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Data Mining in Translational Bioinformatics

Xing-Ming Zhao, Jean X. Gao, Jose C. Nacher
2014 BioMed Research International  
Translational bioinformatics is an emerging field that aims to exploit various kinds of biological data for useful knowledge to be translated into clinical practice.  ...  The rapid accumulation of various kinds of biological data requires more powerful statistical approaches to extract useful signals from the huge amount of noisy data. L.  ... 
doi:10.1155/2014/656519 pmid:25025066 pmcid:PMC4082924 fatcat:ul2xb46oinc7bophrtazz6dm4y

Data Mining Applications in Big Data

Lidong Wang, Guanghui Wang
2015 Computer Engineering and Applications Journal  
Data mining is a process of extracting hidden, unknown, but potentially useful information from massive data. Big Data has great impacts on scientific discoveries and value creation.  ...  This paper introduces methods in data mining and technologies in Big Data. Challenges of data mining and data mining with big data are discussed.  ...  Frequent itemset mining (FIM) is a method to extract knowledge from data.  ... 
doi:10.18495/comengapp.v4i3.155 fatcat:w5gqffk5u5aahld5gzp354d6wu

Data Mining Industrial Applications [chapter]

Waldemar Wojcik, Konrad Gromaszek
2011 Knowledge-Oriented Applications in Data Mining  
Considering the golden triangle of research, knowledge and innovation, data mining approach should find also practical application in supervisory and control systems.  ...  The latest publications from 2010 concern a new approach based on particle swarm optimization algorithm for clustering problems description (Durán, O. et al., 2010) or knowledge induction from data to  ...  Data Mining Industrial Applications, Knowledge-Oriented Applications in Data Mining, Prof.  ... 
doi:10.5772/13573 fatcat:cbd3g2orfzgcth2qjvhzycukrq

Data Mining in Healthcare using Hybrid Approach

Monica Sharma, Rajdeep Kaur
2015 International Journal of Computer Applications  
Extracting useful data and making scientific decision for diagnosis and treatment of disease from the database increasingly becomes necessary.  ...  Modern medicine generates a great deal of information stored in the medical database.  ...  It is said that it is defined as to mine the knowledge from complex data and mined information can be used for various applications.  ... 
doi:10.5120/ijca2015906539 fatcat:bmqm44jlhfg2blpm57gn4o2cmi

Application Of Data Mining In Bioinformatics [article]

Khalid Raza
2012 arXiv   pre-print
The application of data mining in the domain of bioinformatics is explained. It also highlights some of the current challenges and opportunities of data mining in bioinformatics.  ...  This article highlights some of the basic concepts of bioinformatics and data mining. The major research areas of bioinformatics are highlighted.  ...  Mining biological data helps to extract useful knowledge from massive datasets gathered in biology, and in other related life sciences areas such as medicine and neuroscience.  ... 
arXiv:1205.1125v1 fatcat:mpri2z7itbgqfhcezd7bq7m5he

Role of Cloud Computing in Data Mining

Garima Gupta, Dr. Rajesh Pathak
2016 International Journal Of Engineering And Computer Science  
Data Mining is a procedure of extracting potentially helpful information from raw data, so as to get better the excellence of the information service.  ...  Cloud computing can give infrastructure to huge and multifaceted data of data mining, in addition to innovative demanding issues for data mining of cloud computing research are emerged.  ...  Privacy of data is a major concern in people who use public cloud services, so an approach is planned to keep data safe and secure also keeping sure only authorized personnel can access data.  ... 
doi:10.18535/ijecs/v5i4.01 fatcat:tnbhiatg4rg4xjx3crvcv5w724

DATA MINING IN RELATIONAL SYSTEMS

Valentin Filatov, Valerii Semenets, Oleg Zolotukhin
2020 Сучасний стан наукових досліджень та технологій в промисловості  
have been developed for the use of a relational data model for building functional association rules in problems of mining relational databases, conclusion: the main source of knowledge for database operation  ...  To develop a method for evaluating a relational data model and a procedure for constructing functional associative rules when solving problems of mining relational databases.  ...  Data Mining is a process of discovering in "raw data" previously unknown non-trivial practically useful and accessible interpretation of knowledge necessary for decision-making in various spheres of human  ... 
doi:10.30837/itssi.2020.13.065 fatcat:mq2plfw4rfhgde5eqg2xnil4sq

