49 research outputs found
Automatic taxonomy evaluation
This thesis would not be made possible without the generous support of IATA.Les taxonomies sont une représentation essentielle des connaissances, jouant un rÎle central dans de nombreuses applications riches en connaissances. Malgré cela, leur construction est laborieuse que ce soit manuellement ou automatiquement, et l'évaluation quantitative de taxonomies est un sujet négligé. Lorsque les chercheurs se concentrent sur la construction d'une taxonomie à partir de grands corpus non structurés, l'évaluation est faite souvent manuellement, ce qui implique des biais et se traduit souvent par une reproductibilité limitée. Les entreprises qui souhaitent améliorer leur taxonomie manquent souvent d'étalon ou de référence, une sorte de taxonomie bien optimisée pouvant service de référence.
Par conséquent, des connaissances et des efforts spécialisés sont nécessaires pour évaluer une taxonomie.
Dans ce travail, nous soutenons que l'évaluation d'une taxonomie effectuée automatiquement et de maniÚre reproductible est aussi importante que la génération automatique de telles taxonomies. Nous proposons deux nouvelles méthodes d'évaluation qui produisent des scores moins biaisés: un modÚle de classification de la taxonomie extraite d'un corpus étiqueté, et un modÚle de langue non supervisé qui sert de source de connaissances pour évaluer les relations hyperonymiques. Nous constatons que nos substituts d'évaluation corrÚlent avec les jugements humains et que les modÚles de langue pourraient imiter les experts humains dans les tùches riches en connaissances.Taxonomies are an essential knowledge representation and play an important role in classification and numerous knowledge-rich applications, yet quantitative taxonomy evaluation remains to be overlooked and left much to be desired. While studies focus on automatic taxonomy construction (ATC) for extracting meaningful structures and semantics from large corpora, their evaluation is usually manual and subject to bias and low reproducibility. Companies wishing to improve their domain-focused taxonomies also suffer from lacking ground-truths. In fact, manual taxonomy evaluation requires substantial labour and expert knowledge.
As a result, we argue in this thesis that automatic taxonomy evaluation (ATE) is just as important as taxonomy construction. We propose two novel taxonomy evaluation methods for automatic taxonomy scoring, leveraging supervised classification for labelled corpora and unsupervised language modelling as a knowledge source for unlabelled data. We show that our evaluation proxies can exert similar effects and correlate well with human judgments and that language models can imitate human experts on knowledge-rich tasks
The robust optimization of non-linear requirements models
Solutions to non-linear requirements engineering problems may be brittle ; i.e. small changes may dramatically alter solution effectiveness. Hence, it is not enough to just generate solutions to requirements problems---we must also assess solution robustness. This thesis aims to address two concerns: (a) Is demonstrating robustness a time consuming task? and (b) Is it necessary that solution quality be traded off against solution robustness?;Using a Bayesian ranking heuristic, the KEYS2 algorithm fixes a small number of important variables, rapidly pushing the search into a stable, optimal plateau. By design, KEYS2 generates decision ordering diagrams (in time experimentally shown to be O(N2)). Once generated, these diagrams can confirm solution robustness in linear time. When assessed in terms of reducing inference times, increasing solution quality, and decreasing the variance of the generated solution, KEYS2 out-performs other search algorithms (simulated annealing, A*, MaxWalkSat)
Exploring how entrepreneurs make decisions on the growth of their business: A cognitive perspective
