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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  
In our proposed approach, we are using UP growth with Genetic Algorithm.  ...  Hence an emerging technique called Utility-based data mining is used in data mining processes.The utility mining not only considers the frequency but also see the utility associated with the itemsets.The  ...  A novel approach THUI (Temporal High Utility Itemsets)-Mine has been used for mining temporal high utility itemsets from data streams. III.  ... 
doi:10.17762/ijritcc2321-8169.150394 fatcat:kj5qs6ohfjfmdcj66hr2i2aieq

An ontology-driven method for hierarchical mining of temporal patterns: application to HIV drug resistance research

Rashmi Raj, Martin J O'Connor, Amar K Das
2007 AMIA Annual Symposium Proceedings  
To make use of such knowledge about research data, we have developed an ontology-driven temporal mining method, called ChronoMiner. Most mining algorithms require data be inputted in a single table.  ...  In this paper, we present the application of our method to the discovery of temporal associations between newly arising mutations in the HIV genome and past drug regimens.  ...  Acknowledgements This work was supported in part by a Universitywide AIDS Research Program Award and a PhRMA Foundation Starter Grant Award in Informatics. We thank Dr.  ... 
pmid:18693909 pmcid:PMC2655843 fatcat:nhoscmzqfreldcusnjesgdxxgy

Application of Genetic Algorithm for the Discovery of Hidden Temporal Patterns in Earthquakes Data

Sohair F Higazi, Walaa Eddien Abdelhadi, Rania M Shalaby
2013 Pakistan Journal of Statistics and Operation Research  
Time Series Data mining (TSDM) is one of the most widely used technique that deals with temporal patterns.  ...  Genetic algorithm (GA) is a predictive TSDM search technique that is used for solving search/optimization problems.  ...  DM has two main functions: descriptive data mining via decision trees and neural networks (Feng and , and predictive data mining via Genetic algorithm, genetic programming, regression and correlation analysis  ... 
doi:10.18187/pjsor.v9i3.275 fatcat:snhb4pnchrh4lekf2dl6pfgvby

Optimal Water Allocation Using Data Mining Techniques- A Survey

Sara Kutty T K, Hanumanthappa M
2018 International Journal of Emerging Research in Management and Technology  
This survey paper elaborates the theoretical background of data-mining models and highlights the applications in knowledge data discovery from a water resources database, in particularly on optimal water  ...  All living beings depend on water and it is used for agriculture, environment, household, power generation, industries, navigation, recreation etc.  ...  If there is not much variations in the parameters used in the water management study mapping of temporal and spatial knowledge can be used instead of numerical modelling.  ... 
doi:10.23956/ijermt.v6i8.143 fatcat:rwu343b3qffqvi42kow7wmm4ua

A survey of temporal knowledge discovery paradigms and methods

J.F. Roddick, M. Spiliopoulou
2002 IEEE Transactions on Knowledge and Data Engineering  
At the same time, interest in temporal databases has been increasing and a growing number of both prototype and implemented systems are using an enhanced temporal understanding to explain aspects of behavior  ...  This paper investigates the confluence of these two areas, surveys the work to date, and explores the issues involved and the outstanding problems in temporal data mining.  ...  ACKNOWLEDGMENTS This work was conceived while the authors attended the Integrating Spatial and Temporal Databases Workshop at Schloss Dagstuhl in November 1998.  ... 
doi:10.1109/tkde.2002.1019212 fatcat:vcofptm3i5aozake7s35w2pbde


Ann L. Hild, Nancy L. Shaw, Ginger B. Paige, Mary I. Williams
2009 Journal American Society of Mining and Reclamation  
However, in order to attain functioning systems, attention to structure and process must compliment existing efforts. We ask how to use a systems approach to enhance reclamation success.  ...  Research should assist managers with integrating spatial and temporal variability of ecosystem processes into long-term management planning.  ...  the exchange of genetic materials in out-crossing species.  ... 
doi:10.21000/jasmr09010578 fatcat:yglwq3suene7xfpdhyxtoi52jy

Page 9231 of Mathematical Reviews Vol. , Issue 2001M [page]

2001 Mathematical Reviews  
dynamically reconfigurable web server groups using the DyGOP model (65-77); Alessandra Raffaeta and Thom Friihwirth, Two se- mantics for temporal annotated constraint logic programming (78- 92); M.  ...  Orgun, Applied hidden periodicity analysis for mining discrete-valued time series databases (182-196); Ion Androutsopoulos, Temporal meaning representations in a natural language front-end (197-213); Win  ... 

