6693843
From Spatial Proximity to Semantic Coherence: A Quantitative Approach to the Study of Group Dynamics in Collaborative Virtual Environments
This article describes a quantitative approach to the study of group dynamics in Collaborative Information Visualization Environments (CIVEs). This approach characterizes group dynamics in terms of two concepts introduced in this articlespatial proximity and semantic coherence. The concepts are crucial to the understanding of profound interrelationships between spatial, semantic, and social navigation. Furthermore, this article describes three visualization techniquessemantic indentation chat sequence displays, activity maps, and clock-face mapsthat permit the identification of important features of group interaction that are related to semantic coherence and spatial proximity. The approach is illustrated by applying it to the analysis of an empirical study in which four groups of subjects performed collaborative search tasks through 3D visualizations of knowledge domains. The major contribution of the work is the conceptualization and quantification of group coherence as a generic methodology for the study of a range of collaborative virtual environments such as collaborative learning, distance learning, social networks, collaborative information visualization, and digital libraries. Further research challenges for the study of group behavior in collaborative information-visualization environments are identified.
15424500
Semantically modified diffusion limited aggregation for visualizing large-scale networks
Diffusion-limited aggregation (DLA) is a model of fractal growth. Computer models can simulate the fast aggregation of millions of particles. We propose a modified version of DLA, called semantically modified DLA (SM-DLA), for visualizing large-scale networks. SM-DLA introduces similarity measures between particles so that instead of attaching to the nearest particle in the aggregation, a new particle is stochastically directed to attach to particles that are similar to it. The results of our initial experiment with a co-citation network using SM-DLA are encouraging, suggesting that the algorithm has the potential as an alternative paradigm for visualizing large-scale networks. Further studies in this direction are recommended.
46129433
Behavioural Patterns of Collaborative Writing with Hypertext - A State Transition Approach
This study investigates behavioural patterns of collaborative writing with a hypertext system by using a state-transition approach. State-transition models are empirically developed for capturing the dynamic nature of collaborative writing. Users were frequently engaged in tasks such as exploration, organization, and editing, whereas the use of collaborative support functions was transient in nature. The study shows that state-transition analysis is an important approach to task analysis, requirements engineering, and human-computer interaction studies. This study has produced some valuable experiences and lessons for researchers and practitioners in collaborative writing.
206109439
How did university departments interweave the Web: A study of connectivity and underlying factors
This paper presents two studies of the use of the WWW in Scottish universities and American land-grant universities. First, we investigated the relationship between the organisational profile of a university department in Scotland and its structural connectivity on the WWW. A Spearman rank order correlation analysis revealed a number of strong correlation relationships between structural connectivity measures and the organisational profile based on research assessment exercise ratings, teaching quality assessments, student‐staff ratios and funding levels. Linkage patterns from 13 Scottish academic sites to commercial sites in Britain and America highlighted the impact of culture and the appropriateness of information technologies on the acceptance of the WWW. The second study is a content survey of WWW-based education activities in American land-grant universities to investigate successful applications of these enabling techniques in education. The two studies together highlighted cultural, political and technological interactions in the use of the WWW. q 1998 Elsevier Science B.V. All rights reserved
468820
Tracing knowledge diffusion
Knowledge diffusion is the adaptation of knowledge in a broad range of scientific and engineering research and development. Tracing knowledge diffusion between science and technology is a challenging issue due to the complexity of identifying emerging patterns in a diverse range of possible processes. In this article, we describe an approach that combines complex network theory, network visualization, and patent citation analysis in order to improve the means for the study of knowledge diffusion. In particular, we analyze patent citations in the field of tissue engineering. We emphasize that this is the beginning of a longer-term endeavor that aims to develop and deploy effective, progressive, and explanatory visualization techniques for us to capture the dynamics of the evolution of patent citation networks. The work has practical implications on resource allocation, strategic planning, and science policy.
45076304
Spatial Semantic Virtual Worlds: The Structural Duality and Beyond
27714693
Efficient Parallel Processing for K-Nearest-Neighbor Search in Spatial Databases
Even though the problem of k nearest neighbor (kNN) query is well-studied in serial environment, there is little prior work on parallel kNN search processing in parallel one. In this paper, we present the first Best-First based Parallel kNN (BFPkNN) query algorithm in a multi-disk setting, for efficient handling of kNN retrieval with arbitrary values of k by parallelization. The core of our method is to access more entries from multiple disks simultaneously and enable several effective pruning heuristics to discard non-qualifying entries. Extensive experiments with real and synthetic datasets confirm that BFPkNN significantly outperforms its competitors in both efficiency and scalability.
41020572
Cycle Partitions in Graphs
In this paper, we prove that every graph contains a cycle intersecting all maximum independent sets. Using this, we further prove that every graph with stability number α is spanned by α disjoint cycles. Here, the empty set, the graph of order 1 and the path of order 2 are all considered as degenerate cycles.
14219803
A new method to measure the semantic similarity of GO terms
MOTIVATION
Although controlled biochemical or biological vocabularies, such as Gene Ontology (GO) (http://www.geneontology.org), address the need for consistent descriptions of genes in different data sources, there is still no effective method to determine the functional similarities of genes based on gene annotation information from heterogeneous data sources.


RESULTS
To address this critical need, we proposed a novel method to encode a GO term's semantics (biological meanings) into a numeric value by aggregating the semantic contributions of their ancestor terms (including this specific term) in the GO graph and, in turn, designed an algorithm to measure the semantic similarity of GO terms. Based on the semantic similarities of GO terms used for gene annotation, we designed a new algorithm to measure the functional similarity of genes. The results of using our algorithm to measure the functional similarities of genes in pathways retrieved from the saccharomyces genome database (SGD), and the outcomes of clustering these genes based on the similarity values obtained by our algorithm are shown to be consistent with human perspectives. Furthermore, we developed a set of online tools for gene similarity measurement and knowledge discovery.


AVAILABILITY
The online tools are available at: http://bioinformatics.clemson.edu/G-SESAME.


SUPPLEMENTARY INFORMATION
http://bioinformatics.clemson.edu/Publication/Supplement/gsp.htm.
596165
Combining models and guided empirical search to optimize for multiple levels of the memory hierarchy
This paper describes an algorithm for simultaneously optimizing across multiple levels of the memory hierarchy for dense-matrix computations. Our approach combines compiler models and heuristics with guided empirical search to take advantage of their complementary strengths. The models and heuristics limit the search to a small number of candidate implementations, and the empirical results provide the most accurate information to the compiler to select among candidates and tune optimization parameter values. We have developed an initial implementation and applied this approach to two case studies, matrix multiply and Jacobi relaxation. For matrix multiply, our results on two architectures, SGI R10000 and Sun UltraSparc IIe, outperform the native compiler, and either outperform or achieve comparable performance as the ATLAS self-tuning library and the hand-tuned vendor BLAS library. Jacobi results also substantially outperform the native compilers.
13521805
A Systematic Approach to Model-Guided Empirical Search for Memory Hierarchy Optimization
The goal of this work is a systematic approach to compiler optimization for simultaneously optimizing across multiple levels of the memory hierarchy. Our approach combines compiler models and heuristics with guided empirical search to take advantage of their complementary strengths. The models and heuristics limit the search to a small number of candidate implementations, and the empirical results provide accurate feedback information to the compiler. In previous work, we propose a compiler algorithm for deriving a set of parameterized solutions, followed by a model-guided empirical search to determine the best integer parameter values and select the best overall solution. This paper focuses on formalizing the process of deriving parameter values, which is a multi-variable optimization problem, and considers the role of AI search techniques in deriving a systematic framework for the search.