the person modelled.     

An approach to information requirements specification for process control tasks

This paper discusses the need for designers of process plant supervisory systems to make greater effort in anticipating the information that operators require to carry out their duties. A method for dealing with this problem of information requirements specification in process plant design is proposed. This method translates a task analysis into a set of standard task elements from which standard sets of information, called ‘sub-goal templates’ can be derived. The resultant information requirements specification sets out the operators' information needs in the context of the operating goals that have to be attained. Early trials with the method indicate its promise, but highlight the need for its implementation in a computer tool to assist the designer. The features of such a tool and the further work necessary to develop and test the method are described.     

Investigating user activities and the corresponding requirements for information and functions in autonomous vehicles of the future

The potential benefits of autonomous vehicles, including safety, convenience, fuel economy, and low emissions can only be achieved when consumers are comfortable with the vehicle design. There are only a limited number of user studies in the design of future autonomous vehicles, owing to the difficulties of shifting focus “from the present to the future.” An integrated method of simulator study and user enactment was applied in the research to bridge the gap between the current and the future. Thirty drivers participated in the study to experience enacted driving scenarios in an autonomous vehicle simulator. The participants were divided into two groups, i.e., driving-alone drivers and driving-with-a-passenger drivers, to investigate the effect of passenger presence. Rich data were elicited about possible in-vehicle activities, the corresponding requirements of information and functions to support any such activities. Also identified were the preferred methods of interacting with the information and functions. Passenger presence was found to have an influence on the attributes of activities undertaken as well as the preferences for in-vehicle information and functions. Dominant themes were identified in future autonomous vehicle designs, including a more flexible and adaptive design language, concerns of trust and safety, and trade-offs between safety and convenience and between privacy and social connection. Based on the findings, design implications for future autonomous vehicles are discussed.     

An ontological basis for computer aided innovation

Knowledge acquisition and capitalization to solve problems concerning artefact evolution, still called inventive design, has a certain quantity of specific characteristics. It needs the choice of certain pieces of knowledge that may induce evolutions; it leads to reformulating the initial problem to build an abstract model of the artefact. The theoretical approach we are interested in, called TRIZ (the Russian acronym for Theory for Inventive Problem Solving), when translated into a methodological procedure, has not been fully formalized yet. This article proposes an ontology of the main notions of the concepts associated to knowledge acquisition in this framework. This ontology, beyond the clarification it brings to the involved notions, will be the support of a software architecture for implementing the method for knowledge acquisition and problem formulation.     

An ontological model of the domain of applications for the Internet of Things in analyzing information security

In this paper, we have proposed an ontological model for the application domain of the Internet of Things (IoT) that provides a detailed representation of the relationships and interrelations between system elements at different levels of abstraction with different degrees of detail. The ontological model allows one to understand the technical aspects of developing security information and event management (SIEM) systems for the detection and analysis of security incidents in the IoT.     

管理信息系统业务流程的OWL本体模型*

针对传统的开发方式将管理信息系统的业务流程以硬编码形式固化在系统软件中带来的诸多问题,将本体论的思想引入到管理信息系统软件的开发中,将其业务流程抽象成一个合理、机器可读的OWL本体模型,并进一步阐述问题的解决方法.