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An Empirical Research on Spatial Data Mining
2019
VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE
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A lot of effort put forth to summarize various spatial based knowledge discovery in data mining such as based on generalization, clustering based, spatial associations based, and approximations and aggregations ...
Spatial data mining is a process of extracting expertise from large volumes of spatial data collected from different applications such as remote sensing, geographic systems and social networks, etc. ...
All algorithms adopted the mined rules and the user started the discovery process with an explicitly SQL-like query [10] . ...
doi:10.35940/ijitee.l1136.10812s219
fatcat:zp546xjq4fge5l5czo2vhpys2u
A Review Study of various Data Mining Classification and Clustering Techniques
2017
International Journal of Trend in Scientific Research and Development
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Data mining application includes a variety of methodologies that have been developed by commercial & research centers. This technique has been used for industrial, commercial and scientific purposes. ...
The WEKA contains a set of visualization tools & algorithms for data analysis and predictive modeling, together with graphical user interfaces for simple access to this functionality. ...
Data Mining (DM) represents a set of specific methods and algorithms aimed solely at extracting patterns from raw data. Data mining sometimes is also called knowledge discovery in databases (KDD). ...
doi:10.31142/ijtsrd135
fatcat:faftldo3tvdbtlmxuglcwcbzmy
Knowledge Discovery in Databases and Libraries
ENGLISH
2011
DESIDOC Journal of Library & Information Technology
ENGLISH
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So, intelligent tools for automated data mining and knowledge discovery are needed to deal with enormous data. ...
As library and information centres are considered the backbone of knowledge organisation, knowledge discovery in databases (KDD) is also getting attention of library and information scientists. ...
Hitherto, data mining tools mostly adopt techniques from statistics 10 , neural networks 11 , and visualisation 12 to classify data and extract patterns 13 . ...
doi:10.14429/djlit.31.6.1319
fatcat:cpjjesfgfbc6dndvlczmkhwabe
Discovering spatio-social motifs of electoral support using discriminative pattern mining
2010
Proceedings of the 1st International Conference and Exhibition on Computing for Geospatial Research & Application - COM.Geo '10
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, Chapman & Hall/CRC, Data Mining and Knowledge
Discovery Series, September, 2012.
91. ...
Symposium on Data, Privacy, and E-Commerce (ISDPE'10).
10. ...
doi:10.1145/1823854.1823898
dblp:conf/comgeo/StepinskiSD10
fatcat:lt77jekqtzagtnemf7ll3mcryq
An Updated Bibliography of Temporal, Spatial, and Spatio-temporal Data Mining Research
[chapter]
2001
Lecture Notes in Computer Science
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Data mining and knowledge discovery have become important issues for research over the past decade. ...
It is therefore not surprising that the increased interest in temporal and spatial data has led also to an increased interest in mining such data. ...
Trans-
actions on Knowledge and Data Engineering 10(2): 222-237. ...
doi:10.1007/3-540-45244-3_12
fatcat:wr3inqmxdfbv3bi6r6ozf2luau
Knowledge management and data mining for marketing
2001
Decision Support Systems
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A systematic methodology that uses data mining and knowledge management techniques is proposed to manage the marketing knowledge and support marketing decisions. ...
Current emphasis on customer relationship management makes the marketing function an ideal application area to greatly benefit from the use of data mining tools for decision support. ...
More recent research on data mining w x and knowledge discovery 20,26,27 has further enhanced our understanding of the application of data mining and the knowledge discovery process. ...
doi:10.1016/s0167-9236(00)00123-8
fatcat:fdptozecrred5kyykzylnxbg2e
Parallelism in Knowledge Discovery Techniques
[chapter]
2002
Lecture Notes in Computer Science
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Knowledge discovery in databases or data mining is the semiautomated analysis of large volumes of data, looking for the relationships and knowledge that are implicit in large volumes of data and are 'interesting ...
Data mining and knowledge discovery on large amounts of data can benefit of the use of parallel computers both to improve performance and quality of data selection. ...
Knowledge discovery in databases, also called data mining, is the semi-automated analysis of large volumes of data, looking for the relationships and knowledge that are implicit in large volumes of data ...
doi:10.1007/3-540-48051-x_14
fatcat:qsrphyqkgna7zg3hcpkizrenr4
Survey of Process of Data Discovery and Environmental Decision Support Systems
2021
VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE
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The process of data discovery is an approach to extracting knowledge, valid, and usable information from large amounts of data, using automatic or semi-automatic methods. ...
This article is an inventory of the different information extraction processes encountered in the literature for different fields of application and for the development of environmental informatics. ...
