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KNOWLEDGE ORGANIZATION KO Contents
Knowl. Org. 34(2007)No.4 KNOWLEDGE ORGANIZATION KO Official Quarterly Journal of the International Society for Knowledge Organization ISSN 0943 – 7444 International Journal devoted to Concept Theory, Classification, Indexing and Knowledge Representation Contents International Society for Knowledge Book Reviews Organization. 11th General Assembly 2008. Agenda ........................... 196 Murtha Baca, Patricia Harping, Elisa Lanzi, Linda McCrea, and Ann Whiteside (eds.). Articles Cataloging Cultural Objects: A Guide to Describing Cultural Work and Their Images. Fulvio Mazzocchi, Melissa Tiberi, Chicago: American Library Association, 2006. Barbara De Santis, and Paolo Plini. 396 p. ISBN 978-0-8389-3564-4 (pbk.) ..........................264 Relational Semantics in Thesauri: Some Remarks at Theoretical and Practical Levels........ 197 Patrick Lambe. Organising Knowledge: Taxonomies, Knowledge and Organisational Guglielmo Trentin. Effectiveness. Oxford: Chandos, 2007. Graphic Tools for Knowledge Representation xix, 277 p. ISBN 978-1-84334-228-1 (hbk.); and Informal Problem-Based Learning 978-1-84334-227-4 (pbk.)................................................266 in Professional Online Communities............................. 215 ISKO News ......................................................................268 Jody L. DeRidder. The Immediate Prospects for the Application Knowledge Organization Literature of Ontologies in Digital Libraries .................................. 227 34 (2007) No.4.................................................................269 -
Using Course Maps to Enhance Navigation of E Learning Environments
AC 2008-2363: USING COURSE MAPS TO ENHANCE NAVIGATION OF E-LEARNING ENVIRONMENTS Susan Miertschin, University of Houston Cheryl Willis, University of Houston Page 13.1333.1 Page © American Society for Engineering Education, 2008 Using Course Maps to Enhance Navigation of E-Learning Environments Abstract A concept map is a graphical representation of relationships among concepts. Willis and Miertschin suggested the use of technology-based concept mapping as an active learning strategy that can enhance learning and thinking skills, particularly among students native to a digital environment [16]. In addition, modern concept mapping software tools enable instructors and students to create visual navigation structures through complex knowledge domains. The authors find value in visual navigation structures for their relevance to organizing and simplifying learning environments and for their appeal to visual learners. This paper investigates different ways to develop digital interactive concept maps (CMaps) to help students navigate complex knowledge domains, such as the content of a course or a curriculum. CMaps can be used to present information in a nonsequential way or in several different ways, depending on the need. Interactivity enables students to easily locate digital information artifacts pertinent to a concept (media files, slide presentations, web pages, etc.) by clicking on links associated with a CMap node representing the course concept or category. A review of recent literature is provided, different software tools are compared, and the authors document their personal experience. This material is based upon work supported by the National Science Foundation under Grant No. 0511672. Complex Learning Environments Information and communications technologies (ICT) have advanced together so that anyone with a computer connected to the Internet is able to create and/or consume varied format information stored in digital files. -
Using Concept Maps to Navigate Complex Learning Environments Susan L
Using Concept Maps to Navigate Complex Learning Environments Susan L. Miertschin Cheryl L. Willis Information and Logistics Technology Information and Logistics Technology University of Houston University of Houston Houston, TX 77204-2083 Houston, TX 77204-4083 (713) 743-4038 (713) 743-4087 [email protected] [email protected] ABSTRACT new, has come of age. A resource-based learning environment A concept map is a graphical representation of relationships (RBLE) is described as “an integrated set of strategies to promote among concepts. Willis and Miertschin suggested the use of student-centered learning in a mass education context, through a technology-based concept mapping as an active learning strategy combination of specially designed learning resources and that can enhance learning and thinking skills, particularly among interactive media and technologies” [5]. What is described here is students native to a digital environment [16]. In addition, modern an environment that increasing numbers of higher education concept mapping software tools enable instructors and students to faculty find they are challenged to create and manage. Typically, a create visual navigation structures through complex knowledge faculty member is armed with their personal content knowledge domains. The authors find value in visual navigation structures for and personal experiences with education and learning; traditional their relevance to organizing and simplifying learning learning material such as a textbook; a learning management environments and for their appeal to visual learners. This paper system (LMS); access to computer technologies for content investigates different ways to develop digital interactive concept creation together with, sometimes, support staff; and the wealth of maps (CMaps) to help students navigate complex knowledge information and tools that are freely and readily available via the domains, such as the content of a course or a curriculum. -
Catalyst Entity Extraction and Disambiguation Study Final Report (U)
UNCLASSIFIED//FOR OFFICIAL USE ONLY (U//FOUO) Catalyst Entity Extraction and Disambiguation Study Final Report (U) Prepared for: IARPA/RDEC Prepared by: Dr. A. Joseph Rockmore/Cyladian Technology Consulting 21 June 2008 UNCLASSIFIED//FOR OFFICIAL USE ONLY UNCLASSIFIED//FOR OFFICIAL USE ONLY (U//FOUO) Executive Summary (U) (U) Catalyst, a component of DDNI/A’s Analytical Transformation Program, will process unstructured, semistructured, and structured data to produce a knowledge base of entities (people, organizations, places, events, …) with associated attributes and the relationships among them. It will perform functions such as entity extraction, relationship extraction, semantic integration, persistent storage of entities, disambiguation, and related functions (these are defined in the body of the report). The objective of this study is to assess the state-of-the-art and state-of-the-practice in these areas. (U) The approach to the study was to survey relevant commercial and open source products, and to identify and describe relevant government systems. (Work in academia was postponed.) Over 230 products and over 20 government systems were identified and analyzed. The conclusions and recommendations are summarized below. (U) In the commercial and open source worlds, there is significant activity to deliver functions needed by Catalyst. By function, the conclusions of the analysis are: • Entity Extraction (14 open source/50 commercial products) – There are many products, with Aerotext, Inxight, and NetOwl best known. There have been no significant breakthroughs in capability or performance recently. Some vendors claim precision and recall over 90%, but with varying scoring definitions. • Relationship Extraction (2/24) – Nearly all are an adjunct to Entity Extraction. -
