17153152
What Are You Looking At? Newest Findings from an Empirical Study of Group Awareness
Real-time, distributed, collaborative writing systems are useful tools allowing a group of distributed authors to work on a document simultaneously. A very important factor in achieving effective and efficient collaborative writing is the incorporation of group awareness (GA). GA conveniently provides comprehensive knowledge about the status of a document and activities other authors perform upon the document. However, far more work needs to be carried out in determining exactly what awareness elements (awareness information, such as where users are viewing within a document versus where they are working on a document) are required in collaborative writing. This involves empirically determining which elements are more important than others for support.
14447070
Achieving convergence, causality preservation, and intention preservation in real-time cooperative editing systems
Real-time cooperative editing systems allow multiple users to view and edit the same text/graphic/image/multimedia document at the same time for multiple sites connected by communication networks. Consistency maintenance is one of the most significant challenges in designing and implementing real-time cooperative editing systems. In this article, a consistency model, with properties of convergence, causality preservation, and intention preservation, is proposed as a framework for consistency maintenance in real-time cooperative editing systems. Moreover, an integrated set of schemes and algorithms, which support the proposed consistency model, are devised and discussed in detail. In particular, we have contributed (1) a novel generic operation transformation control algorithm for achieving intention preservation in combination with schemes for achieving convergence and causality preservation and (2) a pair of reversible inclusion and exclusion transformation algorithms for stringwise operations for text editing. An Internet-based prototype system has been built to test the feasibility of the proposed schemes and algorithms
3428244
An Organisational Perspective on Collaborative Business Processes
Business collaboration is about coordinating the flow of information among organisations and linking their business processes. It brings great challenge to keep participating organisations as autonomous entities in integrating business processes of these organisations seamlessly. To address this issue, we develop a new perspective on business collaborations with a novel concept called relative workflow, which defines what a participating organisation can perceive in collaboration. By incorporating a visibility control mechanism, relative workflows allow each organisation to define its own collaboration structure and behaviours. In this paper, we present a formal definition of relative workflows and related algorithms for generating relative workflows, along with a discussion on how to perform tracking over relative workflows.
4924842
Assigning Local Fixed-time Constraints in Grid Workflow Systems
Many complex grid workflow processes often have only one global fixed-time constraint at the last activity. Since grid workflow execution normally lasts a long time, local control is very important to ensure the overall temporal correctness. With only one global fixed-time constraint, we cannot control grid workflow execution locally in terms of time. As a result, for any temporal violations, we must handle them globally with the consideration of all activities. This would impact the overall cost-effectiveness of grid workflow execution. Therefore, in this paper, we investigate how to assign local fixed-time constraints within the global one so that we can control grid workflow execution locally. Corresponding assigning and verification methods are developed. With local fixed-time constraints, we can achieve better cost-effectiveness
4928164
A service workflow management framework based on peer-to-peer and agent technologies
Service workflow management which consolidates multiple services to achieve business goals has become a critical issue in service-oriented computing. Due to the unique feature of service workflows such as full distribution and high dynamicity, the contemporary workflow technology has exhibited inefficiency, vulnerability, inflexibility and lack of adaptability. Based upon the authors' previous work on peer-to-peer based workflow management and seamless integration of agents and Web services, this paper innovatively presents SwinDeW-A which is a decentralised service workflow management framework based on peer-to-peer and agent technologies. Based on this framework, this paper also discusses how autonomous service level agreement negotiation, decentralised process enactment, and autonomous process adaptation can be achieved. The proposed approach takes advantages of the peer-to-peer computing technology and the agent technology to provide more efficient, reliable, flexible and adaptive service workflow management.
1701823
Dynamic checking of temporal constraints for concurrent workflows
At present, workflow management systems have not sufficiently dealt with the issues of time, involving time modelling at build-time and time management at run-time. They are lack of the ability to support the checking of temporal constraints at run-time. Although some approaches have been devised to tackle this problem, they are limited to a single workflow and use only static techniques to verify temporal constraints. In reality, there are multiple workflows executing concurrently in a workflow management system. There may well exist resource constraints between these concurrent workflows, which affect significantly the verification of temporal constraints at run-time. This paper proposes a novel approach for dynamic verification of temporal constraints for concurrent workflows. We first investigate resource constraints in workflow management systems, and then define concurrent workflow executions. Based on these definitions, we propose a verification method by analysing the temporal relationship and resource constraints between activities among concurrent workflows.
