50,416 research outputs found

    The Structured Process Modeling Method (SPMM) : what is the best way for me to construct a process model?

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    More and more organizations turn to the construction of process models to support strategical and operational tasks. At the same time, reports indicate quality issues for a considerable part of these models, caused by modeling errors. Therefore, the research described in this paper investigates the development of a practical method to determine and train an optimal process modeling strategy that aims to decrease the number of cognitive errors made during modeling. Such cognitive errors originate in inadequate cognitive processing caused by the inherent complexity of constructing process models. The method helps modelers to derive their personal cognitive profile and the related optimal cognitive strategy that minimizes these cognitive failures. The contribution of the research consists of the conceptual method and an automated modeling strategy selection and training instrument. These two artefacts are positively evaluated by a laboratory experiment covering multiple modeling sessions and involving a total of 149 master students at Ghent University

    Automated user modeling for personalized digital libraries

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    Digital libraries (DL) have become one of the most typical ways of accessing any kind of digitalized information. Due to this key role, users welcome any improvements on the services they receive from digital libraries. One trend used to improve digital services is through personalization. Up to now, the most common approach for personalization in digital libraries has been user-driven. Nevertheless, the design of efficient personalized services has to be done, at least in part, in an automatic way. In this context, machine learning techniques automate the process of constructing user models. This paper proposes a new approach to construct digital libraries that satisfy user’s necessity for information: Adaptive Digital Libraries, libraries that automatically learn user preferences and goals and personalize their interaction using this information

    Identifying and Modelling Complex Workflow Requirements in Web Applications

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    Workflow plays a major role in nowadays business and therefore its requirement elicitation must be accurate and clear for achieving the solution closest to business’s needs. Due to Web applications popularity, the Web is becoming the standard platform for implementing business workflows. In this context, Web applications and their workflows must be adapted to market demands in such a way that time and effort are minimize. As they get more popular, they must give support to different functional requirements but also they contain tangled and scattered behaviour. In this work we present a model-driven approach for modelling workflows using a Domain Specific Language for Web application requirement called WebSpec. We present an extension to WebSpec based on Pattern Specifications for modelling crosscutting workflow requirements identifying tangled and scattered behaviour and reducing inconsistencies early in the cycle

    Requirements for an Adaptive Multimedia Presentation System with Contextual Supplemental Support Media

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    Investigations into the requirements for a practical adaptive multimedia presentation system have led the writers to propose the use of a video segmentation process that provides contextual supplementary updates produced by users. Supplements consisting of tailored segments are dynamically inserted into previously stored material in response to questions from users. A proposal for the use of this technique is presented in the context of personalisation within a Virtual Learning Environment. During the investigation, a brief survey of advanced adaptive approaches revealed that adaptation may be enhanced by use of manually generated metadata, automated or semi-automated use of metadata by stored context dependent ontology hierarchies that describe the semantics of the learning domain. The use of neural networks or fuzzy logic filtering is a technique for future investigation. A prototype demonstrator is under construction

    A Collaborative System Software Solution for Modeling Business Flows Based on Automated Semantic Web Service Composition

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    Nowadays, business interoperability is one of the key factors for assuring competitive advantage for the participant business partners. In order to implement business cooperation, scalable, distributed and portable collaborative systems have to be implemented. This article presents some of the mostly used technologies in this field. Furthermore, it presents a software application architecture based on Business Process Modeling Notation standard and automated semantic web service coupling for modeling business flow in a collaborative manner. The main business processes will be represented in a single, hierarchic flow diagram. Each element of the diagram will represent calls to semantic web services. The business logic (the business rules and constraints) will be structured with the help of OWL (Ontology Web Language). Moreover, OWL will also be used to create the semantic web service specifications.automated service coupling, business ontology, semantic web, BPMN, semantic web

    Adaptive hypermedia for education and training

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    Adaptive hypermedia (AH) is an alternative to the traditional, one-size-fits-all approach in the development of hypermedia systems. AH systems build a model of the goals, preferences, and knowledge of each individual user; this model is used throughout the interaction with the user to adapt to the needs of that particular user (Brusilovsky, 1996b). For example, a student in an adaptive educational hypermedia system will be given a presentation that is adapted specifically to his or her knowledge of the subject (De Bra & Calvi, 1998; Hothi, Hall, & Sly, 2000) as well as a suggested set of the most relevant links to proceed further (Brusilovsky, Eklund, & Schwarz, 1998; Kavcic, 2004). An adaptive electronic encyclopedia will personalize the content of an article to augment the user's existing knowledge and interests (Bontcheva & Wilks, 2005; Milosavljevic, 1997). A museum guide will adapt the presentation about every visited object to the user's individual path through the museum (Oberlander et al., 1998; Stock et al., 2007). Adaptive hypermedia belongs to the class of user-adaptive systems (Schneider-Hufschmidt, KĂźhme, & Malinowski, 1993). A distinctive feature of an adaptive system is an explicit user model that represents user knowledge, goals, and interests, as well as other features that enable the system to adapt to different users with their own specific set of goals. An adaptive system collects data for the user model from various sources that can include implicitly observing user interaction and explicitly requesting direct input from the user. The user model is applied to provide an adaptation effect, that is, tailor interaction to different users in the same context. In different kinds of adaptive systems, adaptation effects could vary greatly. In AH systems, it is limited to three major adaptation technologies: adaptive content selection, adaptive navigation support, and adaptive presentation. The first of these three technologies comes from the fields of adaptive information retrieval (IR) and intelligent tutoring systems (ITS). When the user searches for information, the system adaptively selects and prioritizes the most relevant items (Brajnik, Guida, & Tasso, 1987; Brusilovsky, 1992b)
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