The purpose of this study was to explore how entrepreneurs, who are past the start-up stage of business, evaluate and make decisions on growth opportunities. Small business growth is a complex, dynamic and episodic phenomenon and prior research on firm growth has emphasised cross-sectional approaches, rather than view growth as a dynamic process over time. Understanding small business entrepreneursâ cognition and behaviours when making opportunity-related decisions will show how growth decisions are made. It is still unclear what cognitive styles and knowledge structures entrepreneurs use to process and frame information for opportunity-related decision-making. A closer look at opportunity evaluation, decision-making and entrepreneurial cognition revealed fragmentation, research gaps and areas for future research recommended by key scholars. As a consequence of this, an integrated process approach was taken using these three research streams. Specifically, a cognitive style lens, as a complex construct with multiple dimensions was used for viewing opportunity-related decisions, an approach missing from the opportunity evaluation literature. Additionally, the study was conceptually underpinned by dual process theory, the cognitive experiential self-theory or CEST. A longitudinal, concurrent triangulation design was used to explore the decision-making process over five time points in a two-year period. A mixed methods approach supported the pragmatic paradigm for an exploratory study. A multiple-case strategy used a sample of 11 small manufacturing entrepreneurs, from novice to mature, with 3-30 yearsâ experience as owner-manager. Data was collected at each time point using semi-structured interviews and two style assessments, the CoSI and REI. Quantitative data was analysed using descriptive statistics and thematic analysis for the qualitative data. Combining interviews and psychometric questionnaires for triangulation produced robust findings. Data was used to construct cognitive maps and cognitive complexity for insight. Findings showed entrepreneurs were high on more than one style and switched between styles according to context, demonstrating styles were orthogonal. A unique finding was a synthesised, versatile style observed as a âmirror effectâ between the analytical and intuitive styles. Novices developed a more intuitive style over time, contingent with experience. A developing link in the novicesâ mental structures showed how past experience increased cognitive complexity and connectivity. A further unique finding showed the central concept âThinks it throughâ in the decision process as a structural conduit or 'Hub' for both analytical and intuitive processing. Analysis suggested that cognitive complexity mediated the relationship between creative and experiential information styles and successful opportunity-related decision-making effectiveness. These unique findings show opportunity-related decisions as a dynamic, time-based process. The time-based model provided a framework for future opportunity evaluation research as a contribution to theory. Likewise, a dual process and information processing perspective has offered an alternative structure for examining opportunity evaluation. Finally, a teaching model was developed to improve metacognitive thinking and connectivity for decision-making effectiveness as a contribution to practice
Collective intelligence: creating a prosperous world at peace
XXXII, 612 p. ; 24 cmLibro ElectrĂłnicoEn este documento se plantea un tema de interes general mas como lo es especificamente el tema de la evolucion de la sociedad en materia de industria y crecimiento de las actividades humanas en el aspecto de desarrollo de la creatividad enfocada a los mercadosedited by Mark Tovey ; foreword by Yochai Benkler (re-mixed by Hassan Masum) ; prefaces by Thomas Malone, Tom Atlee & Pierre Levy ; afterword by Paul Martin & Thomas Homer-Dixon.The era of collective intelligence has begun in earnest. While others have written about the wisdom of crowds, an army of Davids, and smart mobs, this collection of essays for the first time brings together fifty-five pioneers in the emerging discipline of collective intelligence. They provide a base of tools for connecting people, producing high-functioning teams, collaborating at multiple scales, and encouraging effective peer-production. Emerging models are explored for digital deliberative democracy, self-governance, legislative transparency, true-cost accounting, and the ethical use of open sources and methods. Collective Intelligence is the first of a series of six books, which will also include volumes on Peace Intelligence, Commercial Intelligence, Gift Intelligence, Cultural Intelligence, and Global Intelligence.Table of Contents
Dedication i
