This work describes a software program named LEO, a Learning Environment Organizer that provides information and knowledge visualization capabilities to students and instructors. LEO provides a Concept Map-like interf...
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Knowledge-based recommender systems comprise one category of user-modeling system that can draw inferences from user models. This brief paper contains a global description of a multi-faceted, educational, knowledge-ba...
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Dynapad is a development environment designed to support research prototyping of multiscale workspaces. In this paper we describe applications designed to facilitate visual access to and spatial organization of digita...
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Dynapad is a development environment designed to support research prototyping of multiscale workspaces. In this paper we describe applications designed to facilitate visual access to and spatial organization of digital photo collections and personal libraries of PDF documents. The research objective is to explore a generalization of the notion of a "pile" as a foundation for a versatile suite of tools to provide unobtrusive assistance for organizing collections and other sensemaking activities. We detail the architecture underlying the applications, explain how it supports diverse functionality and interaction styles, and abstract a set of principles for designing spatial tools.
A conversational robot can take on different personas that have more or less common ground with users. With more common ground, communication is more efficient. We studied this process experimentally. A "male&quo...
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Semantic relations between text concepts denote the core elements of lexical semantics. This paper presents a model for the automatic detection of INTENTION semantic relation. Our approach first identifies the syntact...
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作者：
Wu, DekaiDepartment of Computer Science
HKUST Human Language Technology Center Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong
We offer a perspective on EBMT from a statistical MT standpoint, by developing a three-dimensional MT model space based on three pairs of definitions: (1) logical versus statistical MT, (2) schema-based versus example...
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With the advances of robotics, computerscience, and other related areas, home service robots attract much attention from both academia and industry. Home service robots present interesting technical challenges to the...
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With the advances of robotics, computerscience, and other related areas, home service robots attract much attention from both academia and industry. Home service robots present interesting technical challenges to the community in that they have a wide range of potential applications, such as home security, patient caring, cleaning, etc., and that the services provided by the robots in each application area are being defined as markets are formed and, therefore, they change constantly. Without architectural considerations to address these challenges, robot manufacturers often focus on developing technical components (e.g., vision recognizer, speech processor, and actuator) and then attempt to develop service robots by integrating these components. When prototypes are developed for a new application, or when services are added, modified, or removed from existing robots, unexpected, undesirable, and often dangerous side-effects, which are known as feature interaction problem, happen frequently. Reengineering of such robots can make a serious impact in delivery time and development cost. In this paper, we present our experience of re-engineering a prototype of a home service robot developed by Samsung Advanced Institute of Technology. First, we designed a modular and hierarchical software architecture that makes interaction among the components visible. With the visibility of interactions, we could assign functional responsibilities to each component clearly. Then, we re-engineered existing codes to conform to the new architecture using a reactive language Esterel. As a result, we could detect and solve feature interaction problems and alleviate the difficulty of adding or updating components. Copyright 2005 ACM.
We here propose a training algorithm for multi-layered neural-network (NN) classifiers that improves the generalization ability, the ability to classify previously unseen patterns. A correlation term was added to the ...
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The subject described herein is a novel method for model- ing and visualizing the deformation of a rheological object. In the method, we propose a dynamic adaptive triangle mesh of which the vertex link is a rheology ...
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The subject described herein is a novel method for model- ing and visualizing the deformation of a rheological object. In the method, we propose a dynamic adaptive triangle mesh of which the vertex link is a rheology element con- sisting of the group of a viscous element joining to two viscous and elastic elements associated parallelly. Based on the physical and geometrical properties of a rheological object, the mesh conforms dynamically to the deforma- tion. We apply the dynamic adaptive triangle mesh for the problems of visualizing force interactions of a deforma- tion process.
Software and product designers use card sorting to understand item groups and relationships. In the usability community, a common method of formal statistical analysis for open card sort data is hierarchical cluster a...
Software and product designers use card sorting to understand item groups and relationships. In the usability community, a common method of formal statistical analysis for open card sort data is hierarchical cluster analysis, which results in a tree of the items sorted into distinct, nested clusters. Hierarchical cluster analysis is appropriate for highly structured settings, like software menus. However, many situations call for softer clusters, such as designing websites where multiple pages link to the same target page. Factor analysis summarizes the categories created in card sorts and generates clusters that can overlap. This paper explains how to prepare card sort data for statistical analysis, describes the results of factor analysis and how to interpret them, and discusses when hierarchical cluster analysis and factor analysis are appropriate.
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