Fast mining of non-derivable episode rules in complex sequences

Researchers have been endeavoring to discover concise sets of episode rules instead of complete sets in sequences. Existing approaches, however, are not able to process complex sequences and can not guarantee the accuracy of resulting sets due to the violation of anti-monotonicity of the frequency metric. In some real applications, episode rules need to be extracted from complex sequences in which multiple items may appear in a time slot. This paper investigates the discovery of concise episode rules in complex sequences. We define a concise representation called non-derivable episode rules and formularize the mining problem. Adopting a novel anti-monotonic frequency metric, we then develop a fast approach to discover non-derivable episode rules in complex sequences. Experimental results demonstrate that the utility of the proposed approach substantially reduces the number of rules and achieves fast processing.

A study on the accuracy of frequency measures and its impact on knowledge discovery in single sequences

In knowledge discovery in single sequences, different results could be discovered from the same sequence when different frequency measures are adopted. It is natural to raise such questions as (1) do these frequency measures reflect actual frequencies accurately? (2) what impacts do frequency measures have on discovered knowledge? (3) are discovered results accurate and reliable? and (4) which measures are appropriate for reflecting frequencies accurately? In this paper, taking three major factors (anti-monotonicity, maximum-frequency and window-width restriction) into account, we identify inaccuracies inherent in seven existing frequency measures, and investigate their impacts on the soundness and completeness of two kinds of knowledge, frequent episodes and episode rules, discovered from single sequences. In order to obtain more accurate frequencies and knowledge, we provide three recommendations for defining appropriate frequency measures. Following the recommendations, we introduce a more appropriate frequency measure. Empirical evaluation reveals the inaccuracies and verifies our findings. 

Subsequence frequency measurement and its impact on knowledge discovery in single sequences

Subsequence frequency measurement is a basic and essential problem in knowledge discovery in single sequences. Frequency based knowledge discovery in single sequences tends to be unreliable since different resulting sets may be obtained from a same sequence when different frequency metrics are adopted. In this chapter, we investigate subsequence frequency measurement and its impact on the reliability of knowledge discovery in single sequences. We analyse seven previous frequency metrics, identify their inherent inaccuracies, and explore their impacts on two kinds of knowledge discovered from single sequences, frequent episodes and episode rules. We further give three suggestions for frequency metrics and introduce a new frequency metric in order to improve the reliability. Empirical evaluation reveals the inaccuracies and verifies our findings.

Financial accounting reforms in the Australian public sector: an episode in institutional thinking

In recent years in Australia, accounting regulations have been developed that require the adoption of commercial accounting and reporting practices by public-sector organisations, including the recognition of cultural, heritage and scientific collections as assets by non-profit cultural organisations. The regulations inappropriately apply traditional accounting concepts of accountability and performance, notwithstanding that the primary objectives of many of the organisations affected are not financial. This study examines how this was able to occur within the ideas outlined in Douglas’s (1986) How Institutions Think. The study provides evidence to demonstrate that the development; promotion, and defense of the detailed accounting regulations were each constrained by institutional thinking and, as a result, only certain questions were asked and many problems and issues associated with the regulations were not addressed. Thus, it seeks to further our understanding of the nature and limits of change in accounting and the role of institutions in promoting and defending changes to accounting practice.

Importance of administrative transparency in the correctional context : knowing the rules

As a class, prisoners are vulnerable to numerous privations while in custody. In particular, prisoners are at a distinct disadvantage in terms of being able to control the central features of their daily lives. The lives of prisoners are circumscribed by numerous rules and regulations and their administration by correctional administrators. It is important that prisoners are aware of the content of the rules that govern their existence and the precise basis upon which power is exercised over them. In a recent freedom of information application in Victoria, a prisoner sought a personal copy of the rules that would govern his life in that particular institution. The prison authorities refused that request. The prisoner then appealed that decision to the Victorian Civil and Administrative Tribunal and was unsuccessful. It is contended that the analysis used in that case was flawed through the misreading of the nature of correctional environment and the fundamental importance of transparency in such a context.

An optimal strategy for extracting probabilistic rules by combining rough sets and genetic algorithm

This paper proposes an optimal strategy for extracting probabilistic rules from databases. Two inductive learning-based statistic measures and their rough set-based definitions: accuracy and coverage are introduced. The simplicity of a rule emphasized in this paper has previously been ignored in the discovery of probabilistic rules. To avoid the high computational complexity of rough-set approach, some rough-set terminologies rather than the approach itself are applied to represent the probabilistic rules. The genetic algorithm is exploited to find the optimal probabilistic rules that have the highest accuracy and coverage, and shortest length. Some heuristic genetic operators are also utilized in order to make the global searching and evolution of rules more efficiently. Experimental results have revealed that it run more efficiently and generate probabilistic classification rules of the same integrity when compared with traditional classification methods.

Rules and resources: a structuration approach to understanding the coordination of childrens`s inpatient health care

Aim. This paper presents findings from a multi-method study exploring the process of care coordination in children's inpatient health care.

Background. Existing work on care coordination is typified by 'black-box' type studies that measure inputs to and outcomes of care coordination roles and practices, without addressing the process of coordination.

Method. Using questionnaires, interviews and observation to collect data in multiple sites in the United Kingdom and Denmark between 1999 and 2005, the study gathered the perceptions of staff and compared these with observed practice. Giddens' structuration theory was used to provide an analytical and explanatory framework.

Findings. Current care coordination practice is diverse and inconsistent. It involves a wide range of clinical and non-clinical staff, many of whom perceive a lack of clarity about who should perform specific coordination activities. Staff draw upon a wide range of different material and non-material resources in coordinating care, the use of which is governed by largely tacit and informal rules.

Conclusions. Care coordination can be usefully conceptualized as a 'structurated' process – one that is continually produced and reproduced by staff using rules and resources to 'instantiate' or bring about care coordination through action. Potentially negative implications of this are manifested in diversity and inconsistency in care coordination practice. However, positive aspects such as the opportunity this provides to tailor care to the needs of the individual patient can be realized.