93891
An Evaluation of Statistical Approaches to Text Categorization
This paper focuses on a comparative evaluation of a wide-range of text categorization methods, including previously published results on the Reuters corpus and new results of additional experiments. A controlled study using three classifiers, kNN, LLSF and WORD, was conducted to examine the impact of configuration variations in five versions of Reuters on the observed performance of classifiers. Analysis and empirical evidence suggest that the evaluation results on some versions of Reuters were significantly affected by the inclusion of a large portion of unlabelled documents, mading those results difficult to interpret and leading to considerable confusions in the literature. Using the results evaluated on the other versions of Reuters which exclude the unlabelled documents, the performance of twelve methods are compared directly or indirectly. For indirect compararions, kNN, LLSF and WORD were used as baselines, since they were evaluated on all versions of Reuters that exclude the unlabelled documents. As a global observation, kNN, LLSF and a neural network method had the best performance; except for a Naive Bayes approach, the other learning algorithms also performed relatively well.
5522263
HybMig: A Hybrid Approach to Dynamic Plan Migration for Continuous Queries
In data stream environments, the initial plan of a long-running query may gradually become inefficient due to changes of the data characteristics. In this case, the query optimizer generates a more efficient plan based on the current statistics. The online transition from the old to the new plan is called dynamic plan migration. In addition to correctness, an effective technique for dynamic plan migration should achieve the following objectives: 1) minimize the memory and CPU overhead of the migration, 2) reduce the duration of the transition, and 3) maintain a steady output rate. The only known solutions for this problem are the moving states (MS) and parallel track (PT) strategies, which have some serious shortcomings related to the above objectives. Motivated by these shortcomings, we first propose HybMig, which combines the merits of MS and PT and outperforms both in every aspect. As a second step, we extend PT, MS, and HybMig to the general problem of migration, where both the new and the old plans are treated as black boxes
14899560
Dealing with Predictive-but-Unpredictable Attributes in Noisy Data Sources
Attribute noise can affect classification learning. Previous work in handling attribute noise has focused on those predictable attributes that can be predicted by the class and other attributes. However, attributes can often be predictive but unpredictable. Being predictive, they are essential to classification learning and it is important to handle their noise. Being unpredictable, they require strategies different from those of predictable attributes. This paper presents a study on identifying, cleansing and measuring noise for predictive-but-unpredictable attributes. New strategies are accordingly proposed. Both theoretical analysis and empirical evidence suggest that these strategies are more effective and more efficient than previous alternatives.
19972899
Exploring Multilingual Negotiation Support for English-Chinese Dyads: An Experimental Study
The increasing number of international negotiations involving multiple languages necessitates a growing reliance on multilingual support. Whereas empirical studies on negotiation support systems (NSS) have shown that NSS generally improve negotiation performance, no existing NSS caters for multilingual negotiations. With multilingual support, communication problems brought by the different negotiators' cultures and languages are expected to be addressed. In this study, a negotiation support system with multilingual support was developed and a laboratory experiment was conducted to examine the impact of such support on six important dependent variables. Findings suggested significant effects of NSS support on individual outcome and joint outcome. Multilingual support helped to improve equality of outcome (under qualified conditions) but the time taken was significantly longer.
14593921
Stochastic link and group detection
Link detection and analysis has long been important in the social sciences and in the government intelligence community. A significant effort is focused on the structural and functional analysis of "known" networks. Similarly, the detection of individual links is important but is usually done with techniques that result in "known" links. More recently the internet and other sources have led to a flood of circumstantial data that provide probabilistic evidence of links. Co-occurrence in news articles and simultaneous travel to the same location are two examples.We propose a probabilistic model of link generation based on membership in groups. The model considers both observed link evidence and demographic information about the entities. The parameters of the model are learned via a maximum likelihood search. In this paper we describe the model and then show several heuristics that make the search tractable. We test our model and optimization methods on synthetic data sets with a known ground truth and a database of news articles.