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Analytical Study of Association Rule Mining Methods in Data Mining

Bhavesh M. Patel, Vishal H. Bhemwala, Dr. Ashok R. Patel
2018 International Journal of Scientific Research in Computer Science Engineering and Information Technology  
In data processing, the foremost common and effective technique is to spot frequent pattern victimization association rule mining.  ...  It's true that one paper isn't enough for complete analysis of all smart researches, however it'll facilitate in future to urge right direction towards association rule mining analysis for fascinating,  ...  They also proposed an efficient algorithm RE (Recursive Estimation) to estimate the support of itemsets under this framework. For geographically distributed data sets, Ashrafi M.Z.  ... 
doi:10.32628/cseit1833244 fatcat:ndopsdk6enfr7hphvuhmiym43e

Cross-Mining Binary and Numerical Attributes

Gemma C. Garriga, Hannes Heikinheimo, Jouni K. Seppanen
2007 Seventh IEEE International Conference on Data Mining (ICDM 2007)  
We consider the problem of relating itemsets mined on binary attributes of a data set to numerical attributes of the same data.  ...  From the viewpoint of itemset mining, the task is to select a small collection of interesting itemsets using the numerical attributes; from the viewpoint of the numerical attributes, the task is to constrain  ...  Imagine a rectangular grid drawn on a map, each of whose cells corresponds to a row in a database, recording what bird species occur in the cell, and the geographical coordinates of the cell as well as  ... 
doi:10.1109/icdm.2007.32 dblp:conf/icdm/GarrigaHS07 fatcat:vey4b2pmjfckvkdmmyrhybmnma

A framework for regional association rule mining and scoping in spatial datasets

Wei Ding, Christoph F. Eick, Xiaojing Yuan, Jing Wang, Jean-Philippe Nicot
2010 Geoinformatica  
We evaluate our approach in a real-world case study to identify spatial risk patterns from arsenic in the Texas water supply.  ...  The motivation for regional association rule mining and scoping is driven by the facts that global statistics seldom provide useful insight and that most relationships in spatial datasets are geographically  ...  A transaction is not naturally defined in spatial space.  ... 
doi:10.1007/s10707-010-0111-6 fatcat:uqsbt5o6ijca3pbrwah7gasmhq

Mini track: 'data and process mining'

S. Piramuthu, H.M. Chung
2004 37th Annual Hawaii International Conference on System Sciences, 2004. Proceedings of the  
They present a generic spatial decision-making process and a domain-independent Flexible Spatial Decision Support System framework and architecture to support this process.  ...  Theoretical and methodological exploration in the previous years motivates us to further investigate the various and richer data and knowledge representation schemes such as Web, multimedia, and geographic  ...  They present a generic spatial decision-making process and a domain-independent Flexible Spatial Decision Support System framework and architecture to support this process.  ... 
doi:10.1109/hicss.2004.1265197 dblp:conf/hicss/PiramuthuC04 fatcat:bychholugnhf5m7u6b27i4slfm

Mining Volunteered Geographic Information datasets with heterogeneous spatial reference

Sadiq Hussain, G.C. Hazarika
2011 International Journal of Advanced Computer Science and Applications  
However, these methods cannot directly be applied to a spatiotemporal sequence because of the fuzziness of spatial locations in the sequence.  ...  When the information created online by users has a spatial reference, it is known as Volunteered Geographic Information (VGI).  ...  Ding et al. (2006) introduce a framework to mine regional association rules based on prior clustering to find patterns in sub regions.  ... 
doi:10.14569/specialissue.2011.010319 fatcat:37733sl44bf5xegs5p7dr5b4eu

Spatio-sequential patterns mining: Beyond the boundaries

Hugo Alatrista-Salas, Sandra Bringay, Frédéric Flouvat, Nazha Selmaoui-Folcher, Maguelonne Teisseire
2016 Intelligent Data Analysis  
In addition, as our approach generates a lot of patterns which are not easy to interpret by the experts, we propose in this paper, an interestingness measure to overcome this problem.  ...  . / Spatio-sequential patterns mining: Beyond the boundaries we define a new type of spatiotemporal pattern called Spatio-Sequential Patterns or simply S2P, which allows us to discover the temporal evolution  ...  A formal framework is established to define the S2P generically.  ... 
doi:10.3233/ida-160806 fatcat:sagjohtixjdjlioaqqhx6dsk4y

Association Rule Mining Method Based on the Similarity Metric of Tuple-Relation in Indoor Environment

Naixia Mou, Hongen Wang, Hengcai Zhang, Xin Fu
2020 IEEE Access  
, conditional probability, and multiple potential association information among POI sets, to form a new support-confidence-relation constraint framework and to improve the quality and application value  ...  In this paper, a new index, tuple-relation, is defined, which reflects the association strength between POI sets in indoor environment.  ...  ACKNOWLEDGMENT The authors are grateful to Shanghai Palmap Science & Technology Company Limited for providing indoor trajectory data support, which has made this research possible.  ... 
doi:10.1109/access.2020.2980952 fatcat:ifkrcjpxgjcy3atwv6i6jjnery

