Knowledge Representation with Ontologies: The Present and Future

Recently, we have seen an explosion of interest in ontologies as artifacts to represent human knowledge and as critical components in knowledge management, the semantic Web, business-to-business applications, and several other application areas. Various research communities commonly assume that ontologies are the appropriate modeling structure for representing knowledge. However, little discussion has occurred regarding the actual range of knowledge an ontology can successfully represent

STYLENE : an environment for stylometry and readability research for Dutch

We describe an educational demonstration interface and tools for stylometry (authorship attribution and profiling) and readability research for Dutch. The Stylene system consists of a popularisation interface for learning about stylometric analysis, and of web-based interfaces to software for readability and stylometry research aimed at researchers from the humanities and social sciences who do not want to develop or install such software themselves

Proceedings of the International Conference Sensory Motor Concepts in Language & Cognition

This volume contains selected papers of the 2008 annual conference of the German Association for Social Science Research on Japan (Vereinigung für sozialwissenschaftliche Japanforschung e.V. – VSJF). The academic meeting has addressed the issue of demographic change in Japan in comparison to the social developments of ageing in Germany and other member states of the European Union. The conference was organized by the Institute for Modern Japanese Studies at Heinrich-Heine-University of Duesseldorf and took place at the Mutter Haus in Kaiserswerth (an ancient part of Duesseldorf). Speakers from Germany, England, Japan and the Netherlands presented their papers in four sessions on the topics “Demographic Trends and Social Analysis”, “Family and Welfare Policies”, “Ageing Society and the Organization of Households” and “Demographic Change and the Economy”. Central to all transnational and national studies on demographic change is the question of how societies can be reconstructed and be made adaptive to these changes in order to survive as solidarity communities. The authors of this volume attend to this question by discussing on recent trends of social and economic restructuring and giving insight into new research developments such as in the area of households and housing, family care work, medical insurance, robot technology or the employment sector

A Neuroeducation Description of a Paradigm Shift in Identification, Assessment, and Treatment of Suspected Childhood Apraxia of Speech with Supporting Evidence Through Interview and Artifact Analysis Provided by Speech Language Pathologists and Educators

The purpose of this study was twofold. First, the study explored the pertinent cognitive psychology, neuroscience, and language literature that surrounds the diagnosis and treatment of children with Suspected Childhood Apraxia of Speech (sCAS) with the intent of finding a translational neuroeducation approach to the treatment of sCAS. The results of this literature suggest that the surface problems-phonology, morphology, syntax- are mapped onto a semantic basis. This semantic basis is feature based and people with speech sound disorders are likely to use a visual semantic feature basis. So, the literature supports a shift to a new lens that aligns with the Neurosemantic Language Learning Theory (NLLT) and that could be the basis for intervention in sCAS. Second, while traditional treatment is aimed at the acoustic motor patterns of phonological processes, this study sought to uncover what professionals who have some neuroeducation training say they do when they treat children with sCAS. Interviews were conducted with sixteen Speech Language Pathologists (SLPs) and Educators currently using principles of neuroeducation to treat children with sCAS in order to uncover the methods that they report having used in interventions with this population. It was found that both SLPs and educators who use methods of assessment and intervention based on the NLLT reported positive outcomes for intelligibility and language function. The respondents also reported using intervention methods that align with the NLLT to a high degree. The interviews, along with artifacts provided by interview participants, served as confirmatory evidence to the findings from the literature review by demonstrating the reported change in children over time as a result of the intervention. Additional themes were found around definitions of sCAS, intervention methods and alignment of diagnostic criterion, philosophy and intervention methods among interviewees

CLiFF Notes: Research in the Language, Information and Computation Laboratory of the University of Pennsylvania

