88 Abstract— One of the most challenging areas in data mining is Association rule mining. Several algorithms have been developed to solve this problem. These algorithms work efficiently with static datasets. But if new records are added time to time to the datasets means if the datasets are incremental in nature, scenario of association rules may changed. Some of the new itemsets may become fre...

Data and knowledge hiding are two research directions that investigate how the privacy of raw data, or information, can be maintained either before or after the course of mining the data. By focusing on the knowledge hiding thread, we present a taxonomy and a survey of recent approaches that have been applied to the association rule hiding problem. Association rule hiding refers to the process ...

Association rule mining is one of the well established fields in data mining. This paper has surveyed the research papers in this field from 1993 to 2013. This paper gives detailed account of fundamental algorithms and its advantages and disadvantages. This also provides brief overview of current trends of association and frequent pattern mining and medical applications.

In the last thirty years fuzzy logic became very popular. One can find solutions based on it in several fields from industrial systems to house appliances. Recently a new category of fuzzy systems gained more attention, the so called fuzzy rule interpolation (FRI) based systems. Owing to the low complexity of their rule bases, i.e. they can infer as well when only the relevant rules are known, ...

BACKGROUND AND PURPOSE Four percent to 10% of patients with transient ischemic attack (TIA) have a stroke or die within 1 week of their diagnosis. This national survey examined Canadian neurologists' current practice for managing TIA, the need for a clinical decision rule to identify high-risk patients, and the required sensitivity of such a rule. METHODS We surveyed 650 neurologists register...

Moving from single-rule Xcerpt programs as described in previous deliverables to full Xcerpt programs requires to address the issue of efficient rule chaining. In this deliverable, we first survey existing approaches for efficient rule chaining (using some form of memoization) in logic programming and then briefly outline first results and challenges when extending these results to Xcerpt. Keyw...

Approximate fuzzy reasoning methods serves the task of inference in case of fuzzy systems built on sparse rule bases. This paper is a part of a longer survey that aims to provide a qualitative view through the various ideas and characteristics of interpolation based fuzzy reasoning methods. It also aims to define a general condition set for fuzzy rule interpolation methods brought together from...

Reaction rules and event processing technologies play a key role in making business and IT / Internet infrastructures more agile and active. While event processing is concerned with detecting events from large event clouds or streams in almost real-time, reaction rules are concerned with the invocation of actions in response to events and actionable situations. They state the conditions under w...