241,135 research outputs found
Conceptual modelling: framework, principles, and future research
The conceptual modelling task in a simulation project is very important and yet is still generally regarded as more of an art than a science. The meaning and nature of conceptual modelling are discussed and a framework set out. The overall aim should be to choose the best model for the project and conceptual modelling can be viewed as a difficult optimisation problem that can be tackled effectively using a creative search process that develops alternative models and predicts their performance throughout the project. An experiment relating model characteristics to some aspects of performance is described and this type of experiment may inform the process of predicting model performance. Based on advice from the literature and my own previous work on conceptual modelling 17 principles of conceptual modelling are suggested. Conceptual modelling research is still at an early stage and ideas for future research are proposed
Constraint capture and maintenance in engineering design
The Designers' Workbench is a system, developed by the Advanced Knowledge Technologies (AKT) consortium to support designers in large organizations, such as Rolls-Royce, to ensure that the design is consistent with the specification for the particular design as well as with the company's design rule book(s). In the principal application discussed here, the evolving design is described against a jet engine ontology. Design rules are expressed as constraints over the domain ontology. Currently, to capture the constraint information, a domain expert (design engineer) has to work with a knowledge engineer to identify the constraints, and it is then the task of the knowledge engineer to encode these into the Workbench's knowledge base (KB). This is an error prone and time consuming task. It is highly desirable to relieve the knowledge engineer of this task, and so we have developed a system, ConEditor+ that enables domain experts themselves to capture and maintain these constraints. Further we hypothesize that in order to appropriately apply, maintain and reuse constraints, it is necessary to understand the underlying assumptions and context in which each constraint is applicable. We refer to them as âapplication conditionsâ and these form a part of the rationale associated with the constraint. We propose a methodology to capture the application conditions associated with a constraint and demonstrate that an explicit representation (machine interpretable format) of application conditions (rationales) together with the corresponding constraints and the domain ontology can be used by a machine to support maintenance of constraints. Support for the maintenance of constraints includes detecting inconsistencies, subsumption, redundancy, fusion between constraints and suggesting appropriate refinements. The proposed methodology provides immediate benefits to the designers and hence should encourage them to input the application conditions (rationales)
Modeling social information skills
In a modern economy, the most important resource consists in\ud
human talent: competent, knowledgeable people. Locating the right person for\ud
the task is often a prerequisite to complex problem-solving, and experienced\ud
professionals possess the social skills required to find appropriate human\ud
expertise. These skills can be reproduced more and more with specific\ud
computer software, an approach defining the new field of social information\ud
retrieval. We will analyze the social skills involved and show how to model\ud
them on computer. Current methods will be described, notably information\ud
retrieval techniques and social network theory. A generic architecture and its\ud
functions will be outlined and compared with recent work. We will try in this\ud
way to estimate the perspectives of this recent domain
Probing physics students' conceptual knowledge structures through term association
Traditional tests are not effective tools for diagnosing the content and
structure of students' knowledge of physics. As a possible alternative, a set
of term-association tasks (the "ConMap" tasks) was developed to probe the
interconnections within students' store of conceptual knowledge. The tasks have
students respond spontaneously to a term or problem or topic area with a
sequence of associated terms; the response terms and timeof- entry data are
captured. The tasks were tried on introductory physics students, and
preliminary investigations show that the tasks are capable of eliciting
information about the stucture of their knowledge. Specifically, data gathered
through the tasks is similar to that produced by a hand-drawn concept map task,
has measures that correlate with inclass exam performance, and is sensitive to
learning produced by topic coverage in class. Although the results are
preliminary and only suggestive, the tasks warrant further study as
student-knowledge assessment instruments and sources of experimental data for
cognitive modeling efforts.Comment: 31 pages plus 2 tables and 8 figure
Recommended from our members
Harnessing agile concepts for the development of intelligent systems
Traditional and current approaches to intelligent systems design, have led to the creation of sophisticated and computationally-intensive packages and environments, for a wide range of applications. This paper proposes methods with which to extend the functionality of such systems, borrowing knowledge management concepts from the field of Agile Manufacturing. As such, this paper proposes that the future of intelligent systems design should be based not only upon the continuing development of artificial intelligence techniques, but also effective methods for harnessing human skills and core competencies to achieve these aims
Towards automated knowledge-based mapping between individual conceptualisations to empower personalisation of Geospatial Semantic Web
Geospatial domain is characterised by vagueness, especially in the semantic disambiguation of the concepts in the domain, which makes defining universally accepted geo- ontology an onerous task. This is compounded by the lack of appropriate methods and techniques where the individual semantic conceptualisations can be captured and compared to each other. With multiple user conceptualisations, efforts towards a reliable Geospatial Semantic Web, therefore, require personalisation where user diversity can be incorporated. The work presented in this paper is part of our ongoing research on applying commonsense reasoning to elicit and maintain models that represent users' conceptualisations. Such user models will enable taking into account the users' perspective of the real world and will empower personalisation algorithms for the Semantic Web. Intelligent information processing over the Semantic Web can be achieved if different conceptualisations can be integrated in a semantic environment and mismatches between different conceptualisations can be outlined. In this paper, a formal approach for detecting mismatches between a user's and an expert's conceptual model is outlined. The formalisation is used as the basis to develop algorithms to compare models defined in OWL. The algorithms are illustrated in a geographical domain using concepts from the SPACE ontology developed as part of the SWEET suite of ontologies for the Semantic Web by NASA, and are evaluated by comparing test cases of possible user misconceptions
Towards a Theory of Software Development Expertise
Software development includes diverse tasks such as implementing new
features, analyzing requirements, and fixing bugs. Being an expert in those
tasks requires a certain set of skills, knowledge, and experience. Several
studies investigated individual aspects of software development expertise, but
what is missing is a comprehensive theory. We present a first conceptual theory
of software development expertise that is grounded in data from a mixed-methods
survey with 335 software developers and in literature on expertise and expert
performance. Our theory currently focuses on programming, but already provides
valuable insights for researchers, developers, and employers. The theory
describes important properties of software development expertise and which
factors foster or hinder its formation, including how developers' performance
may decline over time. Moreover, our quantitative results show that developers'
expertise self-assessments are context-dependent and that experience is not
necessarily related to expertise.Comment: 14 pages, 5 figures, 26th ACM Joint European Software Engineering
Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE
2018), ACM, 201
Academic team formation as evolving hypergraphs
This paper quantitatively explores the social and socio-semantic patterns of
constitution of academic collaboration teams. To this end, we broadly underline
two critical features of social networks of knowledge-based collaboration:
first, they essentially consist of group-level interactions which call for
team-centered approaches. Formally, this induces the use of hypergraphs and
n-adic interactions, rather than traditional dyadic frameworks of interaction
such as graphs, binding only pairs of agents. Second, we advocate the joint
consideration of structural and semantic features, as collaborations are
allegedly constrained by both of them. Considering these provisions, we propose
a framework which principally enables us to empirically test a series of
hypotheses related to academic team formation patterns. In particular, we
exhibit and characterize the influence of an implicit group structure driving
recurrent team formation processes. On the whole, innovative production does
not appear to be correlated with more original teams, while a polarization
appears between groups composed of experts only or non-experts only, altogether
corresponding to collectives with a high rate of repeated interactions
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