Faceted Analysis Research Articles

Taxonomy of Virtual and Augmented Reality Applications in Education

This article presents and analyzes existing taxonomies of virtual and augmented reality and demonstrates knowledge gaps and mixed terminology, which may cause confusion among educators, researchers, and developers. Several such occasions of confusion are presented. A methodology is then presented to construct a taxonomy of virtual reality and augmented reality applications based on a combination of: a faceted analysis approach for the overall design of the taxonomy; an existing taxonomy of educational objectives to derive the educational purpose; an information systems analysis to establish important facets of the taxonomy; and two systematic mapping studies to identify categories within each facet. Using this methodology, a new taxonomy is proposed and the implications of its facets (and combinations of facets) are demonstrated. The taxonomy focuses on technology used to provide the virtual or augmented reality as well as the content presented to the user, including the type of gamification and how it is operated. It also accommodates a large number of devices and approaches developed throughout the years and for multiple industries, and provides a way to categorize them in order to clarify communication between researchers, developers, and educators. Use of the taxonomy is then demonstrated in two case studies-a virtual reality chemical plant for use in chemical engineering education and an augmented reality dog for veterinary education.

Human biases in body measurement estimation

Body measurements, including weight and height, are key indicators of health. Being able to visually assess body measurements reliably is a step towards increased awareness of overweight and obesity and is thus important for public health. Nevertheless it is currently not well understood how accurately humans can assess weight and height from images, and when and how they fail. To bridge this gap, we start from 1,682 images of persons collected from the Web, each annotated with the true weight and height, and ask crowd workers to estimate the weight and height for each image. We conduct a faceted analysis taking into account characteristics of the images as well as the crowd workers assessing the images, revealing several novel findings: (1) Even after aggregation, the crowd’s accuracy is overall low. (2) We find strong evidence of contraction bias toward a reference value, such that the weight of light people and the height of short people are overestimated, whereas the weight of heavy people and the height of tall people are underestimated. (3) We estimate workers’ individual reference values using a Bayesian model, finding that reference values strongly correlate with workers’ own height and weight, indicating that workers are better at estimating people similar to themselves. (4) The weight of tall people is underestimated more than that of short people; yet, knowing the height decreases the weight error only mildly. (5) Accuracy is higher on images of females than of males, but female and male workers are no different in terms of accuracy. (6) Crowd workers improve over time if given feedback on previous guesses. Finally, we explore various bias correction models for improving the crowd’s accuracy, but find that this only leads to modest gains. Overall, this work provides important insights on biases in body measurement estimation as obesity-related conditions are on the rise.

Big data moment and faceted theory: a structured review

Over the last years, information growth has been the source of a large volume and variety of data, therefore new processes to represent, organize, seek and retrieve the information are needed. The background theory that supports the big data settings is diverse, however, one theory has deserved special attention in the literature, not only as a model for structuring data but also for locating information: the faceted theory. In this paper, a brief review of the literature about big data and faceted theory is presented. According to literature, web system architecture based on the faceted analysis appears to be highly common even in the big data settings. Regarding description, navigation, seek and search, and retrieval of the information, the authors write up the faceted theory, methods, and models in a digital environment. Nevertheless, more theoretical and empirical work is necessary to firm up this standpoint.Keywords: Faceted theory, Big Data, Information seeking, Information retrieval, Web system architecture

Tesauros e ontologias como modelos de sistemas de organização do conhecimento

Discute os conceitos de organização e representação do conhecimento como subsídios para a compreensão dos tesauros e das ontologias enquanto modalidades de sistemas de organização do conhecimento. A análise das relações de complementaridade entre ambos os instrumentos faz-se necessária para reafirmar a concepção de que o aspecto tecnológico e, principalmente, categorial mais os aproxima do que os isola. Subordinando, portanto, os conceitos de tesauro e de ontologias ao conceito mais amplo de sistemas de organização do conhecimento, reflete sobre algumas de suas implicações teóricas e aplicadas. Tais reflexões são orientadas pelo modo como cada instrumento compreende as relações conceituais associativas. Conclui-se que o aparato tecnológico que se utiliza para a caracterização dos conceitos e de suas relações nas ontologias contribui para a construção de tesauros mais sofisticados do ponto de vista da explicitação dos conceitos e das relações conceituais que visa estabelecer. Em outra direção e de modo complementar, o modelo de análise categorial e facetado empregado na construção de tesauros também contribui para a construção de ontologias semântica e estruturalmente mais densas.

