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  • Big Data Hadoop Aggregation Techniques
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    of three algorithmsunder different values of α in Fig 4 by changing itsvalue from 02 to 10 A small value of α indicates alower aggregation efficiency for the intermediate dataWe observe that network traffic increases as the growthof under both DA and HRA In particular when α is 02 DA achieves the lowest traffic cost of 11 10 5...

  • Urban Data Mining Using Emergent SOM
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    The further aggregation leads to the five classes of Table 2 The classed are con- Urban Data Mining Using Emergent SOM 317 Fig 7 Localisation of...

  • Data minig with Big data analysis
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    Mar 24 2015 0183 32 Developing a safe and sound information sharing protocol is a major challenge To support Big Data mining high-performance computing platforms are required which impose systematic designs to unleash the full power of the Big Data Big data as an emerging trend and the need for Big data mining is rising in all science and engineering domains 5...

  • Gaussian Processes for Active Data Mining of Spatial
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    The Spatial Aggregation Language SAL Bailey-Kellogg et al 1996 supports struc-ture discovery in spatial datasets through a small set of generic operators parameterized with domain-specific knowledge on uniform data typ These operators and data types mediate increasingly abstract descriptions of the input data see Fig 2 to form...

  • Data Mining and Data Warehouse
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    summary or aggregation operations Fig 1 Data mining process et Pandey Mohan Bisht and Pant 156 5 Data Mining Data mining is defined as extracting information from a large set of data Data mining is mining the knowledge from data from large amount of database 6...

  • Data Mining with Semantic Features Represented as
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    data mining with ontologi The method is illustrated via examples of K-Means clustering and Association Rule mining Keywords Semantic Similarity Ontologies Taxonomies Semantic Vectors 1 Introduction Data mining with taxonomies has been studied as an approach to include background knowledge in the mining process...

  • Data aggregation processes a survey a taxonomy and
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    Nov 16 2018 0183 32 Data aggregation processes are essential constituents for data management in modern computer systems such as decision support systems and Internet of Things systems many with timing constraints Understanding the common and variable features of data aggregation processes especially their implications to the time-related properties is key to improving the quality of the designed system...

  • Data Mining techniques
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    Data Mining Interpretation Evaluation Fig Process used in data mining 3 WORKING While large-scale information technology has been evolving separate transaction and analytical systems data mining provides the link between the two Data mining software analyzes relationships and patterns in stored transaction data based on open-ended user...

  • Data Aggregation
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    Summarizing data finding totals and calculating averages and other descriptive measures are probably not new to you When you need your summaries in the form of new data rather than reports the process is called aggregation Aggregated data can become the basis for additional calculations merged with other datasets used in any way that other...

  • Preparing Data Sets for the Data Mining Analysis using the
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    Data mining refers to the finding of relevant and useful information from databas A data mining project consists of several phas Fig1 Example of Horizontal Aggregation 3 LITERATURE SURVEY The programming of the clustering algorithm with SQL queries is explored in 2 which shows that the horizontal...

  • Overview Applications of Data Mining In Health Care The
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    It is known from Fig 2 below that data mining is one of the important processes of knowledge discovery From the definitions by the scholars it is clear that the usage of data mining is an analysis process within a series of knowledge discovery 12 As time changes the term data mining...

  • Comparative Analysis of Data Mining Algorithms for
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    d Data mining algorithms to estimate LOS 31 Aggregation of Attributes Health care data often have many characteristics and attribut Some of these attributes are irrelevant and can be removed and some are closely related and thus can be grouped A few of the attributes in Clinics data set are illustrated in Fig1...

  • Data mining notes
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    Jul 03 2013 0183 32 data mining notes 1 avccollege of engineering mannampandal mayiladuthurai-609 305 course material for the subject of sub name cs1011 data warehousing and data mining sem vii department computer science and engineering academic year 2013-2013 name of the faculty parvathim designation asstprofessor 1...

  • Content Aggregation in Natural Language Hypertext
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    content aggregation in the context of generating hypertext summaries of OLAP and data mining discoveri Two key properties make this approach innovative and interesting 1 it encapsulates aggregation inside the sentence planning component and 2 it relies on a domain independent algorithm working on a data structure that...

  • Data sets preparing for Data mining analysis by SQL
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    Data sets preparing for Data mining analysis by SQL Horizontal Aggregation VNikitha1 PJhansi2 KNeelima3 DAnusha4 Department Of IT GPullaiah College of Engineering and Technology Kurnool JNTU Anatapur Andhra Pradesh India Abstract - Data mining is essentially employed in getting ready information sets for data processing analysis...