Mining Social Structure on Context Objects Database

Tingting Fu
2015 Open Automation and Control Systems Journal  
To support social information routing, this paper brought forward an unbalanced sliding window based social structure mining algorithm.  ...  We also discussed the application of the COD such as mining social structure using sliding window model.  ...  Temporal-spatial database, including time and space element is a three-dimensional or four-dimensional database by adding temporal dimensional on traditional spatial database.  ... 
doi:10.2174/1874444301507012090 fatcat:by2t7oydgbeslmyn5jwrgwx5gq

Efficiently Mining Interesting Emerging Patterns [chapter]

Hongjian Fan, Kotagiri Ramamohanarao
2003 Lecture Notes in Computer Science  
Knowledge Discovery in Databases (KDD), or Data Mining is used to discover interesting or useful patterns and relationships in data, with an emphasis on large volume of observational databases.  ...  A reliable classifier should be tolerant to a reasonable level of noise.  ...  A set enumeration tree (Rymon 1993) is usually used to systematically explore the itemset space.  ... 
doi:10.1007/978-3-540-45160-0_19 fatcat:5dx6cgvn6jeb7pxzckxsc3ov3e

Parallel and Distributed Data Mining: An Introduction [chapter]

Mohammed J. Zaki
2000 Lecture Notes in Computer Science  
The explosive growth in data collection in business and scientific fields has literally forced upon us the need to analyze and mine useful knowledge from it.  ...  This chapter presents a survey on large-scale parallel and distributed data mining algorithms and systems, serving as an introduction to the rest of this volume.  ...  We hope that this volume, representing the state-of-the-art in parallel and distributed mining methods, will be successful in bringing to surface the requirement and challenges in large-scale parallel  ... 
doi:10.1007/3-540-46502-2_1 fatcat:3mmcofbadbas7f7r5y5opxxwdy

Database Issues in Knowledge Discovery and Data Mining

Chris Rainsford, John Roddick
1999 Australasian Journal of Information Systems  
Data mining is useful in situations where the volume of data is either too large or too complicated for manual processing or, to a lesser extent, where human experts are unavailable to provide knowledge  ...  The success already attained by a wide range of data mining applications has continued to prompt further investigation into alternative data mining techniques and the extension of data mining to new domains  ...  Spatial Data Spatial databases model multi-dimensional space and are typically found within geographical information systems (CIS) Roddick 1998, 1999) .  ... 
doi:10.3127/ajis.v6i2.310 fatcat:57zzkqzw2bdgndhjp5tumgicd4

Novel Algorithm for Mining ENSO-Oriented Marine Spatial Association Patterns from Raster-Formatted Datasets

Xue Cunjin, Liao Xiaohan
2017 ISPRS International Journal of Geo-Information  
among geographical parameters have been obtained, and the other is that great challenges exist in exploring the spatial association patterns among multiple geographical parameters.  ...  In addition, taking one given item as a core, the mining algorithm may easily visualize and find the interesting spatial association patterns from raster-formatted datasets.  ...  The other explores marine spatial association patterns against ENSO events in the Pacific Ocean.  ... 
doi:10.3390/ijgi6050139 fatcat:keepouvn4ncl3o3xschkrdzwu4

Mining Multivariate Associations within GIS Environments [chapter]

Ickjai Lee
2004 Lecture Notes in Computer Science  
Association rules mining is a core technique in data mining and is a solid candidate for the cause-effect analysis of large geospatial databases.  ...  As geospatial data grows explosively, needs for the incorporation of data mining techniques into Geographic Information Systems (GISs) are in great demand.  ...  We use ArcView GIS for our experiments and use its scripting language AVENUE and dynamic link library to implement the three-phase geospatial mining framework.  ... 
doi:10.1007/978-3-540-24677-0_109 fatcat:muqh5rszijcyjgekw2uukaa3hy

A Novel Approach of Multilevel Positive and Negative Association Rule Mining for Spatial Databases [chapter]

L. K. Sharma, O. P. Vyas, U. S. Tiwary, R. Vyas
2005 Lecture Notes in Computer Science  
A pruning strategy is used in our approach to efficiently reduce the search space. Further efficiency is gained by interestingness measure.  ...  Spatial data mining is a demanding field since huge amounts of spatial data have been collected in various applications, ranging form Remote Sensing to GIS, Computer Cartography, Environmental Assessment  ...  of the relation and points to a geographic map.  ... 
doi:10.1007/11510888_61 fatcat:bu3tv3veurgy3i3ffulo57spdi

Using Ontology Based Semantic Association Rule Mining in Location Based Services

Ali Mousavi, Andrew Hunter, Mohammad Akbari
2016 International Journal of Data Mining & Knowledge Management Process  
The techniques are good at extracting patterns, but they are hard to interpret in a specific application domain.  ...  Finally, a system prototype was developed to evaluate the behavior models in different aspects using one of the location based services.  ...  Therefore, in this work we extend a typical DM framework by considering ontologies in the knowledge discovery process.  ... 
doi:10.5121/ijdkp.2016.6501 fatcat:mfhhcreawvejvba3rebzjipumy
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