Categories in Charles A. Cutter's Systems of Subject Cataloging and Bibliographical Classification

Categories are considered to be an essential element in the design of many knowledge organization systems (KOS), particularly those following the categorial approach of faceted analysis. Standard narratives of knowledge organization (KO) identify S.R. Ranganthan as the founder of the categorial approach to KO. However, they also acknowledge that elements of a categorial approach to KO can be found in a number of earlier KOSs created in the late 19th and early 20th centuries by such pioneers of KO as Paul Otlet, James D. Brown, and Julius O. Kaiser. This paper seeks to expand the list of precursors to the categorial approach by examining the role of categories in two KOSs created by Charles Ammi Cutter: the system of subject cataloging outlined in the Rules for a Dictionary Catalog (RDC) and the bibliographical classification known as the Expansive Classification (EC). In the RDC, Cutter divided subjects into three categories—concrete individual, concrete general, and abstract general—which were articulated into a classificatory, hierarchical structure that provided the framework for his principle of specific entry. Cutter also established a “significance order” of precedence for these categories, which functioned as a decision tree for selecting the most specific subject headings under which books treating of complex subjects should be entered. In the EC, Cutter divided the classification into schedules for subjects, a list of bibliographical forms, and an auxiliary table of place names (the Local List), with each of these divisions sharply distinguished from the other by notational means; moreover, he established a mechanism for class synthesis, whereby classes in the classification could take the forms Subject–Place or Place–Subject. Both KOSs were designed to allow maximal treatment of concrete, specific classes and so manifest the underlying unity of Cutter’s vision of KO. The pervasive, but implicit and untheorized, use of categorial structures in both the RDC and EC justifies the inclusion of Cutter among the precursors of the categorial approach to KO.

Social Question Answering

Community question answering (CQA) sites use a collaborative paradigm to satisfy complex information needs. Although the task of matching questions to their best answers has been tackled for more than a decade, the social question-answering practice is a complex process. The factors influencing the accuracy of question-answer matching are many and hard to disentangle. We approach the task from an application-oriented perspective, probing the space of several dimensions relevant to this problem: features, algorithms, and topics. We gather under a learning to rank framework the most extensive feature set used in literature to date, including 225 features from five different families. We test the power of such features in predicting the best answer to a question on the largest dataset from Yahoo Answers used for this task so far (40M answers) and provide a faceted analysis of the results along different topical areas and question types. We propose a novel family of distributional semantics measures that most of the time can seamlessly replace widely used linguistic similarity features, being more than one order of magnitude faster to compute and providing greater predictive power. The best feature set reaches an improvement between 11% and 26% in P@1 compared to recent well-established state-of-the-art methods.

Products' Shared Visual Features Do Not Cancel in Consumer Decisions

Consumers' product purchase decisions typically involve comparing competing products' visual features and functional attributes. Companies strive for “product differentiation” (Liu et al., 2013, “Product Family Design Through Ontology-Based Faceted Component Analysis, Selection, and Optimization,” ASME J. Mech. Des., 135(8), p. 081007; Thevenot and Simpson, 2009, “A Product Dissection-Based Methodology to Benchmark Product Family Design Alternatives,” ASME J. Mech. Des., 131(4), p. 041002; Kota et al., 2000, “A Metric for Evaluating Design Commonality in Product Families,” ASME J. Mech. Des., 122(4), pp. 403–410; Orfi et al. 2011, “Harnessing Product Complexity: Step 1—Establishing Product Complexity Dimensions and Indicators,” Eng. Econ., 56(1), pp. 59–79; and Shooter et al. 2005, “Toward a Multi-Agent Information Management Infrastructure for Product Family Planning and Mass Customisation,” Int. J. Mass Customisation, 1(1), pp. 134–155), which makes consumers' product comparisons fruitful but also sometimes challenging. Psychologists who study decision-making have created models of choice such as the cancellation-and-focus (C&F) model. C&F explains and predicts how people decide between choice alternatives with both shared and unique attributes: The shared attributes are “canceled” (ignored) while the unique ones have greater weight in decisions. However, this behavior has only been tested with text descriptions of choice alternatives. To be useful to designers, C&F must be tested with product visuals. This study tests C&F under six conditions defined by: The representation mode (text-only, image-only, and image-with-text) and presentation (sequentially or side-by-side) of choice alternatives. For the products tested, C&F holds for only limited situations. Survey and eye-tracking data suggest different cognitive responses to shared text attributes versus shared image features: In text-only, an attribute's repetition cancels its importance in decisions, while in images, repetition of a feature reinforces its importance. Generally, product differences prove to attract more attention than commonalities, demonstrating product differentiation's importance in forming consumer preferences.

