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Data Mining Applications And Techniques: A Systematic Review

Fabio T. Matsunaga, Jacques D. Brancher, Rosângela M. Busto
2015 Zenodo  
There are several techniques and tasks related to data mining, such as clustering, classification, association rules, time series forecasting and regression model, which is being applied in several multidisciplinary  ...  Also, data mining techniques and tasks are not being used in an isolated way or individually, but also as being a module or part of a project of an expert system, by combining mathematical, computational  ...  Acknowledgements This work has received funding from the CNPq project number 487430/2013-1. Fabio Takeshi Matsunaga is supported by CNPq grant, process number 381241/2014-9.  ... 
doi:10.5281/zenodo.59454 fatcat:g3uzwkokrvbsfhwwqcbcagefda

◾ Knowledge Discovery Applications [chapter]

2012 Service-Oriented Distributed Knowledge Discovery  
The scope of the series includes, but is not limited to, titles in the areas of data mining and knowledge discovery methods and applications, modeling, algorithms, theory and foundations, data and knowledge  ...  This series aims to capture new developments and applications in data mining and knowledge discovery, while summarizing the computational tools and techniques useful in data analysis.  ...  In particular, we would like to thank Mario Cannataro, Eugenio Cesario, Carmela Comito, Antonio Congiusta, Marco Lackovic, and Oreste Verta.  ... 
doi:10.1201/b12990-15 fatcat:vte5ahxzbvgizetdwimfxfic54

Knowledge Discovery From Production Databases For Hierarchical Process Control

Pavol Tanuska, Pavel Vazan, Michal Kebisek, Dominika Jurovata
2013 Zenodo  
One of the main project goals was the proposal of knowledge discovery model for process control. Specifics data mining methods and techniques was used for defined problems of the process control.  ...  The paper gives the results of the project that was oriented on the usage of knowledge discoveries from production systems for needs of the hierarchical process control.  ...  One of the existing and suitable methods is KDD -knowledge discovery in databases. III.  ... 
doi:10.5281/zenodo.1088949 fatcat:pxvodh2ez5faxo5ymof7k7wxmu

YALE

Ingo Mierswa, Michael Wurst, Ralf Klinkenberg, Martin Scholz, Timm Euler
2006 Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '06  
These case studies cover tasks like feature engineering, text mining, data stream mining and tracking drifting  ...  A rapid prototyping system should support maximal re-use and innovative combinations of existing methods, as well as simple and quick integration of new ones.  ...  These plugins currently cover text, audio, time series, and multimedia processing, data stream simulation and concept drift handling, clustering, and distributed data mining.  ... 
doi:10.1145/1150402.1150531 dblp:conf/kdd/MierswaWKSE06 fatcat:6oz263ifqjdrdbse6dtixb7kza

An approach for increasing the level of accuracy in Supply Chain simulation by using patterns on input data

Markus Rabe, Anne Antonia Scheidler
2014 Proceedings of the Winter Simulation Conference 2014  
Therefore an approach for using techniques of Knowledge Discovery in Databases is introduced to derive logical relations from the data.  ...  SC simulation needs a large amount of input data -especially in times of big data, in which the data is often approximated by statistical distributions from real world observations.  ...  COMBINATION -SIMULATION AND KNOWLEDGE DISCOVERY Combining DES and KDD to support a higher accuracy of simulation input seems to be a promising opportunity.  ... 
doi:10.1109/wsc.2014.7020037 dblp:conf/wsc/RabeS14 fatcat:lt2tykqbejcw3jorddrkwtnlea

Hands-on Process Discovery with Python - Utilizing Jupyter Notebook for the Digital Assistance in Higher Education

Adrian Rebmann, Alexander Beuther, Steffen Schumann, Peter Fettke
2020 Modellierung  
From this, a meaningful event log is to be generated and consequently, process model discovery techniques are to be applied.  ...  To this end, we present an exercise, which consists to a large extent of the data preparation of process execution data, distributed in database tables.  ...  Especially in process model discovery, proven concepts, existing models in different representations, real-world data and software technologies must be combined to create process models.  ... 
dblp:conf/modellierung/RebmannBSF20 fatcat:n2qyemdgojaihmcuryu3xm7dwm

Parallel and Distributed Data Mining [chapter]

Sujni Paul
2011 New Fundamental Technologies in Data Mining  
Life Cycle of knowledge presentation Data cleaning is to remove noise and inconsistent data. Data integration is to combine data from multiple data sources, such as a database and data warehouse.  ...  In fact, the term "knowledge discovery" is more general than the term "data mining."  ...  The series of books entitled by "Data Mining" address the need by presenting in-depth description of novel mining algorithms and many useful applications.  ... 
doi:10.5772/13124 fatcat:ejqjwjbluvcopmwtyrmmapawxu

How Close to Reality is the "as-is" Business Process Simulation Model?

