Search Results - (( decision missing data processing ) OR ( decision using data processing ))
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Optimizing skyline query processing in incomplete data
Published 2019“…Hence, missing data pose new challenges if the processing skyline queries cannot easily apply those methods that are designed for complete data. …”
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Development Of Output-Based Decision Support Maintenance Model (OBDSMM) For Production Machines
Published 2012“…This literature finding can be argued according to the three application criteria; data required and collection, data analysis/modelling and decision process. …”
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Evaluation of missing values imputation methods towards the effectiveness of asset valuation prediction model
Published 2019“…The problem of missing values also led to a data quality problem which then resulted inaccurate decisions. …”
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Skyline queries computation on crowdsourced- enabled incomplete database
Published 2020“…This process aims at reducing the number of values to be estimated using the crowd when local estimation is inappropriate. …”
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An enhanced robust association rules method for missing values imputation in Arabic language data set
Published 2023“…In data quality, missing values is one form of data completeness problem faced by people who deal with data. …”
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Skyline queries computation on crowdsourced- enabled incomplete database
Published 2020“…This process aims at reducing the number of values to be estimated using the crowd when local estimation is inappropriate. …”
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Data prediction and recalculation of missing data in soft set / Muhammad Sadiq Khan
Published 2018“…Uncertain data cannot be processed by using the regular tools and techniques of clear data. …”
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Development of an imputation technique - INI for software metric database with incomplete data
Published 2007“…Missing data leads to loss of information, causes biasness in data analysis and hence results to inaccurate decision-making for project management and implementation. …”
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Big data analytics and its role in election – a case study on Malaysia General Election 15 / An Nur Misha Badrul Kahar, Nur Ain Samsuddin and Nur Syakirah Salihin
Published 2023“…Questionnaires were distributed to the selected sample size to collect respondents' preferences. The collected data underwent a data cleansing process to identify missing or erroneous data. …”
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Efficient skyline query processing in incomplete graph databases using machine learning techniques
Published 2025“…Processing skyline queries in such massive, incomplete graphs is computationally intensive due to missing values and high-dimensional data. …”
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A systematic review of recurrent neural network adoption in missing data imputation
Published 2025“…It is often resulting from human error, system faults, and respondent non-response. Failing to address missing data can lead to inaccurate results during data analysis, as incomplete data sequences introduce biases and compromise the distribution of the synthesized data, and cause a negative impact on the decision-making process. …”
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Diagnosis of Coronary Artery Disease Using Artificial Intelligence Based Decision Support System
Published 2009“…RST rule inq'u ction is applied to ANNRST imputed data sets. Numerical values are discretized using Boolean reasoning method. …”
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GNN-based skyline query processing for large-scale and incomplete graphs
Published 2026“…Skyline queries are crucial in database management, selecting optimal points from multi-dimensional datasets based on dominance relationships. They are widely used in decision-making, recommendation systems, and data filtering. …”
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Facilitate risk management in construction process by using hierarchical risk breakdown structure
Published 2016“…Risk management is an important part of the decision-making process in construction project management, particularly regarding the project’s integration, scope, time, cost, quality, human resources, communications and procurement. …”
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Petroleum reservoir analogues
Published 2020“…Therefore, the technical team, geologist and reservoir engineers must evaluate all accessible data types such as seismic, well logs, well testing, production data, cores and analogues data available, to make the best technical and business decisions in exploration and production operations process. …”
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Rough Set Significant Reduct and Rules of Intrusion Detection System
Published 2017“…Intrusion Detection System deals with huge amount of data which contains irrelevant and redundant features causing slow training and testing process, also higher resource consumption as well as poor detection rate. …”
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A Study on determinants of Customer Satisfaction Towards Broadband Services in Songkhla Province
Published 2012“…It can be mentioned that factors influencing between internet service of all Broadband Services providers in Songkhla Province in Thailand, quality, speed of internet and price are influential for the decision making process of the customers to select the Broadband Services providers in Songkhla Province in Thailand. …”
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Rough Set Significant Reduction and Rules of Intrusion Detection System
Published 2016“…Intrusion Detection System deals with huge amount of data which contains irrelevant and redundant features causing slow training and testing process, also higher resource consumption as well as poor detection rate. …”
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