Publisherâs Preface iii
Foreword by Yochai Benkler Remix Hassan Masum xi
The Wealth of Networks: Highlights remixed
Editorâs Preface xxi
Table of Contents xxv
A What is collective intelligence and what will we do 1
about it? (Thomas W. Malone, MIT Center for
Collective Intelligence)
B Co-Intelligence, collective intelligence, and conscious 5
evolution (Tom Atlee, Co-Intelligence Institute)
C A metalanguage for computer augmented collective 15
intelligence (Prof. Pierre LĂ©vy, Canada Research
Chair in Collective Intelligence, FRSC)
I INDIVIDUALS & GROUPS I-01 Foresight I-01-01 Safety Glass (Karl Schroeder, science fiction author 23
and foresight consultant)
I-01-02 2007 State of the Future (Jerome C. Glenn & 29
Theodore J. Gordon, United Nations Millennium
Project)
I-02 Dialogue & Deliberation I-02-01 Thinking together without ego: Collective intelligence 39
as an evolutionary catalyst (Craig Hamilton and Claire
Zammit, Collective-Intelligence.US)
I-02-02 The World Café: Awakening collective intelligence 47
and committed action (Juanita Brown, David Isaacs
and the World Café Community)
I-02-03 Collective intelligence and the emergence of 55
wholeness (Peggy Holman, Nexus for Change, The
Change Handbook)
I-02-04 Knowledge creation in collective intelligence (Bruce 65
LaDuke, Fortune 500, HyperAdvance.com)
I-02-05 The Circle Organization: Structuring for collective 75
wisdom (Jim Rough, Dynamic Facilitation & The
Center for Wise Democracy)
I-03 Civic Intelligence I-03-01 Civic intelligence and the public sphere (Douglas 83
Schuler, Evergreen State College, Public Sphere
Project)
I-03-02 Civic intelligence and the security of the homeland 95
(John Kesler with Carole and David Schwinn,
IngeniusOnline)
I-03-03 Creating a Smart Nation (Robert Steele, OSS.Net) 107
I-03-04 University 2.0: Informing our collective intelligence 131
(Nancy Glock-Grueneich, HIGHEREdge.org)
I-03-05 Producing communities of communications and 145
foreknowledge (Jason âJZâ Liszkiewicz,
Reconfigure.org)
I-03-06 Global Vitality Report 2025: Learning to transform I-04 Electronic Communities & Distributed Cognition I-04-01 Attentional capital and the ecology of online social 163
conflict and think together effectively (Peter+Trudy networks (Derek Lomas, Social Movement Lab,
Johnson-Lenz, Johnson-Lenz.com ) UCSD)
I-04-02 A slice of life in my virtual community (Howard 173
Rheingold, Whole Earth Review, Author & Educator)
I-04-03 Shared imagination (Dr. Douglas C. Engelbart, 197
Bootstrap)
I-05 Privacy & Openness I-05-01 Weâre all swimming in media: End-users must be able 201
to keep secrets (Mitch Ratcliffe, BuzzLogic &
Tetriad)
I-05-02 Working openly (Lion Kimbro, Programmer and 205
Activist)
I-06 Integral Approaches & Global Contexts I-06-01 Meta-intelligence for analyses, decisions, policy, and 213
action: The Integral Process for working on complex
issues (Sara Nora Ross, Ph.D. ARINA & Integral
Review)
I-06-02 Collective intelligence: From pyramidal to global 225
(Jean-Francois Noubel, The Transitioner)
I-06-03 Cultivating collective intelligence: A core leadership 235
competence in a complex world (George PĂłr, Fellow
at Universiteit van Amsterdam)
II LARGE-SCALE COLLABORATION II-01 Altruism, Group IQ, and Adaptation II-01-01 Empowering individuals towards collective online 245
production (Keith Hopper, KeithHopper.com)
II-01-02 Whoâs smarter: chimps, baboons or bacteria? The 251
power of Group IQ (Howard Bloom, author)
II-01-03 A collectively generated model of the world (Marko 261
A. Rodriguez, Los Alamos National Laboratory)
II-02 Crowd Wisdom and Cognitive Bias II-02-01 Science of CI: Resources for change (Norman L 265
Johnson, Chief Scientist at Referentia Systems, former
LANL)
II-02-02 Collectively intelligent systems (Jennifer H. Watkins, 275
Los Alamos National Laboratory)
II-02-03 A contrarian view (Jaron Lanier, scholar-in-residence, 279
CET, UC Berkeley & Discover Magazine)
II-03 Semantic Structures & The Semantic Web II-03-01 Information Economy Meta Language (Interview with 283
Professor Pierre LĂ©vy, by George PĂłr)
II-03-02 Harnessing the collective intelligence of the World- 293
Wide Web (Nova Spivack, RadarNetworks, Web 3.0)
II-03-03 The emergence of a global brain (Francis Heylighen, 305
Free University of Brussels)
II-04 Information Networks II-04-01 Networking and mobilizing collective intelligence (G.
