28021583
The Human Use Regulatory Affairs Advisor: A Web Based Information Retrieval System with a User-Friendly Interface Design
206601195
The Role of Discourse Structure and Response Time in Multimodal Communication
In an ongoing project on multimodal communication in humans and agents [1], we investigate the interaction between two linguistic modalities (prosody and dialog structure) and two non-linguistic modalities (eye gaze and facial expressions). The goal is to gain a better understanding of the use of communicative channels in discourse and can subsequently aid the development of more effective animated conversational agents. We studied conversations between humans involved in the Map Task scenario whereby an Instruction Giver (IG) navigates an Instruction Follower (IF) from a starting point to an end point on a map [2].
11533272
The Impact of Conversational Navigational Guides on the Learning, Use, and Perceptions of Users of a Web Site
Knowledge management systems will presumably benefit from intelligent interfaces, including those with animated conversational agents. One of the functions of an animated conversational agent is to serve as a navigational guide that nudges the user how to use the interface in a productive way. This is a different function from delivering the content of the material. We conducted a study on college students who used a web facility in one of four navigational guide conditions: Full Guide (speech and face), Voice Guide, Print Guide, and No Guide. The web site was the Human Use Regulatory Affairs Advisor (HURAA), a web-based facility that provides help and training on research ethics, based on documents and regulations in United States Federal agencies. The college students used HURAA to complete a number of learning modules and document retrieval tasks. There was no significant facilitation of any of the guides on several measures of learning and performance, compared with the No Guide condition. This result suggests that the potential benefits of conversational guides are not ubiquitous, but they may save time and increase learning under specific conditions that are yet to be isolated.
12292456
The Embodiment of Amodal Symbolic Knowledge Representations
Latent semantic analysis (LSA) is a statistical, corpus-based technique of representing knowledge. It has been successfully used in a variety of applications including intelligent tutoring systems, essay grading and coherence metrics. From its very introduction LSA has been claimed to simulate aspects of human knowledge representation. This amodal symbolic view immediately resulted in a rebuttal from cognitive scientists who argued that LSA can never come close to human knowledge representation, because it lacks embodiment into perceptual experience or action as in human cognition. The ultimate test to determine the embodiment of LSA is to evaluate how well it operates on typical embodied dimensions like spatiality and temporality. The results of such a test would have an impact on theories of meaning and knowledge representation, and would help us in the development of natural language processing modules for applications that use these embodied dimensions. Six Multidimensional Scaling representations are derived from the LSA cosines between spatial and temporal words. Results show that by combining LSA with MDS previously hidden spatial and temporal relations can now be revealed.
6260724
Finding an optimal path without growing the tree
For problems on computing an optimal path as well as its length in a certain setting, the "standard" approach for finding an actual optimal path is by building (or "growing") a single-source optimal path tree. In this paper, we study a class of optimal path problems with the following phenomenon: The space complexity of the algorithms for reporting the lengths of single-source optimal paths for these problems is asymptotically smaller than the space complexity of the "standard" tree-growing algorithms for finding actual optimal paths. We present a general and efficient algorithmic paradigm for finding an actual optimal path for such problems without having to grow a single-source optimal path tree. Our paradigm is based on the "marriage-before-conquer" strategy, the prune-and-search technique, and a new data structure called clipped trees. The paradigm enables us to compute an actual path for a number of optimal path problems and dynamic programming problems in computational geometry, graph theory, and combinatorial optimization. Our algorithmic solutions improve the space bounds (in certain cases, the time bounds as well) of the previously best known algorithms, and settle some open problems. Our techniques are likely to be applicable to other problems.
