We explore and extend the metaphor of "piles" to include computationally-enriched piles, portable regions of automation in Dynapad, a multiscale workspace. We describe these collection-management tools and h...
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We explore and extend the metaphor of "piles" to include computationally-enriched piles, portable regions of automation in Dynapad, a multiscale workspace. We describe these collection-management tools and how their design was informed by observing people organizing collections of personal digital photographs
We introduce a conservative error correcting model, Stacked TBL, that is designed to improve the performance of even high-performing models like boosting, with little risk of accidentally degrading performance. Stacke...
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ISBN:
(纸本)2951740816
We introduce a conservative error correcting model, Stacked TBL, that is designed to improve the performance of even high-performing models like boosting, with little risk of accidentally degrading performance. Stacked TBL is particularly well suited for corpus-based natural language applications involving high-dimensional feature spaces, since it leverages the characteristics of the TBL paradigm that we appropriate. We consider here the task of automatically annonating named entities in text corpora. The task does pose a number of challenges for TBL, to which there are some simple yet effective solutions. We discuss the empirical behavior of Stacked T BL, and consider evidence that despite its simplicity, more complex and time-consuming variants are not generally required.
This paper contains a description of MODeLeR, a Multimedia Object Design Learning Resource. The impetus for the creation of MODeLeR was to provide an authentic learning environment for the study of object-oriented des...
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ISBN:
(纸本)1581137982
This paper contains a description of MODeLeR, a Multimedia Object Design Learning Resource. The impetus for the creation of MODeLeR was to provide an authentic learning environment for the study of object-oriented design to augment intermediate level programming classes. The Resource affords active, collaborative learning experiences in object modeling with the goal of helping students to gain design capabilities in UML and to appreciate the need for design that they often do not perceive since the programs they write are relatively small. Students typically create several different UML diagrams. This paper describes the MODeLeR environment and a pilot study in its use. This paper contains results of both a quantitative study and a qualitative evaluation of the Resource. Copyright 2004 ACM.
As speech interfaces become more prevalent, it is becoming more crucial that they be developed in a way that minimizes cognitive load for users. One major barrier to creating systems that are more human-centered has b...
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As speech interfaces become more prevalent, it is becoming more crucial that they be developed in a way that minimizes cognitive load for users. One major barrier to creating systems that are more human-centered has been the lack of an accepted online methodology for directly evaluating the cognitive resource demands of different systems. The present study extends a classic tool from cognitive psychology, the dual-task paradigm, to speech interface evaluation. Participants follow simple instructions generated by a system, while simultaneously monitoring for a simple visual probe. Performance on the monitoring task is used as a measure of cognitive resource demands;whenever language understanding is more demanding, performance on the monitoring task suffers. In the present study we used this methodology to investigate patterns of reference generation and how they impact human understanding.
We present the first known result for named entity recognition (NER) in realistic large-vocabulary spoken Chinese. We establish this result by applying a maximum entropy model, currently the single best known approach...
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The goal of this panel is to discuss theoretical and methodological approaches that may inform and support the design of temporal aspects of interactive systems. Time Design is an emerging research and development dom...
The goal of this panel is to discuss theoretical and methodological approaches that may inform and support the design of temporal aspects of interactive systems. Time Design is an emerging research and development domain that emphasizes the functional, causal role of time in human control behavior. It draws on a diverse literature on time in cognitive psychology, psychophysics, sociology, computerscience, engineering, human Factors and HCI. Relevant research domains include heuristics and biases in temporal decisions, temporal aspects of human-automation interaction, planning and scheduling, visualisation of temporal information, and the timing of alarms and interruptions.
The present research focuses on the development of an intelligent, computer-based tutoring model for selecting problems in domains where multiple skills are needed to solve a problem and the reasons for errors are not...
The present research focuses on the development of an intelligent, computer-based tutoring model for selecting problems in domains where multiple skills are needed to solve a problem and the reasons for errors are not easily diagnosed. In this paper we report on the development and evaluation of the Mental Rotation Tutors and the intelligent models driving the problem selection engine or “domain reasoner”. The domain reasoner evaluated each student based upon seven different core skills and chose the next problem based upon the student's level of proficiency in all seven areas. Two versions of the tutor were developed. The first versions targeted improving the student's ability to infer what combination of rotations were required to go from one view to another. The second version targeted improving the student's ability to apply a provided set of rotations to an object and report the final orientation. The results of two successive experiments demonstrated that students with low spatial ability derived the most measurable benefit from interacting with the tutors. The tutors also successfully diagnosed students' skill levels and provided problems that were appropriate to each student's current level of proficiency.
In this paper, we propose a new method to generate modular structures. In the method, the number of elements, that is, the number of competitive units is gradually increased. To control a process of module generation,...
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In this paper, we propose a new method to generate modular structures. In the method, the number of elements, that is, the number of competitive units is gradually increased. To control a process of module generation, we introduce two kinds of information, that is, unit and modular information. Unit information represents information content obtained by individual elements in all modules. On the other hand, modular information is information content obtained by each module. We try to increase both types of information simultaneously. We applied our method to two classification problems: random data classification and Web data classification. In both cases, we observed that modular structures were automatically generated.
In this paper, we propose a new computational method for a network-growing method called greedy network-growing [R. Kamimura, et al., (2002)]. We have so far introduced a network-growing algorithm called greedy networ...
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In this paper, we propose a new computational method for a network-growing method called greedy network-growing [R. Kamimura, et al., (2002)]. We have so far introduced a network-growing algorithm called greedy network-growing based upon information theoretic competitive learning. For competitive unit outputs, we have used the inverse of the squares of Euclidean distance between input patterns and connections. The algorithm has extracted very faithful representations of input patterns. However, one problem is that learning is very slow, and sometimes ambiguous final representations are obtained. To remedy these shortcomings, we introduce a new activation function, that is, Gaussian activation functions for competitive units. By changing a parameter for the Gaussian activation functions, we can build a network that does not focus on faithful representations of input patterns, but try to extract the main characteristics of input patterns. Because this method are not concerned with detailed parts of input patterns, learning is significantly accelerated and salient features should be extracted. We applied the method to a road classification problem. Experimental results confirmed that learning was significantly accelerated and salient features could be extracted.
We developed a voice guidance system that increases-mobility for visually impaired people. We use infrared communication technology called Compact Battery-less Information Terminals. The user-friendly information term...
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