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WIS: Weighted Interesting Sequential Pattern Mining with a Similar Level of Support and/or Weight

Unil Yun
2007 ETRI Journal  
Using these measures, weighted interesting sequential patterns with similar levels of support and/or weight are mined.  ...  This strategy provides basic pruning; however, it cannot mine correlated sequential patterns with similar support and/or weight levels.  ...  Previous sequential pattern mining algorithms could not detect sequential patterns with support and/or weight affinity.  ... 
doi:10.4218/etrij.07.0106.0067 fatcat:i6om3ipyazfhnob2je6uemyvny

On Identifying Useful Patterns to Analyze Products in Retail Transaction Databases

Unil YUN
2009 IEICE transactions on information and systems  
In this paper, we suggest weighted support affinity pattern mining in which a new measure, weighted support confidence (ws-confidence) is developed to identify correlated patterns with the weighted support  ...  In previous mining approaches, patterns with the weak affinity are found even with a high minimum support.  ...  Weighted support affinity pattern mining can give answers about the comparative analysis queries and discover interesting patterns which cannot be detected by the conventional sequential pattern mining  ... 
doi:10.1587/transinf.e92.d.2430 fatcat:x233wcwrznhazcle7ycufrouxq

IWFPM: Interested Weighted Frequent Pattern Mining with Multiple Supports

Xuyang Wei, Zhongliang Li, Tengfei Zhou, Haoran Zhang, Guocai Yang
2015 Journal of Software  
Our paradigm is to assign appropriate minimum support (minsup) and weight for each item, which reduces the number of unnecessary patterns.  ...  This paper presents an efficient approach for mining users' interest weighted frequent patterns from a transactional database.  ...  Acknowledgment This work is supported by the key technology integration and demonstration of rural Internet information services (2012BAD35B08), Chongqing, China  ... 
doi:10.17706/jsw.10.1.9-19 fatcat:kckwhlzr4bb2npxsxci5kti6ni

Extraction of High Utility Itemsets using Utility Pattern with Genetic Algorithm from OLTP System

A Saranya
2015 International Journal on Recent and Innovation Trends in Computing and Communication  
To analyse vast amount of data, Frequent pattern mining play an important role in data mining.  ...  In practice, Frequent pattern mining cannot meet the challenges of real world problems due to items differ in various measures.  ...  In the paper [16] , Yun proposed weighted frequent pattern mining with length decreasing support constraints.  ... 
doi:10.17762/ijritcc2321-8169.150394 fatcat:kj5qs6ohfjfmdcj66hr2i2aieq

BicNET: Flexible module discovery in large-scale biological networks using biclustering

Rui Henriques, Sara C. Madeira
2016 Algorithms for Molecular Biology  
Methods: This work proposes Biclustering NETworks (BicNET), a biclustering algorithm to discover non-trivial yet coherent modules in weighted biological networks with heightened efficiency.  ...  The application of BicNET on protein interaction and gene interaction networks from yeast, E. coli and Human reveals new modules with heightened biological significance.  ...  It was supported by national funds through Fundação para a Ciência e Tecnologia with reference UID/ CEC/50021/2013, the Ph.D. grant SFRH/BD/75924/2011 to RH and the sabbatical leave grant SFRH/BSAB/1427  ... 
doi:10.1186/s13015-016-0074-8 pmid:27213009 pmcid:PMC4875761 fatcat:54uw36eqafdabel2rjjdrvniqa

Computational cell biology

2003 ChoiceReviews  
We propose a method for learning linguistic patterns with a method based on sequential patterns enhanced by a recursive mining of patterns.  ...  DMT4SP (Data Mining Tool For Sequential Patterns) 3 5.  ... 
doi:10.5860/choice.40-2772 fatcat:d73sxzlqk5hldghxuy3huohqau

Computational Cell Biology

S. Schnell
2003 Briefings in Bioinformatics  
We propose a method for learning linguistic patterns with a method based on sequential patterns enhanced by a recursive mining of patterns.  ...  DMT4SP (Data Mining Tool For Sequential Patterns) 3 5.  ... 
doi:10.1093/bib/4.1.87 fatcat:szv5ps3zovawbhrotxdktxrgwe

Computational Cell Biology

J. Sneyd
2003 Mathematical Medicine and Biology  
We propose a method for learning linguistic patterns with a method based on sequential patterns enhanced by a recursive mining of patterns.  ...  DMT4SP (Data Mining Tool For Sequential Patterns) 3 5.  ... 
doi:10.1093/imammb/20.1.131 fatcat:2cmq6zcr6bb7holvjztfu26i6y