A Review of Argumentation for the Social Semantic Web
Semantic Web 0 (0) 1 1 IOS Press A Review of Argumentation for the Social Semantic Web Editor(s): Harith Alani, The Open University, UK Solicited review(s): Fouad Zablith, American University of Beirut, Lebanon; Simon Buckingham Shum, The Open University, UK; Iyad Rahwan, Masdar Institute, Abu Dhabi Open review(s): Jodi Schneider a, Tudor Groza a;b, and tention of scholars from fields such as artificial in- Alexandre Passant a telligence [137], communication theory [5], business a Digital Enterprise Research Institute, National management [88] and e-government [107]. At the University of Ireland, Galway, same time, argumentation researchers began establish- fi[email protected] ing the foundations for a World Wide Argument Web b School of ITEE, The University of Queensland, (WWAW) as “a large-scale Web of interconnected ar- Australia, [email protected] guments posted by individuals to express their opin- ions in a structured manner” [138]. Arguments on the Web can be used in decision- making contexts. Decision-making often requires dis- cussion not just of agreement and disagreement, but Abstract. Argumentation represents the study of views and also the principles, reasons, and explanations driving opinions that humans express with the goal of reaching a the choices between particular options. Furthermore, conclusion through logical reasoning. Since the 1950’s, sev- arguments expressed online for one audience may be eral models have been proposed to capture the essence of in- formal argumentation in different settings. With the emer- of interest to other (sometimes far-flung) audiences. gence of the Web, and then the Semantic Web, this model- It can be difficult to re-find the crucial turning points ing shifted towards ontologies, while from the development of an argumentative discussion, even one in which we perspective, we witnessed an important increase in Web 2.0 have participated. -
First Year Ph.D. Report: Argumentation on the Social Semantic Web
First Year Ph.D. Report: Argumentation on the Social Semantic Web Jodi Schneider, Digital Enterprise Research Institute, National University of Ireland, Galway December 11, 2010 Chapter 1 Introduction Limited time, and limited ability to reconcile contradictory information, con- strain human decision making. Acquiring more information does not always directly lead to increased knowledge, in part because information can be con- tradictory. Further, information can involve constraints and dependencies (such as when or to whom it applies), which may not be readily apparent from the information itself. Finally, information can be intentionally misleading, for in- stance in corporate or state espionage, or white collar crime. The Semantic Web offers great potential to improve decision-making by help- ing to collate and reconcile disparate pieces of information, and by enabling a rule-based trust layer with automatic, machine filtering. Further, the easy-to- use Social Web provides a vast store of continually updated information, as well as emergent data about an individual's trusted network. Using the Social Semantic Web, we envision that an individual could get automatic support for decision-making based on their existing, trusted network, effectively augmenting their time and expertise by that of their network. This will require advances in several areas, including argumentation. Argumentation, in our view, is a reconciliation process, leading to improved knowledge based on possibly contradictory pieces of information. Our main contributions this year have been in 5 areas, as detailed in Sec- tion 8: 1. Surveying the state of the art in computational argumentation, includ- ing publishing a paper with the preeminent computational argumentation conference COMMA [122], providing a chart of the interdisciplinarity of argumentation (Figure 4.1), and outlining a full state-of-the-art on Argu- mentation for the Social Semantic Web proposed to the Semantic Web - Interoperability, Usability, Applicability [117], currently in-progress and advanced to their open review process. -
A Review of Argumentation for the Social Semantic Web
Undefined 0 (0) 1 1 IOS Press A Review of Argumentation for the Social Semantic Web Jodi Schneider a, Tudor Groza a,b, and connected arguments posted by individuals to express Alexandre Passant a their opinions in a structured manner” [5]. a Digital Enterprise Research Institute, National Decision-making often requires discussion not just University of Ireland, Galway, of agreement and disagreement, but also the principles, fi[email protected] reasons, and explanations driving the choices between particular options. Furthermore, arguments expressed b School of ITEE, The University of Queensland, online for one audience may be of interest to other Australia, [email protected] (sometimes farflung) audiences. And it can be difficult to re-find the relevant spot of an argumentative discus- sion in which we have participated. Yet on the Web, we cannot subscribe to arguments or issues, nor can we Abstract. Argumentation represents the study of views and search for them. Nor can we summarize the rationale opinions expressed by humans with the goal of reaching a behind a group’s decision, even when the discussion conclusion through logical reasoning. Beginning with the took place entirely in public venues such as mailing 1950’s, several models were proposed to capture the essence lists, IRC channels, and Web forums. of informal argumentation in different settings. With the By providing common languages and principles to emergence of the Semantic Web, this modeling shifted to- model and query information on the Web (such as RDF wards ontologies, while from the development perspective, [6], RDFS [7], OWL [8], SPARQL [9], Linked Data we witnessed an important increase in Web 2.0 human- principles [10], etc.), the Semantic Web [11] is an ap- centered collaborative deliberation tools.