패싯분석 기법을 적용한 방송자료의 내용 구조화에 관한 연구: 시사보도 뉴스 프로그램을 대상으로

패싯분석 기법을 적용한 방송자료의 내용 구조화에 관한 연구: 시사보도 뉴스 프로그램을 대상으로

Product Family Design Through Ontology-Based Faceted Component Analysis, Selection, and Optimization

Product family design (PFD) is a widely adopted strategy for product realization, especially when design requirements are diversified and multi-faceted. Due to ever-changing customer needs and the increasingly complex and integrated product design structure, PFD and its optimization have been concerned more about a rapid and contextual product analysis and variant derivation based on a multi-objective optimization scheme subject to design concerns, which are often cross disciplinary, such as product service, carbon footprint, user experience, esthetics, etc. Existing PFD modeling approaches, which are primarily structured using component attributes and assembly relationships, possess notable limitations in representing complex component and design relationships. Hence, it has restricted comprehensive PFD analysis in an agile and contextual manner. Previously, we have studied and demonstrated the feasibility of using ontology for product family modeling and have suggested a framework of faceted information search and retrieval for product family design. In this paper, several new perspectives towards PFD based on ontology modeling are presented. Firstly, new metrics of ontology-based commonality that better reveal conceptual similarity under various design perspectives are formed. Secondly, faceted concept ranking is proposed as a new ranking approach for ontology-based component search under complex and heterogeneous design requirements. Thirdly, using these ranked results, a platform selection approach that considers a maximum aggregated ranking with a minimal platform modification among various platform choices is researched. From the selected platform and the newly proposed metrics, a modified multi-objective evolutionary algorithm with an embedded feature of configuration incompatibility check is studied and deployed for the optimal selection of components. A case study of PFD using four laptop computer families is reported as our first attempt to showcase how faceted component analysis, selection, and optimization can be accomplished based on the proposed family ontology.

Advancement of Criminal Profiling Methods in Faceted Multidimensional Analysis

AbstractThe current study seeks to advance the faceted multidimensional scaling (termed FMDS) procedure used in much of the investigative psychology research. To this end, recent research on street robbery by Goodwill and colleagues will be utilised to illustrate the effectiveness of a facet scale method for offender profiling. Four FMDS themes of street robbery (Con, Blitz, Confrontation and Snatch) were revealed by the crossing of two underlying axial facets: the offenders' level of violence and interaction with the victim. The facet scale method, utilising offenders' axial facet scores, was compared to previous count, proportional and centroid classification methods in the prediction of offender criminal histories. Utilising logistic regression and receiver operating characteristic analyses, the axial facet scale method was found to significantly outperform the qualitatively based dominant theme classification methods that typically employ angular and radial facets for FMDS interpretation. Implications for the use of axial facet scales within FMDS analysis for offender profiling research are discussed. Copyright © 2012 John Wiley & Sons, Ltd.

Perspectives on crowdsourcing annotations for natural language processing

Crowdsourcing has emerged as a new method for obtaining annotations for training models for machine learning. While many variants of this process exist, they largely differ in their methods of motivating subjects to contribute and the scale of their applications. To date, there has yet to be a study that helps the practitioner to decide what form an annotation application should take to best reach its objectives within the constraints of a project. To fill this gap, we provide a faceted analysis of crowdsourcing from a practitioner’s perspective, and show how our facets apply to existing published crowdsourced annotation applications. We then summarize how the major crowdsourcing genres fill different parts of this multi-dimensional space, which leads to our recommendations on the potential opportunities crowdsourcing offers to future annotation efforts.

Anticipating new media: A faceted classification of material types

The emergence of new media types, many seemingly without counterparts in the non-digital world, challenges the readiness of existing knowledge organization schemes to accommodate them. A knowledge organization scheme based on a faceted analysis of existing classes of bibliographic materials is likely to accommodate new developments better than one based on a list of unanalyzed material types. The faceted analysis undertaken here, in which seven facets are recognized (content, generation of content, recording of content, publication/distribution, physical characteristics, perception/use, and relationships) shows the inadequacy of the traditional view of the bibliographic community of a fundamental distinction between content and carrier; interaction between content and carrier is common and enters into the characterization of material types. The facet analysis is validated by applying it to two new material types, wikis and blogs.

Describing engineering documents with faceted approaches

PurposeThe purpose of this paper is to highlight the difficulty of applying faceted classification outside of library contexts and also to indicate that faceted approaches are poorly expressed to non‐experts.Design/methodology/approachThe faceted approach is being applied outside of its “home” community, with mixed results. The approach is based in part on examination of a broad base of literature and in part on results and reflections on a case study applying faceted notions to “real world” engineering documentation.FindingsThe paper comes across a number of pragmatic and theoretical issues namely: differing interpretations of the facet notion; confusion between faceted analysis and faceted classification; lack of methodological guidance; the use of simplistic domains as exemplars; description verses analysis; facet recognition is unproblematic; and is the process purely top‐down or bottom‐up.Research limitations/implicationsThat facet analysis is not inherently associated with a particular epistemology; that greater guidance about the derivation is needed, that greater realism is needed when teaching faceted approaches.Practical implicationsExperiences of applying faceted classifications are presented that can be drawn upon to guide future work in the area.Originality/valueNo previous work has reflected on the actual empirical experience used to create a faceted description, especially with reference to engineering documents.