16662300
A comparative investigation on subspace dimension determination
It is well-known that constrained Hebbian self-organization on multiple linear neural units leads to the same k-dimensional subspace spanned by the first k principal components. Not only the batch PCA algorithm has been widely applied in various fields since 1930s, but also a variety of adaptive algorithms have been proposed in the past two decades. However, most studies assume a known dimension k or determine it heuristically, though there exist a number of model selection criteria in the literature of statistics. Recently, criteria have also been obtained under the framework of Bayesian Ying-Yang (BYY) harmony learning. This paper further investigates the BYY criteria in comparison with existing typical criteria, including Akaike's information criterion (AIC), the consistent Akaike's information criterion (CAIC), the Bayesian inference criterion (BIC), and the cross-validation (CV) criterion. This comparative study is made via experiments not only on simulated data sets of different sample sizes, noise variances, data space dimensions, and subspace dimensions, but also on two real data sets from air pollution problem and sport track records, respectively. Experiments have shown that BIC outperforms AIC, CAIC, and CV while the BYY criteria are either comparable with or better than BIC. Therefore, BYY harmony learning is a more preferred tool for subspace dimension determination by further considering that the appropriate subspace dimension k can be automatically determined during implementing BYY harmony learning for the principal subspace while the selection of subspace dimension k by BIC, AIC, CAIC, and CV has to be made at the second stage based on a set of candidate subspaces with different dimensions which have to be obtained at the first stage of learning.
18070841
Ontology-Based Scalable and Portable Information Extraction System to Extract Biological Knowledge from Huge Collection of Biomedical Web Documents
Automated discovery and extraction of biological knowledge from biomedical web documents has become essential because of the enormous amount of biomedical literature published each year. In this paper we present an ontology-based scalable and portable information extraction system to automatically extract biological knowledge from huge collection of online biomedical web documents. Our method integrates ontology-based semantic tagging, information extraction and data mining together, automatically learns the patterns based on a few user seed tuples, and then extract new tuples from the biomedical web documents based on the discovered patterns. A novel system SPIE (Scalable and Portable Information Extraction) is implemented and tested on the PuBMed to find the chromatin protein-protein interaction and the experimental results indicate our approach is very effective in extracting biological knowledge from huge collection of biomedical web documents.
40136335
On Rearrangeability of Multirate Clos Networks
Chung and Ross [SIAM J. Comput., 20 (1991), pp. 726--736] conjectured that the multirate three-stage Clos network C(n,2n-1,r) is rearrangeable in the general discrete bandwidth case; i.e., each connection has a weight chosen from a given finite set {p1, p2,. . .,pk} where $1 \geq p_1 > p_2 > \cdots > p_k > 0$ and pi is an integer multiple of pi, denoted by $p_k \mid p_i$, for $1 \leq i \leq k-1$. In this paper, we prove that multirate three-stage Clos network C(n,2n-1,r) is rearrangeable when each connection has a weight chosen from a given finite set {p1, p2,. . .,pk} where $1 \geq p_1 > p_2 > \cdots > p_{h} > 1/2 \geq p_{h+1} > \cdots > p_k > 0$ and ph+2 | ph+1,ph+3 |ph+2,. . . ,pk | ph+1. We also prove that C(n,2n-1,r) is two-rate rearrangeable and $C(n, \lceil \frac{7n}{3} \rceil, r)$ is three-rate rearrangeable.
12307619
The use of visual search for knowledge gathering in image decision support
This paper presents a new method of knowledge gathering for decision support in image understanding based on information extracted from the dynamics of saccadic eye movements. The framework involves the construction of a generic image feature extraction library, from which the feature extractors that are most relevant to the visual assessment by domain experts are determined automatically through factor analysis. The dynamics of the visual search are analyzed by using the Markov model for providing training information to novices on how and where to look for image features. The validity of the framework has been evaluated in a clinical scenario whereby the pulmonary vascular distribution on Computed Tomography images was assessed by experienced radiologists as a potential indicator of heart failure. The performance of the system has been demonstrated by training four novices to follow the visual assessment behavior of two experienced observers. In all cases, the accuracy of the students improved from near random decision making (33%) to accuracies ranging from 50% to 68%.