35187915
Conceptual Data Modelling in Database Design: Similarities and Differences between Expert and Novice Designers
Abstract This paper explores the similarities and differences between experts and novices engaged in a conceptual data modelling task, a critical part of overall database design, using data gathered in the form of think-aloud protocols. It develops a three-level process model of the subjects' behavior and the differentiated application of this model by experts and novices. The study found that the experts focused on generating a holistic understanding of the problem before developing the conceptual model. They were able to categorize problem descriptions into standard abstractions. The novices tended to have more errors in their solutions largely due to their inability to integrate the various parts of the problem description and map them into appropriate knowledge structures. The study also found that the expert and novice behavior was similar in terms of modelling facets like entity, identifier, descriptor and binary relationship, somewhat different in modelling ternary relationship, but quite different in the modelling of unary relationship and category. These findings are discussed in relation to the results of previous expert-novice studies in other domains.
3198534
Understanding Information Technology Complementarities Using an Augmented Endogenous Growth Framework
The complex relationships between information technology investments and organizational practices have been the focus of intensive research in recent years. The research focus appears to have shifted to investigating the effects of various organizational practices and their interactions with information technology capital. There also is emerging evidence of recent emphasis on organizational factors and a greater shift toward IT complementarities in which value addition is linked to combining complementary organizational practices with IT investments. In this paper we focus on the contributions of IT use and organizational practices and their interactions. We use firm-level data to extend previous studies in three ways: (1) by using a large sample covering 3,299 firms spanning 11 industries, (2) by focusing on a large number of organizational practices, and (3) by augmenting the endogenous growth accounting framework with a data mining technique. Our findings indicate that the set of interrelated organizational practices that complement positively to IT use is different from the set of practices hindering IT use. We conclude that IT complementary factors that positively affect productivity growth do not necessarily have a reverse effect when they are reduced or removed. It appears that some organizational factors have asymmetrical effects on growth.
17316572
Aligning Ontologies through Formal Concept Analysis
Abstract.Ontologies have been developed for a number of knowledge domains as di-verseasclinicalterminology,photocamerapartsandmicro-arraygeneexpressiondata.However,aninnatecharacteristicofthedevelopmentofontologiesisthattheyareoftencreatedbyindependentgroupsofexpertise,whichgeneratedthenecessityofmergingandaligningontologiescoveringoverlappingdomains.Manyalgorithmsandtoolshavebeenproposedformergingofontologies,butmostofthemdisregardthestructuralpropertiesofthesourceontologies,focusingmostlyonsyntacticanalysis.This article focuses on an alignment method for ontologies based on Formal ConceptAnalysis,adataanalysistechniquefoundedonlatticetheory. 1 Introduction IntheheartofSemanticWebinitiative,proposedbyTimBerners-lee[2,3],liestheideaofmachineprocessableinformation,suchthatautomatedagents,orsoftbots,couldscanthewebspaceforinformationwithaspeciﬂcmeaning.Nevertheless,theunderstandingofmeaninginWebpagesdesignedforhumansisnotaneasytaskforthepresentgenerationofsoftbotsandontologiescangreatlyassistinthisendeavour.Manyinitiativesaroundtheworldhavecreatedontologies.Someoftheseontologieswerecreatedforhighleveldescriptionoftheworld,whereasothersrepresentveryspeciﬂcsub-jects,likebreastcancer,forinstance.Sometimes,ontologiesdevelopedindependentlymayhavesomeoverlaps.TheforementionedBreastCancerOntology,forexample,mayhavecommonconceptsandrelationswithaGeneOntology.Theseoverlapsareveryimpor-tantfromthepointofviewofinformationintegration,becausethecommonontologicalentitieshavetobeidentiﬂedbeforeinformationcanbesuccessfullyintegrated.Forthisreason,mergeandalignmentofontologieshavereceivedsigniﬂcantattentionfromtheresearchcommunityinthelastsixyears.Theﬂrstimportantissueinmerge/alignmentofontologiesistherelationsymbol-meaning.Ontologiesareconstitutedofsymbols(entities)andrelationsbetweensymbols.However,inSemiotics[18]symbolshaveassociatedmeaning,whichlinksthemtotheirreferent
1126755
Creating Shared Information Spaces to Support Collaborative Design Work
The provision of computer support for collaborative work is a central concern for Information Systems (IS) research and practice. In this paper we present the details of an information flow study undertaken in the household division of a large European design and manufacturing company (Delta). The goal of the study was to elicit user requirements for a computer system to facilitate the collaborative work of new product design teams. These requirements form the basis for the design and development of a Web-based LIRÉ (Living Repository) prototype system, the functionalities, features, and rationale of which are discussed. We also present the results of the evaluation of LIRÉ by the users at Delta and our observations on enhancing the sophistication and usefulness of this class of system. A production version based on the prototype but using commercially available software is currently in use by the New Product Development group at Delta.