Information architecture: IA and RIAs — You know more than you think you do

Information architecture: IA and RIAs — You know more than you think you do

Efficiency parameters estimation in gemstones cut design using artificial neural networks

This paper deals with the problem of estimating cut results for faceted gemstones. The proposed approach applies artificial neural networks for a faceted gemstones analysis tool that could be further developed for incorporation in a computer-aided-design (CAD) context. Basic concepts concerning gemstone processing are introduced and the design of computational tools using neural networks is discussed. The model presented proposes two criteria to assess the efficiency of lapidary designs for rock crystal quartz: brilliance and yield. Closing the article, 62 different lapidary models were used to train and test the neural network tool.

Taxonomy for science and engineering indicators: a reassessment

Science policy researchers and scientists themselves know reflexively that differences among scientific fields matter. However, sets of government-sponsored science and engineering (S&E) indicators are quite general and in most instances do not report differences among fields. We evaluate the current limitations of S&E indicators, identifying particular data needs about scientific fields. We suggest developing a disaggregated, flexible S&E classification. We argue that disaggregating S&E indicators through faceted analysis or webbed or networked databases will enable users to account for specialization, interdisciplinarity and emerging fields, and to adapt the S&E indicators across databases, making indicators more useful for international comparison.

High- [formula omitted] superconductivity as an indirect-exchange phenomenon—a faceted analysis

The phenomenon of high- T C superconductivity has remained a field of puzzling complexity and widely divergent interpretations. Although the number of different materials exhibiting high- T C has increased substantially, and the massive research effort has led to considerably enhanced knowledge, the phenomenon itself is still very far from a generally accepted explanation. In the present paper we review principles and progress we made over the years, following an “indirect-exchange” approach started in 1988, which has appeared to be applicable to the vast spectrum of high- T C superconductors, and which originated out of an earlier theory for low- T C superconductivity such as the elemental metals. The principal theoretical aspects of superconductivity (low- and high- T C ) forming the basis of our approach are reviewed, together with a number of concepts used in the applications. Thereafter, different properties of high- T C superconductors will be treated in this context, elucidating five selected subjects: c-axis layered structures in cuprates and their maximum T C , hole-versus-electron doping in cuprates, alkali-doped C 60 , iodine-intercalated cuprates and compressed alkali metals.

Las categorías o facetas fundamentales: una metodología para el diseño de taxonomías corporativas de sitios web argentinos

El análisis por facetas ha sido revaloado en los últimos años para el diseño de taxonomías corporativas. Con el fin de confirmar su utilidad, analizamos los sitios Web de diferentes organizaciones argentinas: tres bodegas de vino, tres industrias alimenticias, seis clubes de fútbol, cinco asociaciones profesionales, tres facultades universitarias y cinco agencias de gobierno. De las 16 categorías o facetas fundamentales propuestas por el Classification Research Group, las bodegas de vino coincidieron en 13 (81%), las industrias alimenticias en 11 (68%), los clubes de fútbol en 7 (43%), las asociaciones profesionales en 5 (31%), las facultades en 8 (50%) y las agencias de gobierno en 9 (56%). Estas diferencias se deben al hecho de que no todas las categorías son necesarias para todas las organizaciones. Se concluye que el método del análisis por facetas es útil para diseñar taxonomías corporativas y optimizar los sitios Web, de acuerdo con las características particulares de cada organización.

Social Representations of Multiculturalism: A Faceted Analysis

This paper reports a study that examines how Australians are responding to the policy of multiculturalism. The aim of the study was to define different social representations of the policy. Multiple scalogram analysis (MSA) yielded 3 facets of social representations of multiculturalism (active/passive, substantial/minimal, and threat/benefit). Using these facets, subjects were categorized into social representation groups. The results illustrate the methodological utility of using facet theory techniques to study social representations.

A facet-like shell theory

A linear theory for facet-like thin elastic shells is derived where strain/displacement, curvature change/displacement and constitutive relations appear the same as for flat plates. Application of Koiter's arguments shows that the theory is a valid first approximation. The theory is of interest for limiting cases of faceted finite element analysis of smooth shells. Although the final equations of facet-like shell theory do not have quite as simple a form as more conventional equations it is possible that their derivation from equations for flat plates may appeal to engineers. A specialization of the equations is given to circular cylindrical shells where four simple illustrative examples show no essential differences with results from more conventional theory.