Computational Cell Biology

J. Sneyd
2003 Mathematical Medicine and Biology  
We propose a method for learning linguistic patterns with a method based on sequential patterns enhanced by a recursive mining of patterns.  ...  DMT4SP (Data Mining Tool For Sequential Patterns) 3 5.  ... 
doi:10.1093/imammb20.1.131 fatcat:6sml7goilrdvjphvvhsuerpyuy

Mining web content usage patterns of electronic commerce transactions for enhanced customer services

Sylvanus A. Ehikioya, Jinbo Zeng
2021 Engineering Reports  
Table 6 shows the top five supported Web object sequential patterns discovered using the prefixSpan algorithm with minimal sequential pattern length of three.  ...  We use the PrefixSpan algorithm, 18 a high efficient frequent sequence mining algorithm, to mine Web content usage log to find long sequential access patterns with high support.  ... 
doi:10.1002/eng2.12411 fatcat:yp57yt6jkvgv7h6oz6vvzxk4fm

A Comprehensive Survey on Affinity Analysis, Bibliomining, and Technology Mining: Past, Present, and Future Research

Md. Rashadur Rahman, Mohammad Shamsul Arefin, Sanjida Rahman, Afsana Ahmed, Tahsina Islam, Pranab Kumar Dhar, Oh-Jin Kwon
2022 Applied Sciences  
Three interesting fields in data mining are affinity analysis, bibliomining, and technology mining.  ...  Affinity analysis provides data mining techniques to determine the similarity among objects; bibliomining is a combination of data mining, bibliometrics, and data warehousing; technology mining is a research  ...  [29] We selected 29 papers on affinity analysis, 16 papers on bibliomining, and 8 papers on technology mining from various publishers, including IEEE, ACM, ScienceDirect, Springer- Conflicts of Interest  ... 
doi:10.3390/app12105227 fatcat:xe5vqxyizvdc5obyeg4zuiocai

Color Crafting: Automating the Construction of Designer Quality Color Ramps [article]

Stephen Smart, Keke Wu, Danielle Albers Szafir
2019 arXiv   pre-print
Visualizations often encode numeric data using sequential and diverging color ramps.  ...  We do this using an algorithmic approach that models designer practices by analyzing patterns in the structure of designer-crafted color ramps.  ...  This work was supported by NSF Award # 1657599.  ... 
arXiv:1908.00629v1 fatcat:x3oeyptzybgj7emm434cqi2vrq

Finding the Most Descriptive Substructures in Graphs with Discrete and Numeric Labels [chapter]

Michael Davis, Weiru Liu, Paul Miller
2013 Lecture Notes in Computer Science  
We support our findings with experiments on transaction graphs and single large graphs from the domains of physical building security and digital forensics, measuring the effect on runtime, memory requirements  ...  and coverage of discovered patterns, relative to the unconstrained approach.  ...  Acknowledgments We would like to thank Erich Schubert at Ludwig-Maximilians Universität München for assistance with verifying our LOF implementation and providing us with the RP + PINN + LOF implementation  ... 
doi:10.1007/978-3-642-37382-4_10 fatcat:hvz3v7p3orbwnofe5dv5je7mre

Finding the most descriptive substructures in graphs with discrete and numeric labels

Michael Davis, Weiru Liu, Paul Miller
2013 Journal of Intelligent Information Systems  
We support our findings with experiments on transaction graphs and single large graphs from the domains of physical building security and digital forensics, measuring the effect on runtime, memory requirements  ...  and coverage of discovered patterns, relative to the unconstrained approach.  ...  Acknowledgments We would like to thank Erich Schubert at Ludwig-Maximilians Universität München for assistance with verifying our LOF implementation and providing us with the RP + PINN + LOF implementation  ... 
doi:10.1007/s10844-013-0299-7 fatcat:eqrepgrfi5bi3pwcoiol6ygura

Declarative Process Mining: Reducing Discovered Models Complexity by Pre-Processing Event Logs [chapter]

Pedro H. Piccoli Richetti, Fernanda Araujo Baião, Flávia Maria Santoro
2014 Lecture Notes in Computer Science  
The approach was evaluated through a case study with an artificial event log and its results showed complexity reduction on the resulting hierarchical model.  ...  The discovery of declarative process models by mining event logs aims to represent flexible or unstructured processes, making them visible to business and improving their manageability.  ...  [7] proposed an approach to search for sequential patterns on event logs and replace them with abstract activities.  ... 
doi:10.1007/978-3-319-10172-9_28 fatcat:6545u6h43veablomyx7js6lnie
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