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What is Association Rules

Handbook of Research on Text and Web Mining Technologies
Rules usually in the format X ? Y, meaning that “ifXis present in an object, thenYis also present in this object“.
Published in Chapter:
Concept-Based Text Mining
Stanley Loh (Lutheran University of Brazil, Brazil), Leandro Krug Wives (Federal University of Rio Grande do Sul, Brazil), Daniel Lichtnow (Catholic University of Pelotas, Brazil), and José Palazzo M. de Oliveira (Federal University of Rio Grande do Sul, Brazil)
Copyright: © 2009 |Pages: 13
DOI: 10.4018/978-1-59904-990-8.ch021
Abstract
The goal of this chapter is to present an approach to mine texts through the analysis of higher level characteristics (called “concepts’), minimizing the vocabulary problem and the effort necessary to extract useful information. Instead of applying text mining techniques on terms or keywords labeling or extracted from texts, the discovery process works over concepts extracted from texts. Concepts represent real world attributes (events, objects, feelings, actions, etc.) and, as seen in discourse analysis, they help to understand ideas and ideologies present in texts. A previous classification task is necessary to identify concepts inside the texts. After that, mining techniques are applied over the concepts discovered. The chapter will discuss different concept-based text mining techniques and present results from different applications.
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More Results
User-Adapted Information Services
Association rules describe relationships and correlations between attributes or objects in large data sets. Several algorithms have been developed to extract such rules from large data sets.
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Measuring the Attitudes of Governmental Policies and the Public Towards the COVID-19 Pandemic
Is a rule-based machine learning method for discovering interesting relations between variables in large databases.
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Data Mining Tools: Formal Concept Analysis and Rough Sets
Identification of statistically related attributes in data.
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Incorporating Fuzzy Logic in Data Mining Tasks
Techniques that find in a database conjunctive implication rules of the form “X and Y implies A and B.”
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Neural Networks for Automobile Insurance Pricing
Predict the occurrence of an event based on the occurrences of another event.
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Discovering Personalized Novel Knowledge from Text
Rules consisting items which are highly related to each other based on co-occurrence, or statistical analysis.
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Challenges in Data Mining on Medical Databases
Association rule mining finds interesting associations or correlation relationships among large set of data items. Association rules show attributes value conditions that occur frequently together in a given dataset. Association rules provide information of this type in the form of “if-then” statements.
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Statistical Methods for User Profiling in Web Usage Mining
A methodology used to discover the co-occurrence between two or more items in a large dataset. In Web Mining, association rules are used to identify groups of pages that are jointly consulted within a set of sessions in a browsing process
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Intelligent Slotting for the Warehouse
Many standard algorithms are available to apply machine learning concepts to practical problems. One such class is association rule algorithms. Association rule algorithms determine the associations between the features used to describe a data set. The origin of association rules mining was as a technique for finding interesting rules from transactional databases.
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