Parker Rossman, Future of Learning Pioneer)
II-04-02 Toward high-performance organizations: A strategic 333
role for Groupware (Douglas C. Engelbart, Bootstrap)
II-04-03 Search panacea or ploy: Can collective intelligence 375
improve findability? (Stephen E. Arnold, Arnold IT,
Inc.)
II-05 Global Games, Local Economies, & WISER II-05-01 World Brain as EarthGame (Robert Steele and many 389
others, Earth Intelligence Network)
II-05-02 The Interra Project (Jon Ramer and many others) 399
II-05-03 From corporate responsibility to Backstory 409
Management (Alex Steffen, Executive Editor,
Worldchanging.com)
II-05-04 World Index of Environmental & Social 413
Responsibility (WISER)
By the Natural Capital Institute
II-06 Peer-Production & Open Source Hardware II-06-01 The Makersâ Bill of Rights (Jalopy, Torrone, and Hill) 421
II-06-02 3D Printing and open source design (James Duncan, 423
VP of Technology at Marketingisland)
II-06-03 REBEARTHTM: 425
II-07 Free Wireless, Open Spectrum, and Peer-to-Peer II-07-01 MontrĂ©al Community Wi-Fi (Ăle Sans Fil) (Interview 433
with Michael Lenczner by Mark Tovey)
II-07-02 The power of the peer-to-peer future (Jock Gill, 441
Founder, Penfield Gill Inc.)
Growing a world 6.6 billion people
would want to live in (Marc Stamos, B-Comm, LL.B)
II-07-03 Open spectrum (David Weinberger)
II-08 Mass Collaboration & Large-Scale Argumentation II-08-01 Mass collaboration, open source, and social 455
entrepreneurship (Mark Tovey, Advanced Cognitive
Engineering Lab, Institute of Cognitive Science,
Carleton University)
II-08-02 Interview with Thomas Homer-Dixon (Hassan 467
Masum, McLaughlin-Rotman Center for Global
Health)
II-08-03 Achieving collective intelligence via large-scale
argumentation (Mark Klein, MIT Center for
Collective Intelligence)
II-08-04 Scaling up open problem solving (Hassan Masum & 485
Mark Tovey)
D Afterword: The Internet and the revitalization of 495
democracy (The Rt. Honourable Paul Martin &
Thomas Homer-Dixon)
E Epilogue by Tom Atlee 513
F Three Lists 515
1. Strategic Reading Categories
2. Synopsis of the New Progressives
3. Fifty-Two Questions that Matter
G Glossary 519
H Index 52
2010 Creating/Making Forum
The 2010 Creating/Making Forum was held in conjunction with the Fred Jones Jr. Museum of Artâs âBruce Goff: A Creative Mindâ exhibition and featured peer-reviewed paper sessions titled: Design Education and Tacit Knowledge; Digital Creating and Making; Community Engagement; The Found Object; Innovation, Interdisciplinarity and the Environment; Interpreting Architecture; and History Reframed, as well as a juried poster session. Keynote speakers at the 2010 Forum were Sheila Kennedy, Craig Borum, and Marlon Blackwell.A special thanks to Angela M. Person for editing these proceedings.N
Exploiting Spatio-Temporal Coherence for Video Object Detection in Robotics
This paper proposes a method to enhance video object detection for indoor environments in robotics. Concretely, it exploits knowledge about the camera motion between frames to propagate previously detected objects to successive frames. The proposal is rooted in the concepts of planar homography to propose regions of interest where to find objects, and recursive Bayesian filtering to integrate observations over time. The proposal is evaluated on six virtual, indoor environments, accounting for the detection of nine object classes over a total of ⌠7k frames. Results show that our proposal improves the recall and the F1-score by a factor of 1.41 and 1.27, respectively, as well as it achieves a significant reduction of the object categorization entropy (58.8%) when compared to a two-stage video object detection method used as baseline, at the cost of small time overheads (120 ms) and precision loss (0.92).</p