One concern of the Computer Graphics Research Lab is in simulating human task behavior and understanding why the visualization of the appearance, capabilities and performance of humans is so challenging. Our research has produced a system, called Jack, for the definition, manipulation, animation and human factors analysis of simulated human figures. Jack permits the envisionment of human motion by interactive specification and simultaneous execution of multiple constraints, and is sensitive to such issues as body shape and size, linkage, and plausible motions. Enhanced control is provided by natural behaviors such as looking, reaching, balancing, lifting, stepping, walking, grasping, and so on. Although intended for highly interactive applications, Jack is a foundation for other research. The very ubiquitousness of other people in our lives poses a tantalizing challenge to the computational modeler: people are at once the most common object around us, and yet the most structurally complex. Their everyday movements are amazingly fluid, yet demanding to reproduce, with actions driven not just mechanically by muscles and bones but also cognitively by beliefs and intentions. Our motor systems manage to learn how to make us move without leaving us the burden or pleasure of knowing how we did it. Likewise we learn how to describe the actions and behaviors of others without consciously struggling with the processes of perception, recognition, and language. Present technology lets us approach human appearance and motion through computer graphics modeling and three dimensional animation, but there is considerable distance to go before purely synthesized figures trick our senses. We seek to build computational models of human like figures which manifest animacy and convincing behavior. Towards this end, we: Create an interactive computer graphics human model; Endow it with reasonable biomechanical properties; Provide it with human like behaviors; Use this simulated figure as an agent to effect changes in its world; Describe and guide its tasks through natural language instructions. There are presently no perfect solutions to any of these problems; ultimately, however, we should be able to give our surrogate human directions that, in conjunction with suitable symbolic reasoning processes, make it appear to behave in a natural, appropriate, and intelligent fashion. Compromises will be essential, due to limits in computation, throughput of display hardware, and demands of real-time interaction, but our algorithms aim to balance the physical device constraints with carefully crafted models, general solutions, and thoughtful organization. The Jack software is built on Silicon Graphics Iris 4D workstations because those systems have 3-D graphics features that greatly aid the process of interacting with highly articulated figures such as the human body. Of course, graphics capabilities themselves do not make a usable system. Our research has therefore focused on software to make the manipulation of a simulated human figure easy for a rather specific user population: human factors design engineers or ergonomics analysts involved in visualizing and assessing human motor performance, fit, reach, view, and other physical tasks in a workplace environment. The software also happens to be quite usable by others, including graduate students and animators. The point, however, is that program design has tried to take into account a wide variety of physical problem oriented tasks, rather than just offer a computer graphics and animation tool for the already computer sophisticated or skilled animator. As an alternative to interactive specification, a simulation system allows a convenient temporal and spatial parallel programming language for behaviors. The Graphics Lab is working with the Natural Language Group to explore the possibility of using natural language instructions, such as those found in assembly or maintenance manuals, to drive the behavior of our animated human agents. (See the CLiFF note entry for the AnimNL group for details.) Even though Jack is under continual development, it has nonetheless already proved to be a substantial computational tool in analyzing human abilities in physical workplaces. It is being applied to actual problems involving space vehicle inhabitants, helicopter pilots, maintenance technicians, foot soldiers, and tractor drivers. This broad range of applications is precisely the target we intended to reach. The general capabilities embedded in Jack attempt to mirror certain aspects of human performance, rather than the specific requirements of the corresponding workplace. We view the Jack system as the basis of a virtual animated agent that can carry out tasks and instructions in a simulated 3D environment. While we have not yet fooled anyone into believing that the Jack figure is real , its behaviors are becoming more reasonable and its repertoire of actions more extensive. When interactive control becomes more labor intensive than natural language instructional control, we will have reached a significant milestone toward an intelligent agent

Research in the Language, Information and Computation Laboratory of the University of Pennsylvania

This report takes its name from the Computational Linguistics Feedback Forum (CLiFF), an informal discussion group for students and faculty. However the scope of the research covered in this report is broader than the title might suggest; this is the yearly report of the LINC Lab, the Language, Information and Computation Laboratory of the University of Pennsylvania. It may at first be hard to see the threads that bind together the work presented here, work by faculty, graduate students and postdocs in the Computer Science and Linguistics Departments, and the Institute for Research in Cognitive Science. It includes prototypical Natural Language fields such as: Combinatorial Categorial Grammars, Tree Adjoining Grammars, syntactic parsing and the syntax-semantics interface; but it extends to statistical methods, plan inference, instruction understanding, intonation, causal reasoning, free word order languages, geometric reasoning, medical informatics, connectionism, and language acquisition. Naturally, this introduction cannot spell out all the connections between these abstracts; we invite you to explore them on your own. In fact, with this issue it’s easier than ever to do so: this document is accessible on the “information superhighway”. Just call up http://www.cis.upenn.edu/~cliff-group/94/cliffnotes.html In addition, you can find many of the papers referenced in the CLiFF Notes on the net. Most can be obtained by following links from the authors’ abstracts in the web version of this report. The abstracts describe the researchers’ many areas of investigation, explain their shared concerns, and present some interesting work in Cognitive Science. We hope its new online format makes the CLiFF Notes a more useful and interesting guide to Computational Linguistics activity at Penn

CLiFF Notes: Research in the Language Information and Computation Laboratory of The University of Pennsylvania

This report takes its name from the Computational Linguistics Feedback Forum (CLIFF), an informal discussion group for students and faculty. However the scope of the research covered in this report is broader than the title might suggest; this is the yearly report of the LINC Lab, the Language, Information and Computation Laboratory of the University of Pennsylvania. It may at first be hard to see the threads that bind together the work presented here, work by faculty, graduate students and postdocs in the Computer Science, Psychology, and Linguistics Departments, and the Institute for Research in Cognitive Science. It includes prototypical Natural Language fields such as: Combinatorial Categorial Grammars, Tree Adjoining Grammars, syntactic parsing and the syntax-semantics interface; but it extends to statistical methods, plan inference, instruction understanding, intonation, causal reasoning, free word order languages, geometric reasoning, medical informatics, connectionism, and language acquisition. With 48 individual contributors and six projects represented, this is the largest LINC Lab collection to date, and the most diverse