Tools : Association Rules
نویسندگان
چکیده
The current times have witnessed an exponential increase in the popularity of the Internet as well as advanced data collection tools across a wide variety of application domains. This has led to an explosive growth of data accumulation from terabytes to petabytes at a dramatic pace, and is already trending towards exabytes. The data flows from various sources including business (Web, e-commerce, transactions, stocks, and business intelligence), science (remote sensing, bioinformatics, Large Hedron Collider, and scientific simulations), and society (news, blogs, forums, and social networks). The heterogeneous nature of such voluminous data dictates the requirement to extract and reveal the summary of knowledge that can be used in tasks such as decision making, event prediction, and pattern extraction. More recently, data mining techniques have also been applied to predict vulnerabilities of Web applications, involving scripts running on multiple sites, for computer security (Shar & Tan, 2012; Shar & Tan, 2012).
منابع مشابه
Conceptual Knowledge Discovery with Frequent Concept Lattices
Knowledge discovery support environments include beside classical data analysis tools also data mining tools. For supporting both kinds of tools, a uniied knowledge representation is needed. We show that concept lattices which are used as knowledge representation in Conceptual Information Systems can also be used for structuring the results of mining association rules. Vice versa, we use ideas ...
متن کاملIntroducing an algorithm for use to hide sensitive association rules through perturb technique
Due to the rapid growth of data mining technology, obtaining private data on users through this technology becomes easier. Association Rules Mining is one of the data mining techniques to extract useful patterns in the form of association rules. One of the main problems in applying this technique on databases is the disclosure of sensitive data by endangering security and privacy. Hiding the as...
متن کاملRM-Tool: A framework for discovering and evaluating association rules
Nowadays, there are a great number of both specific and general data mining tools available to carry out association rule mining. However, it is necessary to use several of these tools in order to obtain only the most interesting and useful rules for a given problem and dataset. To resolve this drawback, this paper describes a fully integrated framework to help in the discovery and evaluation o...
متن کاملUsing a Data Mining Tool and FP-Growth Algorithm Application for Extraction of the Rules in two Different Dataset (TECHNICAL NOTE)
In this paper, we want to improve association rules in order to be used in recommenders. Recommender systems present a method to create the personalized offers. One of the most important types of recommender systems is the collaborative filtering that deals with data mining in user information and offering them the appropriate item. Among the data mining methods, finding frequent item sets and ...
متن کاملDeveloping a Course Recommender by Combining Clustering and Fuzzy Association Rules
Each semester, students go through the process of selecting appropriate courses. It is difficult to find information about each course and ultimately make decisions. The objective of this paper is to design a course recommender model which takes student characteristics into account to recommend appropriate courses. The model uses clustering to identify students with similar interests and skills...
متن کاملRevisiting Generic Bases of Association Rules
As a side effect of unprecedented amount of digitization of data, classical retrieval tools found themselves unable to go further beyond the tip of the Iceberg. Data Mining in conjunction with the Formal Concept Analysis, is a clear promise to furnish adequate tools to do so and specially to be able to derive concise generic and easy understandable bases of ”hidden” knowledge, that can be relia...
متن کامل