COMPARATIVE STUDY OF THE DIFFERENT DATA DISCOVERY PROCESSES The KDDM "Knowledge Discovery and Data Mining" processes of Fayyad et al. 2 and the CRISP-DM "Cross Industry Standard Process for Data Mining ...
doi:10.35940/ijitee.g8905.0510721
fatcat:vdbysezzzbbmba7aonyslk4eiu
TEXT AND DATA MINING FOR BIOMEDICAL DISCOVERY
2012
Biocomputing 2013
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Work presented in this session includes data mining techniques applied to the discovery of 3-way genetic interactions and to the analysis of genetic data in the context of electronic medical records (EMRs ...
The biggest challenge for text and data mining is to truly impact the biomedical discovery process, enabling scientists to generate novel hypothesis to address the most crucial questions. ...
knowledge into data mining". ...
doi:10.1142/9789814447973_0036
fatcat:f522y2grifc6xeh7hs245doscy
Distributed data mining systems: techniques, approaches and algorithms
2018
MATEC Web of Conferences
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data into useful information and knowledge, where Data mining uncovers interesting patterns and relationships hidden in a large volume of raw data and big data is a new term used to identify the datasets ...
In this paper, we will discuss Distributed Data Mining systems, approaches, Techniques and algorithms to deal with distributed data to discover knowledge from distributed data in an effective and efficient ...
Knowledge discovery in databases (KDD) The terms knowledge discovery and data mining are distinct. KDD refers to the overall process of discovering useful knowledge from data [3, 4] . ...
doi:10.1051/matecconf/201821004038
fatcat:lwc7lwrnpvakxnjxzymuxjm24y
Técnica de mineração de dados: uma revisão da literatura
2009
Acta Paulista de Enfermagem
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Buscou-se uma coleta ampla utilizando as palavras data mining e mineração de dados, abrangendo o período de 1999 a 2008. ...
Este artigo teve como objetivo realizar uma revisão da literatura sobre a técnica de mineração de dados (Data Mining - DM) nas bases de dados abrangendo o Literatura Latino-Americana e do Caribe em Ciências ...
RESULTS The theme was divided into three topics: Knowledge discovery in databases. Data Mining Tasks and Data Mining Methods. ...
doi:10.1590/s0103-21002009000500014
fatcat:zhastpusovgmtkpg3s5gxkew6m
Text and data mining for biomedical discovery
2013
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
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Work presented in this session includes data mining techniques applied to the discovery of 3-way genetic interactions and to the analysis of genetic data in the context of electronic medical records (EMRs ...
The biggest challenge for text and data mining is to truly impact the biomedical discovery process, enabling scientists to generate novel hypothesis to address the most crucial questions. ...
background knowledge into data mining". ...
pmid:23424141
pmcid:PMC6230431
fatcat:3on3xcf3wvgsfm66e4xns4ycdy
Discrimination Aware Data Mining in Internet of Things (IoT)
2017
International Journal of Computer Applications
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However, it comes across problem of big data and extracting knowledge from such data using data mining techniques. ...
This paper describes discrimination discovery and prevention issues faced by IoT. This paper also specifies the huge future research avenue related to discrimination aware data mining in IoT. ...
Data mining is a technique to extract useful knowledge from raw data. ...
doi:10.5120/ijca2017912894
fatcat:5frrihdbova2dkrv4y2qqyyddm
Importance of Process Mining for Big Data Requirements Engineering
2020
International Journal of Computer Science & Information Technology (IJCSIT)
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Data processing can be benefited by process mining, and in turn, helps to increase the productivity of the big data projects. ...
Employing traditional data processing techniques lacks the invention of useful information because of the main characteristics of big data, including high volume, velocity, and variety. ...
The main characteristics of big data technologies are 5V's: volume, velocity, variety, volatility, and variability [4, [9] [10] [11] . ...
doi:10.5121/ijcsit.2020.12401
fatcat:6fvruwovunfddh7fk22yeztjeq
Importance of Process Mining for Big Data Requirements Engineering
2020
Zenodo
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Data processing can be benefited by process mining, and in turn, helps to increase the productivity of the big data projects. ...
Employing traditional data processing techniques lacks the invention of useful information because of the main characteristics of big data, including high volume, velocity, and variety. ...
The main characteristics of big data technologies are 5V's: volume, velocity, variety, volatility, and variability [4, [9] [10] [11] . ...
doi:10.5281/zenodo.4011576
fatcat:byk4mpi2cneynnu7osiu6xh5bq
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