5,079 research outputs found

    Mining Event Logs to Support Workflow Resource Allocation

    Full text link
    Workflow technology is widely used to facilitate the business process in enterprise information systems (EIS), and it has the potential to reduce design time, enhance product quality and decrease product cost. However, significant limitations still exist: as an important task in the context of workflow, many present resource allocation operations are still performed manually, which are time-consuming. This paper presents a data mining approach to address the resource allocation problem (RAP) and improve the productivity of workflow resource management. Specifically, an Apriori-like algorithm is used to find the frequent patterns from the event log, and association rules are generated according to predefined resource allocation constraints. Subsequently, a correlation measure named lift is utilized to annotate the negatively correlated resource allocation rules for resource reservation. Finally, the rules are ranked using the confidence measures as resource allocation rules. Comparative experiments are performed using C4.5, SVM, ID3, Na\"ive Bayes and the presented approach, and the results show that the presented approach is effective in both accuracy and candidate resource recommendations.Comment: T. Liu et al., Mining event logs to support workflow resource allocation, Knowl. Based Syst. (2012), http://dx.doi.org/ 10.1016/j.knosys.2012.05.01

    Viable tax constitutions

    Get PDF
    Taxation is only sustainable if the general public complies with it. This observation is uncontroversial with tax practitioners but has been ignored by the public finance tradition, which has interpreted tax constitutions as binding contracts by which the power to tax is irretrievably conferred by individuals to government, which can then levy any tax it chooses. However, in the absence of an outside party enforcing contracts between members of a group, no arrangement within groups can be considered to be a binding contract, and therefore the power of tax must be sanctioned by individuals on an ongoing basis. In this paper we offer, for the first time, a theoretical analysis of this fundamental compliance problem associated with taxation, obtaining predictions that in some cases point to a re-interptretation of the theoretical constructions of the public finance tradition while in others call them into question

    Architectural run-time models for performance and privacy analysis in dynamic cloud applications

    Get PDF

    Viable Tax Constitutions

    Get PDF
    Taxation is only sustainable if the general public complies with it. This observation is uncontroversial with tax practitioners but has been ignored by the public finance tradition, which has interpreted tax constitutions as binding contracts by which the power to tax is irretrievably conferred by individuals to government, which can then levy any tax it chooses. However, in the absence of an outside party enforcing contracts between members of a group, no arrangement within groups can be considered to be a binding contract, and therefore the power of tax must be sanctioned by individuals on an ongoing basis. In this paper we offer, for the first time, a theoretical analysis of this fundamental compliance problem associated with taxation, obtaining predictions that in some cases point to a re-interptretation of the theoretical constructions of the public finance tradition while in others call them into questionTaxation ; Public Goods ; Government

    Data-driven conceptual modeling: how some knowledge drivers for the enterprise might be mined from enterprise data

    Get PDF
    As organizations perform their business, they analyze, design and manage a variety of processes represented in models with different scopes and scale of complexity. Specifying these processes requires a certain level of modeling competence. However, this condition does not seem to be balanced with adequate capability of the person(s) who are responsible for the task of defining and modeling an organization or enterprise operation. On the other hand, an enterprise typically collects various records of all events occur during the operation of their processes. Records, such as the start and end of the tasks in a process instance, state transitions of objects impacted by the process execution, the message exchange during the process execution, etc., are maintained in enterprise repositories as various logs, such as event logs, process logs, effect logs, message logs, etc. Furthermore, the growth rate in the volume of these data generated by enterprise process execution has increased manyfold in just a few years. On top of these, models often considered as the dashboard view of an enterprise. Models represents an abstraction of the underlying reality of an enterprise. Models also served as the knowledge driver through which an enterprise can be managed. Data-driven extraction offers the capability to mine these knowledge drivers from enterprise data and leverage the mined models to establish the set of enterprise data that conforms with the desired behaviour. This thesis aimed to generate models or knowledge drivers from enterprise data to enable some type of dashboard view of enterprise to provide support for analysts. The rationale for this has been started as the requirement to improve an existing process or to create a new process. It was also mentioned models can also serve as a collection of effectors through which an organization or an enterprise can be managed. The enterprise data refer to above has been identified as process logs, effect logs, message logs, and invocation logs. The approach in this thesis is to mine these logs to generate process, requirement, and enterprise architecture models, and how goals get fulfilled based on collected operational data. The above a research question has been formulated as whether it is possible to derive the knowledge drivers from the enterprise data, which represent the running operation of the enterprise, or in other words, is it possible to use the available data in the enterprise repository to generate the knowledge drivers? . In Chapter 2, review of literature that can provide the necessary background knowledge to explore the above research question has been presented. Chapter 3 presents how process semantics can be mined. Chapter 4 suggest a way to extract a requirements model. The Chapter 5 presents a way to discover the underlying enterprise architecture and Chapter 6 presents a way to mine how goals get orchestrated. Overall finding have been discussed in Chapter 7 to derive some conclusions

    Report of the Terrestrial Bodies Science Working Group. Volume 9: Complementary research and development

    Get PDF
    Topics discussed include the need for: the conception and development of a wide spectrum of experiments, instruments, and vehicles in order to derive the proper return from an exploration program; the effective use of alternative methods of data acquisition involving ground-based, airborne and near Earth orbital techniques to supplement spacraft mission; and continued reduction and analysis of existing data including laboratory and theoretical studies in order to benefit fully from experiments and to build on the past programs toward a logical and efficient exploration of the solar system

    Working Notes from the 1992 AAAI Spring Symposium on Practical Approaches to Scheduling and Planning

    Get PDF
    The symposium presented issues involved in the development of scheduling systems that can deal with resource and time limitations. To qualify, a system must be implemented and tested to some degree on non-trivial problems (ideally, on real-world problems). However, a system need not be fully deployed to qualify. Systems that schedule actions in terms of metric time constraints typically represent and reason about an external numeric clock or calendar and can be contrasted with those systems that represent time purely symbolically. The following topics are discussed: integrating planning and scheduling; integrating symbolic goals and numerical utilities; managing uncertainty; incremental rescheduling; managing limited computation time; anytime scheduling and planning algorithms, systems; dependency analysis and schedule reuse; management of schedule and plan execution; and incorporation of discrete event techniques
    corecore