Closed-set-based discovery of representative association rules

The output of an association rule miner is often huge in practice. This is why several concise lossless representations have been proposed, such as the “essential” or “representative” rules. A previously known algorithm for mining representative rules relies on an incorrect mathematical claim, and can be seen to miss part of its intended output; in previous work, two of the authors of the present paper have offered a complete but, often, somewhat slower alternative. Here, we extend this alternative to the case of closure-based redundancy. The empirical validation shows that, in this way, we can improve on the original time efficiency, without sacrificing completeness.Peer ReviewedPostprint (author's final draft

Could parental rules play a role in the association between short sleep and obesity in young children?

Short sleep duration is associated with obesity in young children. This study develops the hypothesis that parental rules play a role in this association. Participants were 3-year-old children and their parents, recruited at nursery schools in socioeconomically deprived and non-deprived areas of a North-East England town. Parents were interviewed to assess their use of sleep, television-viewing and dietary rules, and given diaries to document their child's sleep for 4 days/5 nights. Children were measured for height, weight, waist circumference and triceps and subscapular skinfold thicknesses. One-hundred and eight families participated (84 with complete sleep data and 96 with complete body composition data). Parental rules were significantly associated together, were associated with longer night-time sleep and were more prevalent in the non-deprived-area compared with the deprived-area group. Television-viewing and dietary rules were associated with leaner body composition. Parental rules may in part confound the association between night-time sleep duration and obesity in young children, as rules cluster together across behavioural domains and are associated with both sleep duration and body composition. This hypothesis should be tested rigorously in large representative samples

Closed-set-based discovery of representative association rules revisited

The output of an association rule miner is often huge in practice. This is why several concise lossless representations have been proposed, such as the “essential” or “representative” rules. We revisit the algorithm given by Kryszkiewicz (Int. Symp. Intelligent Data Analysis 2001, Springer-Verlag LNCS 2189, 350–359) for mining representative rules. We show that its output is sometimes incomplete, due to an oversight in its mathematical validation, and we propose an alternative complete generator that works within only slightly larger running times.Postprint (author’s final draft

Frequent Lexicographic Algorithm for Mining Association Rules

The recent progress in computer storage technology have enable many organisations to collect and store a huge amount of data which is lead to growing demand for new techniques that can intelligently transform massive data into useful information and knowledge. The concept of data mining has brought the attention of business community in finding techniques that can extract nontrivial, implicit, previously unknown and potentially useful information from databases. Association rule mining is one of the data mining techniques which discovers strong association or correlation relationships among data. The primary concept of association rule algorithms consist of two phase procedure. In the first phase, all frequent patterns are found and the second phase uses these frequent patterns in order to generate all strong rules. The common precision measures used to complete these phases are support and confidence. Having been investigated intensively during the past few years, it has been shown that the first phase involves a major computational task. Although the second phase seems to be more straightforward, it can be costly because the size of the generated rules are normally large and in contrast only a small fraction of these rules are typically useful and important. As response to these challenges, this study is devoted towards finding faster methods for searching frequent patterns and discovery of association rules in concise form. An algorithm called Flex (Frequent lexicographic patterns) has been proposed in obtaining a good performance of searching li-equent patterns. The algorithm involved the construction of the nodes of a lexicographic tree that represent frequent patterns. Depth first strategy and vertical counting strategy are used in mining frequent patterns and computing the support of the patterns respectively. The mined frequent patterns are then used in generating association rules. Three models were applied in this task which consist of traditional model, constraint model and representative model which produce three kinds of rules respectively; all association rules, association rules with 1-consequence and representative rules. As an additional utility in the representative model, this study proposed a set-theoretical intersection to assist users in finding duplicated rules. Four datasets from UCI machine learning repositories and domain theories except the pumsb dataset were experimented. The Flex algorithm and the other two existing algorithms Apriori and DIC under the same specification are tested toward these datasets and their extraction times for mining frequent patterns were recorded and compared. The experimental results showed that the proposed algorithm outperformed both existing algorithms especially for the case of long patterns. It also gave promising results in the case of short patterns. Two of the datasets were then chosen for further experiment on the scalability of the algorithms by increasing their size of transactions up to six times. The scale-up experiment showed that the proposed algorithm is more scalable than the other existing algorithms. The implementation of an adopted theory of representative model proved that this model is more concise than the other two models. It is shown by number of rules generated from the chosen models. Besides a small set of rules obtained, the representative model also having the lossless information and soundness properties meaning that it covers all interesting association rules and forbid derivation of weak rules. It is theoretically proven that the proposed set-theoretical intersection is able to assist users in knowing the duplication rules exist in representative model

Acronyms and Abbreviations

Acronyms and abbreviations that are used throughout this book and that are frequently encountered in Washington legal materials are listed below, along with the full names or titles they represent. The list includes publications (the full titles are printed in italics); bar associations and legal organizations; federal and state agencies, boards, commissions, and departments; legal terms; court rules; statutes; and electronic databases and services. Washington State agencies are designated by the word Washington in parentheses; sections or programs of the Washington State Bar Association are indicated by WSBA in parentheses. It is a representative, not a comprehensive, list.https://digitalcommons.law.uw.edu/librarians-chapters/1017/thumbnail.jp

BILLS AND NOTES - SIGNING IN REPRESENTATIVE CAPACITY - PERSONAL LIABILITY

Defendant, while acting as trustee of the Catholic Diocese of Cleveland, an unincorporated religious association, executed to the plaintiff negotiable promissory notes in the following forms: (1) Ninety days after date, for value received for The Calvary Cemetery . . . we promise to pay . . . [Signed] Joseph Schrembs, Bishop of Cleveland. Calvary Cemetery Association, By: J. T. B., Treas. (2) Six months after date, for value received for Sacred Heart of Mary Church . . . we promise to pay . . . [Signed] Councilmen: A. S.; L. F.; V. J. H.; H. S. Z.; Joseph Schrembs, Bishop of Cleveland; F. T. K., Pastor. Held, defendant signed in a representative capacity and is not personally liable on either note, since Section 20 of the Negotiable Instruments Law has changed the common-law rules. George D. Harter Bank v. Schrembs, 55 Ohio App. 116, 9 N. E. (2d) 154 (1936)

The Impact of Technological Developments on the Rules of Attorney Ethics Regarding Attorney–Client Privilege, Confidentiality, and Social Media

This article focuses on the development of the law of ethics and technology. Emphasis is placed on how technological developments have affected the rules and means by which lawyers practice law and certain ethical pitfalls that have developed hand-in-hand with technological advancements. Topics examined include: (1) the ways by which electronic communication has increased the potential for the attorney–client privilege to be waived and the resulting impact on the present-day practice of law; (2) the effect of social media on lawyers’ ethical obligations, including counseling clients regarding the client’s use of social media and the lawyer’s own use of social media; and (3) the impact of cloud computing on a lawyer’s obligation to protect client confidences. The authors examine the development of these technological effects on the practice of law through an examination of the evolution of the American Bar Association, its Model Rules of Professional Conduct, and state ethics opinions and representative case law