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Correlation Associative Rule Induction Algorithm Using ACO

C. Nalini
2016 Circuits and Systems  
It is important to consider the null invariance property when selecting appropriate interesting measures in the correlation analysis. Real time data set has mixed attributes.  ...  The large data sets may have many null-transactions. A null-transaction is a transaction that does not contain any of the itemsets being examined.  ...  The heuristic function guides an ant to move forward in the search space. The algorithm use correlation based heuristic function to choose the term (attribute-value pair).  ... 
doi:10.4236/cs.2016.710244 fatcat:lzpyxzdw5ve3zi6cacz7je63pq

An Interactive Clustering Methodology for High Dimensional Data Mining

Haibo Wang, Bahram Alidaee, Fred W. Glover, Gary A. Kochenberger
2004 Pacific Asia Conference on Information Systems  
The similarity index is calculated with proposed formulation for both continuous-scaled and nominal-scaled attributes.  ...  This study develops an interactive clustering model and methodology for high dimensional data.  ...  Clustering in data mining is intended to divide objects into groups so that objects within groups are homogeneous and have a high degree of similarity.  ... 
dblp:conf/pacis/WangAGK04 fatcat:xhz5y5q76bdhnmmsoll6j3uuvy

Active Preference Learning for Ranking Patterns

Vladimir Dzyuba, Matthijs Van Leeuwen, Siegfried Nijssen, Luc De Raedt
2013 2013 IEEE 25th International Conference on Tools with Artificial Intelligence  
Pattern mining provides useful tools for exploratory data analysis. Numerous efficient algorithms exist that are able to discover various types of patterns in large datasets.  ...  In particular we focus on Subgroup Discovery, a specific pattern mining task.  ...  Matthijs van Leeuwen is supported by a Rubicon grant of the Netherlands Organisation for Scientific Research (NWO).  ... 
doi:10.1109/ictai.2013.85 dblp:conf/ictai/DzyubaLNR13 fatcat:ve4kndjkubd6rh3gaztwyrtuvu

Mining citizen science data to predict orevalence of wild bird species

Rich Caruana, Mohamed Elhawary, Art Munson, Mirek Riedewald, Daria Sorokina, Daniel Fink, Wesley M. Hochachka, Steve Kelling
2006 Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '06  
We compare a variety of methods for measuring attribute importance with respect to the probability of a bird being observed at a feeder and present initial results for the impact of important attributes  ...  We show how data mining can be successfully applied, enabling the ecologists to discover unanticipated relationships.  ...  There are 600+ BCR-species pairs with sufficient data for a data mining analysis.  ... 
doi:10.1145/1150402.1150527 dblp:conf/kdd/CaruanaEMRSFHK06 fatcat:uch3bjx6z5by5a7hge7hsjrqv4

A Heuristic Storage Location Assignment Based on Frequent Itemset Classes to Improve Order Picking Operations

Yue Li, Francis A. Méndez-Mediavilla, Cecilia Temponi, Junwoo Kim, Jesus A. Jimenez
2021 Applied Sciences  
This paper proposes a heuristic method to optimize the order picking distance based on frequent itemset grouping and nonuniform product weights.  ...  This heuristic is applied to a numerical case using data obtained from a real distribution center in the food retail industry.  ...  The proposed heuristic uses association rule mining (ARM), a well-known data mining algorithm.  ... 
doi:10.3390/app11041839 fatcat:nph66bsitbaeffpc4u7vosk3vm

Deep Web Content Mining

Shohreh Ajoudanian, Mohammad Davarpanah Jazi
2009 Zenodo  
In this paper we present a novel correlation mining algorithm that matches correlated attributes with smaller cost.  ...  After extracting information with parsing approach, we use a new data mining algorithm to match a large number of schemas in databases at a time.  ...  In past years correlation mining approach is used for matching attributes [1] , [10] , [11] , [12] .  ... 
doi:10.5281/zenodo.1075729 fatcat:gu64ismpfrb47hykoskn4vhzay

Interactive Learning of Pattern Rankings

Vladimir Dzyuba, Matthijs van Leeuwen, Siegfried Nijssen, Luc De Raedt
2014 International journal on artificial intelligence tools  
This shows that machine learning techniques in general, and active preference learning in particular, are promising building blocks for interactive data mining systems.  ...  Pattern mining provides useful tools for exploratory data analysis. Numerous e cient algorithms exist that are able to discover various types of patterns in large datasets.  ...  Acknowledgments This work was supported by the Research Foundation-Flanders by means of two Postdoc grants and the project "Instant Interactive Data Exploration" and by the European Commission under the  ... 
doi:10.1142/s0218213014600264 fatcat:z3ierx45cjejbhmxirkg6qhbs4

Context-Based Distance Learning for Categorical Data Clustering [chapter]

Dino Ienco, Ruggero G. Pensa, Rosa Meo
2009 Lecture Notes in Computer Science  
Clustering data described by categorical attributes is a challenging task in data mining applications.  ...  In this paper, we propose a method to learn a context-based distance for categorical attributes.  ...  Periklis Andritsos who provided the implementation of LIMBO, and Elena Roglia for stimulating discussions. Ruggero G. Pensa is co-funded by Regione Piemonte.  ... 
doi:10.1007/978-3-642-03915-7_8 fatcat:mdcy5zasgnhhdahrfh4zclf4w4

