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Evaluation of Customer Ratings on Restaurant by Clustering Techniques using R
2019
Zenodo
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So, in this paper we try to collect data from a restaurant in Bangalore and evaluate its popularity based on ratings given by customers. ...
In today's modern times food and lifestyle has become integral part of human system. People today aspire for good day at work and sumptuous and delicious food to eat at the end of the day. ...
While data mining and
knowledge discovery (or KDD) are
frequently treated as synonyms, data
mining is actually part of the knowledge
discovery process. ...
doi:10.5281/zenodo.3262091
fatcat:ihckvuce2bgzbiulksk4rbqgsi
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. ...
Wu, "Mining Emerging Patterns by Streaming Feature Selection,"
The 18 th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, pp. 60-68, Beijing,
China, August, 2012. ...
doi:10.1145/1823854.1823898
dblp:conf/comgeo/StepinskiSD10
fatcat:lt77jekqtzagtnemf7ll3mcryq
Guest editors' introduction: special section of selected papers from ECML-PKDD 2012
2013
Data mining and knowledge discovery
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After the conference, the authors of the four most highly evaluated data mining and knowledge discovery papers were invited to submit a significantly extended version of their paper to this special section ...
The 2012 instalment of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD) was held in Bristol, United Kingdom during the week of 24- ...
Data Mining and Knowledge Discovery to publish their work. ...
doi:10.1007/s10618-013-0325-y
fatcat:5ebgjvuaw5a7jooc4refoq5yca
Astroinformatics: A 21st Century Approach to Astronomy
[article]
2009
arXiv
pre-print
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Data volumes from multiple sky surveys have grown from gigabytes into terabytes during the past decade, and will grow from terabytes into tens (or hundreds) of petabytes in the next decade. ...
Astroinformatics includes a set of naturally-related specialties including data organization, data description, astronomical classification taxonomies, astronomical concept ontologies, data mining, machine ...
Co-Signers and Contributing Authors: Astronomers: Kirk D. Borne ...
arXiv:0909.3892v1
fatcat:h3xzbdh4crclffxv7qslsbtvsi
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
A Conceptual Framework for Data Quality in Knowledge Discovery Tasks (FDQ-KDT): A Proposal
2015
Journal of Computers
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The most fundamental challenge is to explore the large volumes of data and extract useful knowledge for future actions through data mining and data science methodologies. ...
We proposed a conceptual framework for data quality in knowledge discovery tasks based on CRISP-DM, SEMMA and Data Science, considering the issues of ESE Taxonomy. ...
for technical support and Colciencias for PhD scholarship granted to MsC. ...
doi:10.17706/jcp.10.6.396-405
fatcat:5saz4blr5nccfdgveh4uhb243m
Data Mining in Education : A Review on the Knowledge Discovery Perspective
2014
International Journal of Data Mining & Knowledge Management Process
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In this paper, we have reviewed Knowledge Discovery perspective in Data Mining and consolidated different areas of data mining, its techniques and methods in it. ...
Knowledge Discovery in Databases is the process of finding knowledge in massive amount of data where data mining is the core of this process. ...
KNOWLEDGE DISCOVERY IN DATABASES Data mining and knowledge discovery in databases are related to each other and to other related fields such as machine learning, statistics, and databases. ...
doi:10.5121/ijdkp.2014.4504
fatcat:5wldcmrngvgojhnwbb5nafze4a
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
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. ...
Moreover, techniques like process mining [15] and tools like smart grids [28] can be employed to accelerate the process of knowledge discovery from big data. ...
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. ...
Moreover, techniques like process mining [15] and tools like smart grids [28] can be employed to accelerate the process of knowledge discovery from big data. ...
doi:10.5281/zenodo.4011576
fatcat:byk4mpi2cneynnu7osiu6xh5bq
The role of domain knowledge in data mining
1995
Proceedings of the fourth international conference on Information and knowledge management - CIKM '95
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The ideal situation for a Data Mining or Knowledge Discovery system would be for the user to be able to pose a query of the form "Give me something interesting that could be useful" and for the system ...
We discuss how each one of these types of domain knowledge is incorporated into the discovery process within the EDM (Evidential Data Mining) framework for Data Mining proposed earlier by the authors [ ...
The Northern Ireland Housing Executive, ICL Ltd. and Kainos Software Ltd. are the industrial partners in the project. ...
doi:10.1145/221270.221321
dblp:conf/cikm/AnandBH95
fatcat:ws5ggzakerdfdksabsa5z62nna
Page 265 of Behavior Research Methods Vol. 39, Issue 2
[page]
2007
Behavior Research Methods
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Statis¬ tical themes and lessons for data mining. Data Mining & Knowledge Discovery, 1,11-28.
Han, j., & Kamber, M. (2001). Data mining; Concepts and techniques. San Francisco: Morgan Kaufmann. ...
Handbook of data mining and knowledge discovery. Oxford: Oxford University P^ss.
Langley, P., & Simon, H. A. (1995). Applications of machine learning and rule induction. ...
Decomposition in data mining: a medical case study
2001
Data Mining and Knowledge Discovery: Theory, Tools, and Technology III
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Decomposition is a tool for managing complexity in data mining and enhancing the quality of knowledge extracted form large databases. ...
A typology of decomposition approaches applicable to data mining is presented. ...
One way to reduce computational complexity of knowledge discovery with data mining algorithms and decision making based on the acquired knowledge is to reduce the volume of data to be processed at a time ...
doi:10.1117/12.421082
dblp:conf/dmkdttt/Kusiak01
fatcat:k6w5jsw3ovbc3fg5rplh4wcwvy
Enhancing Big Data Value Using Knowledge Discovery Techniques
2016
International Journal of Information Technology and Computer Science
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Knowledge Presentation: Presentation of the knowledge extracted in the data mining step in a format easily understood by the user is an important issue in knowledge discovery. ...
The primary motivation behind mining bio logical Data is to use automated databases to store, compose, and index of data. This data empowers the discovery of new organic bits of knowledge. ...
doi:10.5815/ijitcs.2016.08.01
fatcat:uwc5is2zlbghrhnuzdp4oazerm
Logistic Model Tree and Decision Tree J48 Algorithms for Predicting the Length of Study Period
2020
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic
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Therefore, the current study used available student data, both academic and non-academic, using data mining. Two model classifications were used, i.e. Logistic Model Tree (LMT) and Decision Tree J48. ...
The study was aimed to compare LMT and Decision Tree J48 algorithm in predicting the length of student's study and to find out the influence factors. ...
and Development No. 28/E/KPT/2019 with Indonesian Scientific Index (SINTA) journal-level of S5, starting from Volume 6 (1) 2018 to Volume 10 (1) 2022. ...
doi:10.33558/piksel.v8i1.2018
fatcat:fiago5ghbrfb3odhgtkxcajdwu
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