SECURED DISCLOSURE OF SENSITIVE DATA IN DATA MINING TECHNIQUES

Gurusamy
2012 Journal of Computer Science  
order to produce meaningful results. Based on the analysis of shortcomings of earlier technologies this study proposes a new method for securing numerical and categorical data.  ...  In this method the categorical data is converted into Binary form and perturbation based noise is introduced as a security method based on the security level anticipated.  ...  This Hybrid data transformation approach can be used to transform the binary data to preserve the privacy of the original data.  ... 
doi:10.3844/jcssp.2012.2042.2052 fatcat:i4ho5aumzvg3hefpdx4dpurhia

Data Mining in Finance
English

Sahil Kadam, Manan Raval
2014 International Journal of Engineering Trends and Technoloy  
Data mining techniques provide a great aid in financial accounting and fraud detection due to their classification and prediction abilities.  ...  This paper provides the relevant background knowledge, presents the various Data Mining technique's as well as implementing them in computers, and applies them to current glitches in finance, including  ...  The naive approach to data mining in finance assumes that somebody can provide a cookbook instruction on "how to achieve the best result".  ... 
doi:10.14445/22315381/ijett-v16p275 fatcat:rb3ibdnjenb2digspgsfm6k5za

Data Mining in Web Applications [chapter]

Julio Ponce, Alberto Hernndez, Alberto Ochoa, Felipe Padilla, Alejandro Padilla, Francisco lvarez, Eunice Ponce de Le
2009 Data Mining and Knowledge Discovery in Real Life Applications  
The contribution of this paper is the use of hybrid technologies in online assessments as a new approach for remote identification of students on real time.  ...  A knowledge discovery tool, WebLogMiner, is discussed in (Zaiane et al., 1998) , which uses OLAP and data mining techniques for mining web server log files.  ... 
doi:10.5772/6454 fatcat:kog666xfhrcxpe3rbsy4zza67a

Data mining in soft computing framework: a survey

S. Mitra, S.K. Pal, P. Mitra
2002 IEEE Transactions on Neural Networks  
The present article provides a survey of the available literature on data mining using soft computing.  ...  A categorization has been provided based on the different soft computing tools and their hybridizations used, the data mining function implemented, and the preference criterion selected by the model.  ...  that useful knowledge is derived from the data.  ... 
doi:10.1109/72.977258 pmid:18244404 fatcat:wz6gxwj3mvgexl6slz3dl4q54i

Text Mining in Big Data Analytics

Hossein Hassani, Christina Beneki, Stephan Unger, Maedeh Taj Mazinani, Mohammad Reza Yeganegi
2020 Big Data and Cognitive Computing  
Text mining in big data analytics is emerging as a powerful tool for harnessing the power of unstructured textual data by analyzing it to extract new knowledge and to identify significant patterns and  ...  In accordance with this, more than 200 academic journal articles on the subject are included and discussed in this review; the state-of-the-art text mining approaches and techniques used for analyzing  ...  Etzioni [136] referred to web mining as the application of data mining techniques to automatically discover and extract knowledge in a website, while Cooley et al.  ... 
doi:10.3390/bdcc4010001 fatcat:6fvmne7f2fbovjp4na5hl2tmv4

Data Mining Applications: Promise and Challenges [chapter]

Rukshan Athauda, Menik Tissera, Chandrika Fernando
2009 Data Mining and Knowledge Discovery in Real Life Applications  
We observe three main approaches taken in practice to determine goals for a DM initiative: • Using domain knowledge to determine goals for the data mining experiment: The use of domain knowledge to determine  ...  A hybrid of the above-mentioned approaches may be considered in determing a suitable goal for data mining.  ...  Data Mining and Knowledge Discovery in Real Life Applications This book presents four different ways of theoretical and practical advances and applications of data mining in different promising areas like  ... 
doi:10.5772/6449 fatcat:ghch3jygknganaxb5wmfnidwhu

Effects of Data Imputation Methods on Data Missingness in Data Mining

Marvin L. Brown, Chien-Hua Mike Lin
2011 GSTF International Journal on Computing  
The purpose of this paper is to study the effectiveness  ...  As the application of Data Mining to large data sets grew more widely practiced, the process was separated into a series of logical procedures.  ...  Since our goal is to present a superior approach for effective Knowledge Discovery in the presence of various levels of missing data to practitioners when confronted with the real-world problem of data  ... 
doi:10.5176/2010-2283_1.2.53 fatcat:n37f7z4r5beddcatompyzvbfli

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.  ...  Here during this analytical paper, we have been tried to incorporate survey of analysis systematically towards association rule mining from last many years to till date from totally different researchers  ...  Data mining is usually known as knowledge discovery in database (KDD). KDD is one of the important process of extracting raw data to get fruitful knowledge which can be useful in DSS.  ... 
doi:10.32628/cseit1833244 fatcat:ndopsdk6enfr7hphvuhmiym43e
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