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Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 41 for “"Association rules"”.
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Learning lost temporal fuzzy association rules
Fuzzy association rule mining discovers patterns in transactions, such as shopping baskets in a supermarket, or Web page accesses by a visitor to a Web site. Temporal patterns can be present in fuzzy association rules because the underlying process generating the data can be dynamic. However, …
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A Hybrid Recommendation System Based on Association Rules
… framework is built upon the integration of association rules mining and the content-based approach. The results of experiments show that our proposed framework can provide accurate recommendations to users.</p>
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Enhancing association rules algorithms for mining distributed databases. Integration of fast BitTable and multi-agent association rules mining in distributed medical databases for decision support.
… into centralized location for mining interesting rules is not a good approach. This is because it violates common issues such as data privacy and it imposes network overheads. The situation becomes worse when the network has limited bandwidth which is the case in most of the real time systems. …
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Text mining with exploitation of user's background knowledge : discovering novel association rules from text
… applies it to the problem of discovering novel association rules from documents. The developed system, uMining, consists of two major components: a background knowledge developer and a novel association rules miner. The background knowledge developer learns a user's background knowledge by …
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Uma abordagem para geração e visualização de regras de associação de acesso a conteúdos de portal de notícias
… approach for the generation and visualization of association rules and sequence rules obtained from the content access history data of a Brazilian journal. The proposed approach is composed of four phases: exploratory data analysis (EDA), data preprocessing, generation of association and sequence …
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A new strategy for case-based reasoning retrieval using classification based on association
… aim of this study is to integrate class association rules (CARs) as a special case of associa-tion rules (ARs), to discover a set (of rules) that can form an accurate classifier in a database. It is an efficient method when used to build a classifier, where the target is pre-determined. …
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Enhancing web marketing by using ontology
… knowledge. In the Web Marketing Project, association rules about marketing knowledge have been derived by applying data mining algorithms to existing Web users' data. An ontology was used as a knowledge backbone to enhance data mining for marketing. The Raising Method was developed by …
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Design and analysis of fuzzy systems supported by social network analysis techniques
… systems, presenting the interaction between rules at the inference level in terms of co-fired rules, i.e., rules fired at the same time by a given input. Even more, Fingrams are likely to act as an effective and efficient tool in several applications regarding both design and refinement of …
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LARGE-SCALE DATA ANALYSIS OF GENE EXPRESSION MAPS OBTAINED BY VOXELATION
… expression maps and gene functions, for mining association rules, and for predicting certain gene functions and functional similarities based on the gene expression maps obtained by voxelation. First, we identified the relationship between gene functions and gene expression maps. On one side, we …
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Optimization Problems in Data Mining
… of finding a sequence of optimized confidence association rules, and give an efficient algorithm for solving a simplification of the problem."
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Meta-RaPS Hybridization with Machine Learning Algorithms
… Decision Tree (supervised learning) and Association Rules (unsupervised learning). The objective behind hybridizing Meta-RaPS with an Inductive Decision Tree algorithm is to perform online control for Meta-RaPS' parameters. This Inductive Decision Tree algorithm is used to find favorable …
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Machine learning and data analytics for multilayer data in policy planning
… new classes. 3. Identify frequent patterns and association rules of various attributes at the school level. 4. Perform a regression analysis on results from the macro level to investigate deeper with additional variables to identify the differences and verify the frequent patterns and …
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Knowledge discovery in biological databases : a neural network approach
… be mined from the dataset may refer to patterns, association rules, classification and clustering rules, and so forth. In this dissertation, we present a neural network approach to finding knowledge in biological databases. Specifically, we propose new methods to process biological sequences in …
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Are You Ready? A Proposed Framework For The Assessment Of Digital Forensic Readiness
… subjected to a q-sort test and validated using association rules, producing a preliminary framework of DFR for practitioners. By classifying these indicators into dimensions, it was possible to distill them into 71 variables further classified into either extant or perceptual variables. Factor …
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Indirect association rule mining for crime data analysis
… of this thesis are 1) develop an indirect association rule mining algorithm from a large, publicly available data set with a focus on crimes of the domestic violence nature 2) extend the indirect association rule mining algorithm for generating indirect association rules and determine its …
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Geovisualization for Association Rule Mining in CHOPS Well Data
Association rule mining has recently been applied to improve the oil recovery of CHOPS by discovering the association rules between reservoir properties and oil production from CHOPS well data. However, it leaves reservoir engineers with big challenging tasks to find interesting rules, understand …
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Data mining with bilattices
… in database after Agrawal and Sirkant introduced association rules in data mining and proposed Apriori for mining association. However, most of the works focuses on finding patterns on itemsets, especially associations between items. With the fast development of high technologies and large scale …
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Data mining using L-fuzzy concept analysis.
Association rules in data mining are implications between attributes of objects that hold in all instances of the given data. These rules are very useful to determine the properties of the data such as essential features of products that determine the purchase decisions of customers. Normally the …
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An association rule dynamics and classification approach to event detection and tracking in Twitter.
… real-life topics over a specified period using Association Rule Mining. We termed our novel methodology Transaction-based Rule Change Mining (TRCM). TRCM is a system built on top of the Apriori method of Association Rule Mining to extract patterns of Association Rules changes in tweets hashtag …
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