  • Gaussian Process Models of Spatial Aggregation Algorithms
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    through a spatial aggregation hierarchy 1 Introduction Many important tasks in data mining scientific computing and qualitative modeling involve the successive and system 173 atic spatial aggregation and redescription of data into higher-level objects For instance consider the characterization of...

  • Data Warehousing and Data Mining
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    What is Data Mining DataMining means extracting data from a large dataset DataMining also known as knowledge discovery from data Similar meaning to DataMining are knowledge mining from data knowledge extraction data/pattern analysis data archeology and data dredging DataMining is a synonym for Knowledge Discovery from data...

  • Analysis of agriculture data using data mining techniques
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    Jul 05 2017 0183 32 In agriculture sector where farmers and agribusinesses have to make innumerable decisions every day and intricate complexities involves the various factors influencing them An essential issue for agricultural planning intention is the accurate yield estimation for the numerous crops involved in the planning Data mining techniques are necessary approach for accomplishing practical and...

  • Data Preprocessing in Data Mining
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    Data Mining Data Preprocessing In this tutorial we are going to learn about the data preprocessing need of data preprocessing data cleaning process data integration process data reduction process and data transformations process Submitted by Harshita Jain on January 05 2020 In the previous article we have discussed the Data Exploration with which we have started a detailed...

  • PDF Data mining techniques and applications
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    Oct 21 2020 0183 32 Data mining is a process which finds useful patterns from large amount of data The paper discusses few of the data mining techniques algorithms and some of...

  • Content aggregation in natural language hypertext
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    Content Aggregation in Natural Language Hypertext Summarization of OLAP and Data Mining Discoveries Jacques Robin Universidade Federal de Pernambuco UFPE Centro de Informfitica CIn Caixa Postal 7851 50732-970 - Recife Brazil jr diufpebr Eloi...

  • Data Mining tools and techniques in construction by
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    Fig01 Typical combination of data mining and risk management9 In the particular field of construction the amount of data available structured or unstructured ELT data integration and aggregation It is a necessary step for understanding the basic features and attributes of data to determine its best use The business value of data...

  • An experimental investigation of the impact of aggregation
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    Jul 01 2005 0183 32 Moreover aggregation enables predictions that go beyond a low granularity Aggregation-based prediction enables prediction of performance for sales stock market index inventory level etc over the following n days where n is a function of the aggregation level For example using a prediction based on 4-day averages a given predicted price represents the...

  • US20040225638A1
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    The proposed computerized method and system is adapted for analyzing a multitude of items in a high dimensional n-dimensional data space D n each described by n item featur The method uses a mining function f with at least one control parameter P i controlling the target of the data mining function A first step is selecting a transformation function T for reducing dimensions of the n...

  • An efficient aggregation scheme resisting on malicious
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    Jul 01 2020 0183 32 Malicious data mining attack In this paper we consider a kind of attack launched by A - see Fig 2 We call the attack shown in Fig 2 as Malicious Data Mining Attack Assume the attack goal of A is to infer the metering data of the target user at T A moment...

  • Data mining in healthcare decision making and precision
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    Data mining in healthcare decision making and precision Ionuț ȚĂRANU University of Economic Studies Bucharest Romania ionuttaranu gmail The trend of application of data mining in healthcare today is increased because the health sector is rich with information and data mining has become a necessity Healthcare...

  • Data mining
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    Data mining is a process of discovering patterns in large data sets involving methods at the intersection of machine learning statistics and database systems Data mining is an interdisciplinary subfield of computer science and statistics with an overall goal to extract information with intelligent methods from a data set and transform the information into a comprehensible structure for...

  • PDF Dynamic optimization of generalized SQL queries with
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    Fig 1 -1Input table a traditional vertical aggregation b and horizontal aggregation c As can be seen in fig 1 input table has some sample data Traditional vertical sum aggregations are presented in b which is the result of SQL SUM function while c holds the horizontal aggregation which is the result of SUM function...

  • US20090222472A1
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    Techniques are disclosed for aggregation in uncertain data in data processing systems For example a method of aggregation in an application that involves an uncertain data set includes the following steps The uncertain data set along with uncertainty information is obtained One or more clusters of data points are constructed from the data set...

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