GPR: A Data Mining Tool Using Genetic Programming

Balasubramaniam Ramesh
2001 Communications of the Association for Information Systems  
In this paper, we present a novel approach to data mining that uses the principles of genetic programming to generate production rules from databases.  ...  We illustrate the use of genetic programming for data mining with a detailed case study in Section V of a real-life application in military manpower management.  ...  GPR: A Data Mining Tool Using Genetic Programming by B. Ramesh and T.  ... 
doi:10.17705/1cais.00506 fatcat:xbklzxyinjgtfj7ifchudm4j74

A new approach to the spatial analysis of temporal change using nodes and neural nets

Peter J Halls, Fiona A C Polack, Simon E M O'Keefe
2000 CyberGeo  
Martin, L, Moal, F, Vrain, C, 1998, A Relational Data Mining Tool Based on Genetic Programming, Principles of Data Mining and Knowledge Discovery. 2nd European Symposium, PKDD'98, Nantes, Springer Verlag  ...  Claramunt, C., and Bai Li, 1999, A Multi-scale Approach to the Propagation of Temporal Constraints in GIS.  ... 
doi:10.4000/cybergeo.911 fatcat:7cf2swpza5ccxjppgvvqmqlc6i

Higher Order Programming to Mine Knowledge for a Modern Medical Expert System [article]

Nittaya Kerdprasop, Kittisak Kerdprasop
2011 arXiv   pre-print
Modern healthcare organizations regularly generate huge amount of electronic data stored in the databases.  ...  In this paper, we propose the design of a novel medical expert system based on a logic-programming framework.  ...  , and constraint mining [7] , i.e. mining with some specified constraints to obtain relevant knowledge.  ... 
arXiv:1107.4651v1 fatcat:midttzcevbddplkaqogp2e6vcq

Evolutionary computation in medicine: an overview

Carlos Andrés Peña-Reyes, Moshe Sipper
2000 Artificial Intelligence in Medicine  
We begin by outlining the basic workings of six types of evolutionary algorithms: genetic algorithms, genetic programming, evolution strategies, evolutionary programming, classifier systems, and hybrid  ...  This paper provides an overview of evolutionary computation as applied to problems in the medical domains.  ...  Programs in genetic programming may be expressed in any language in principle.  ... 
doi:10.1016/s0933-3657(99)00047-0 pmid:10767613 fatcat:zz5hgh56zvfzrluxkj2a7krm3a

Data Transformation and Semantic Log Purging for Process Mining [chapter]

Linh Thao Ly, Conrad Indiono, Jürgen Mangler, Stefanie Rinderle-Ma
2012 Lecture Notes in Computer Science  
Existing process mining approaches are able to tolerate a certain degree of noise in process log.  ...  In this paper, we address these challenges by introducing data transformation and pre-processing steps that improve and ensure the quality of mined models for existing process mining approaches.  ...  In particular, for cleaning data from errors or impossible values, integrity constraints have been utilized in the database area [11] .  ... 
doi:10.1007/978-3-642-31095-9_16 fatcat:ygwpzjpkarhwbd7ddubr2qaowi

A Review on Data mining from Past to the Future

Venkatadri. M, Lokanatha C. Reddy
2011 International Journal of Computer Applications  
Data mining is the knowledge discovery process by analyzing the large volumes of data from various perspectives and summarizing it into useful information.  ...  Hence, this paper discusses the various improvements in the field of data mining from past to the present and explores the future trends.  ...  Recently, various soft computing methodologies have been applied in data mining such as fuzzy logic, rough set, neural networks, evolutionary computing (Genetic Algorithms and Genetic Programming), and  ... 
doi:10.5120/1961-2623 fatcat:6w4qyny3ibcuvp732x47f2f344

Geospatial decision support for drought risk management

Steve Goddard, Sherri K. Harms, Stephen E. Reichenbach, Tsegaye Tadesse, William J. Waltman
2003 Communications of the ACM  
Thus, new research investigates data mining and retrieval, constraint databases, spatial analysis, data interpolation, and visualization.  ...  amounts of data in various databases maintained throughout the country, the spatial extend of the data, and the extended temporal lag between related events.  ... 
doi:10.1145/602421.602442 fatcat:pg5p7hp2nzaobev7zn7wxzsvaq

An Enhanced Algorithm for Association Rule Mining in Huge Temporal Database

Abdel Rahman Mahmoud, Dr. Nagy Ramadan, Abdel Moniem Helmy
2019 Zenodo  
The current algorithms of association rule mining has limitations in handling temporal data in different data sets for these two main reasons.  ...  The discovery of the association relationship among huge temporal database has been legendary to be helpful in selective selling, call analysis and business management.  ...  The problem of mining temporal association rules is to find all association rules in the database that satisfies at least three user-specified constraints: minimum support, minimum confidence and time  ... 
doi:10.5281/zenodo.3372570 fatcat:34v4zq44frbhxkfj2rx6ze73f4
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