Bartlomiej Gawin, Bartosz Marcinkowski
2015 Organizacija  
Results: The simulation model has been constructed with data from the WfMS database, observations, staff knowledge and their experience.  ...  Background and Purpose: Business process simulation (BPS) model is based on real-life data form sources like databases, observations and interviews.  ...  Exploration of the data, also known as Knowledge Discovery in Databases, is a multi-step process that involves raw data transformation from the event log into actionable knowledge about the organization  ... 
doi:10.1515/orga-2015-0013 fatcat:2obvi7tqu5ex7mqv5j52nq57aa

Decision Support Systems Classification in Industry

Musbah Jumah Aqel
2019 Periodicals of Engineering and Natural Sciences (PEN)  
The next part of the research provides a discussion of the decision making process and the data mining phases as these relate to DSS.  ...  ; degree of guidance; and, degree of non-procedurality.  ...  Data Mining: In this step of the process, the data mining phase is executed such that the data leads to information that is valuable in the discovery of knowledge.  ... 
doi:10.21533/pen.v7i2.550 fatcat:ao26tvdjxzgbbboay3chqtujoq

Mobility, Data Mining and Privacy: The GeoPKDD Paradigm [chapter]

Fosca Giannotti, Roberto Trasarti
2010 Proceedings of the 2009 SIAM Conference on "Mathematics for Industry"  
The objective of the GeoPKDD (Geographic Privacy-aware Knowledge Discovery and Delivery), a project funded by European Commission under the Future and emerging technologies (FET) program of the 6th Framework  ...  (FP6), has been to discover useful knowledge about human movement behavior from mobility data, while preserving the privacy of the people under observation.  ...  knowledge discovery process, from raw data to knowledge.  ... 
doi:10.1137/1.9781611973303.2 fatcat:4ig3w67fbrbqvibvq3iwlw7qly

Personalized Teaching Platform Based on Web Data Mining

Lan-zhong Wang
2016 International Journal of Emerging Technologies in Learning (iJET)  
contains knowledge base, individual database, WDM and web server four modules.  ...  The web data mining is used for the construction of the system and by analyzing the character of web data mining (WDM) and the essence of personalization teaching and instruction.  ...  For such as time series flow, uncertainty time series, multi time series and more complex structures such as time series data mining techniques, the conventional time-series data mining technology is relatively  ... 
doi:10.3991/ijet.v11i11.6253 fatcat:j5r4shjdpnh7vbbeq54uugthrm

Mining knowledge in astrophysical massive data sets

Massimo Brescia, Giuseppe Longo, Fabio Pasian
2010 Nuclear Instruments and Methods in Physics Research Section A : Accelerators, Spectrometers, Detectors and Associated Equipment  
Data Mining, or Knowledge Discovery in Databases, while being the main methodology to extract the scientific information contained in such MDS (Massive Data Sets), poses crucial problems since it has to  ...  In the present paper we summarize the present status of the MDS in the Virtual Observatory and what is currently done and planned to bring advanced Data Mining methodologies in the case of the DAME (DAta  ...  the California Institute of Technology, is financed through grants from the Italian Ministry of Foreign Affairs, the European projects VO-TECH and VO-AIDA (Astronomical Observatory of Trieste) and by  ... 
doi:10.1016/j.nima.2010.02.002 fatcat:nvp5xhcvjneflalc5aub6zrc4e

A survey of temporal knowledge discovery paradigms and methods

J.F. Roddick, M. Spiliopoulou
2002 IEEE Transactions on Knowledge and Data Engineering  
AbstractÐWith the increase in the size of data sets, data mining has recently become an important research topic and is receiving substantial interest from both academia and industry.  ...  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  ...  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

Exploiting Data Mining Techniques For Improving the Efficiency of Time Series Data

TARUN DHAR DIWAN, PRADEEP CHOUKSEY, R. S. THAKUR, BHARAT LODHI
2014 International journal of computer and communication technology  
Data mining techniques is the exploration and analysis of data in order to discover useful information from huge databases.  ...  The aim of this paper is to determine the feasibility and effectiveness of data mining techniques in time series data and produce solutions for this purpose.  ...  Using better quality of data influences the whole process of knowledge discovery, takes less time in cleaning and integration, and assures better results from the mining process. 4.  ... 
doi:10.47893/ijcct.2014.1260 fatcat:xyk7jmlq4fgsfd7wenrgij5blm

A Search Method to Support Temporal Transcriptome Analysis

Guenter Tusch, Shahrzad Eslamian
2019 Studies in Health Technology and Informatics  
Recently, there has been an increasing interest in mining time series databases with a focus on data representation.  ...  The method accounts for various challenges that can be found in publicly available gene expression databases.  ...  Methods Finding patterns of interest in time series databases (Query by Content) can be described as follows: Given query time series and some similarity measure, find the most similar time series in a  ... 
doi:10.3233/shti190559 pmid:31438256 fatcat:zt2taqtf3vdr3eytvp6gk7mcqi
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