10674834
Visual Categorization of Children and Adult Walking Styles
We present an approach for visual discrimination of children from adults in video using characteristic regularities present in their locomotion patterns. The framework employs computer vision to analyze correlated, scale invariant locomotion properties for classifying different styles of walking. Male and female subjects for the experiments include six children (3-5 yrs) and nine adults (30-52 yrs). For the analysis, we coordinate a minimalist point-representation of the human body with a space-time analysis of head and ankle trajectories to characterize the modality. Together the properties of relative stride length and stride frequency are shown to clearly differentiate children from adult walkers. The highly correlated log-linear relationships for the stride properties are exploited to reduce the categorization problem to a linear discrimination task. Using a trained two-class linear perceptron, we were able to achieve a correct classification rate of 93-95% on our dataset. Our approach emphasizing the natural modal behavior in human motion offers a useful and general methodology as the basis for designing efficient motion recognition systems using limited visual features.
736283
System support for pervasive applications
Pervasive computing provides an attractive vision for the future of computing. Computational power will be available everywhere. Mobile and stationary devices will dynamically connect and coordinate to seamlessly help people in accomplishing their tasks. For this vision to become a reality, developers must build applications that constantly adapt to a highly dynamic computing environment. To make the developers' task feasible, we present a system architecture for pervasive computing, called <i>one.world</i>. Our architecture provides an integrated and comprehensive framework for building pervasive applications. It includes services, such as discovery and migration, that help to build applications and directly simplify the task of coping with constant change. We describe our architecture and its programming model and reflect on our own and others' experiences with using it.
29147523
SCAPE: shape completion and animation of people
We introduce the SCAPE method (Shape Completion and Animation for PEople)---a data-driven method for building a human shape model that spans variation in both subject shape and pose. The method is based on a representation that incorporates both articulated and non-rigid deformations. We learn a pose deformation model that derives the non-rigid surface deformation as a function of the pose of the articulated skeleton. We also learn a separate model of variation based on body shape. Our two models can be combined to produce 3D surface models with realistic muscle deformation for different people in different poses, when neither appear in the training set. We show how the model can be used for shape completion --- generating a complete surface mesh given a limited set of markers specifying the target shape. We present applications of shape completion to partial view completion and motion capture animation. In particular, our method is capable of constructing a high-quality animated surface model of a moving person, with realistic muscle deformation, using just a single static scan and a marker motion capture sequence of the person.
16674358
Change of Representation for Statistical Relational Learning
Statistical relational learning (SRL) algorithms learn statistical models from relational data, such as that stored in a relational database. We previously introduced view learning for SRL, in which the view of a relational database can be automatically modified, yielding more accurate statistical models. The present paper presents SAYU-VISTA, an algorithm which advances beyond the initial view learning approach in three ways. First, it learns views that introduce new relational tables, rather than merely new fields for an existing table of the database. Second, new tables or new fields are not limited to being approximations to some target concept; instead, the new approach performs a type of predicate invention. The new approach avoids the classical problem with predicate invention, of learning many useless predicates, by keeping only new fields or tables (i.e., new predicates) that immediately improve the performance of the statistical model. Third, retained fields or tables can then be used in the definitions of further new fields or tables. We evaluate the new view learning approach on three relational classification tasks.
11683980
Qualitative interpretation of sensor patterns
A framework that provides the ability to generate qualitative interpretations (QIs) from multisensor trend patterns for monitoring, control, and optimization of chemical plants is presented. QIs are transformations of sensor and quality product data into useful symbolic abstractions. The framework is founded on the principles of similarity-based pattern recognition. Although demonstrated for normality identification, the machine methodology is general-purpose and applicable to any context-dependent QI problem. The objective of this approach is to create a QI-map of known pattern classes that consists of spatially distinguishable regions of patterns in an n-dimensional representation space. Creation of a QI-map is a two-step process: unsupervised map generation followed by supervised labeling. The application of the ART2 neural network for clustering in the QI-map is described. The application of the ART2-based QI-map approach to process monitoring of a recycle reactor is also described.<<ETX>>