Combined Pattern Mining: From Learned Rules to Actionable Knowledge
نویسندگان
چکیده
Association mining often produces large collections of association rules that are difficult to understand and put into action. In this paper, we have designed a novel notion of combined patterns to extract useful and actionable knowledge from a large amount of learned rules. We also present definitions of combined patterns, design novel metrics to measure their interestingness and analyze the redundancy in combined patterns. Experimental results on real-life social security data demonstrate the effectiveness and potential of the proposed approach in extracting actionable knowledge from complex data.
منابع مشابه
Combined Association Rule Mining
This paper proposes an algorithm to discover novel association rules, combined association rules. Compared with conventional association rule, this combined association rule allows users to perform actions directly. Combined association rules are always organized as rule sets, each of which is composed of a number of single combined association rules. These single rules consist of non-actionabl...
متن کاملCombined Pattern Mining for D3M Using Fuzzy
Many algorithms and models were developed but the findings are not actionable and lack of soft power while solving the complex problems. Domain Driven Data mining is used a major efforts to promote the action ability of the knowledge discovery in the real world smart decision making. Combined mining is one of the common methods for analyzing complex data for identifying complex knowledge. The d...
متن کاملCombined Mining: Analyzing Object and Pattern Relations for Discovering Actionable Complex Patterns
Combined mining is a technique for analyzing object relations and pattern relations, and for extracting and constructing actionable complex knowledge (patterns or exceptions) in complex situations. Although combined patterns can be built within a single method, such as combined sequential patterns by aggregating relevant frequent sequences, this knowledge is composed of multiple constituent com...
متن کاملActionable Rules: Issues and New Directions
Knowledge Discovery in Databases (KDD) is the process of extracting previously unknown, hidden and interesting patterns from a huge amount of data stored in databases. Data mining is a stage of the KDD process that aims at selecting and applying a particular data mining algorithm to extract an interesting and useful knowledge. It is highly expected that data mining methods will find interesting...
متن کاملSubgroup Discovery Techniques and Applications
This paper presents the advances in subgroup discovery and the ways to use subgroup discovery to generate actionable knowledge for decision support. Actionable knowledge is explicit symbolic knowledge, typically presented in the form of rules, that allow the decision maker to recognize some important relations and to perform an appropriate action, such as planning a population screening campaig...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2008