Instance-based attribute identification in database integration

Cecil Eng H. Chua, Roger H. L. Chiang, Ee-Peng Lim
2003 The VLDB journal  
In the first experiment, the heuristic rules derived for attribute classification were evaluated on 119 attributes from nine public domain data sets.  ...  Unlike other attribute identification methods that match only single attributes, our method matches attribute groups for integration.  ...  Our heuristics (Sect. 3) have only been applied for the data sets presented in Sect. 6.  ... 
doi:10.1007/s00778-003-0088-y fatcat:ofqncr2irnazllmmkks4tc4f4u

Detecting clusters in moderate-to-high dimensional data

Hans-Peter Kriegel, Peer Kröger, Arthur Zimek
2008 Proceedings of the VLDB Endowment  
measures for local correlation of attributes • drawback: all approaches suffer from locality assumption • successfully employing PCA in correlation clustering in "really" high-dimensional data requires  ...  algorithms compute overlapping clusters • Many approaches compute all clusters in all subspaces -These methods usually implement a bottom-up search strategy á la itemset mining -These methods usually  ...  Evaluation • So, any of the proposed methods is based on at least one assumption because otherwise, it would not be applicable  ... 
doi:10.14778/1454159.1454223 fatcat:yybhhzcqjjeknb5yerhx6yzk4y

Cluster-grouping: from subgroup discovery to clustering

Albrecht Zimmermann, Luc De Raedt
2009 Machine Learning  
We introduce the problem of cluster-grouping and show that it can be considered a subtask in several important data mining tasks, such as subgroup discovery, mining correlated patterns, clustering and  ...  The results indicate that the CG algorithm can be useful as a generic local pattern mining component in a wide variety of data mining and machine learning algorithms.  ...  , and the editor of this paper for his constructive feedback and patience.  ... 
doi:10.1007/s10994-009-5121-y fatcat:qsir34gphff4ladbefvxi3bfwa

Cluster-Grouping: From Subgroup Discovery to Clustering [chapter]

Albrecht Zimmermann, Luc De Raedt
2004 Lecture Notes in Computer Science  
We introduce the problem of cluster-grouping and show that it can be considered a subtask in several important data mining tasks, such as subgroup discovery, mining correlated patterns, clustering and  ...  The results indicate that the CG algorithm can be useful as a generic local pattern mining component in a wide variety of data mining and machine learning algorithms.  ...  , and the editor of this paper for his constructive feedback and patience.  ... 
doi:10.1007/978-3-540-30115-8_56 fatcat:vpkgvqhh75aldpyb36aewcugwq

An Improved Pearson's Correlation Proximity-Based Hierarchical Clustering for Mining Biological Association between Genes

P. M. Booma, S. Prabhakaran, R. Dhanalakshmi
2014 The Scientific World Journal  
A search made with heuristic for standard biological process measures only the gene expression level, threshold, and response time.  ...  Additionally, the Seed Augment algorithm adopts average linkage methods on rows and columns in order to expand a seed PCPHC model into a maximal global PCPHC (GL-PCPHC) model and to identify association  ...  The temporal and spatial correlations and the reliability in the trajectory of datasets of moving objects as shown in [12] are repeatedly modelled as sequential patterns for use in data mining.  ... 
doi:10.1155/2014/357873 pmid:25136661 pmcid:PMC4083291 fatcat:5oym3gmo7jeedkgmy3dcrk5zi4

Heuristic Measures of Interestingness [chapter]

Robert J. Hilderman, Howard J. Hamilton
1999 Lecture Notes in Computer Science  
We demonstrate that for sample data sets, the order in which some of the measures rank summaries is highly correlated.  ...  All sixteen heuristics rank less complex summaries (i.e., those with few tuples and/or few non-ANY attributes) as most interesting.  ...  Ranking summaries generated from databases is useful in the context of descriptive data mining tasks where a single data set can be generalized in many different ways and to many levels of granularity.  ... 
doi:10.1007/978-3-540-48247-5_25 fatcat:bwhebac2ejg5lphpl34dzhprd4

Assessing event correlation in non-process-aware information systems

Ricardo Pérez-Castillo, Barbara Weber, Ignacio García-Rodríguez de Guzmán, Mario Piattini, Jakob Pinggera
2012 Journal of Software and Systems Modeling  
This paper adapts a previous correlation algorithm and incorporates it into a technique for obtaining event logs from traditional systems.  ...  Business process mining is a solution to discover business processes. These techniques take event logs recorded by process-aware information systems.  ...  In turn, NumberPI (Eq. 6) is heuristically assessed as the distinct attribute values for all the different couples of events (executed in a row) containing both attributes.  ... 
doi:10.1007/s10270-012-0285-5 fatcat:2nqfyq3wcffgnaqid6rj4sdeoe
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