Search Results - decision ((missing data) OR (using data)) processing

Optimizing skyline query processing in incomplete data by Gulzar, Yonis, Alwan, Ali Amer, Turaev, Sherzod

“…Hence, missing data pose new challenges if the processing skyline queries cannot easily apply those methods that are designed for complete data. …”
Get full text
Get full text
Get full text
Get full text
Get full text

Evaluation of missing values imputation methods towards the effectiveness of asset valuation prediction model by Mohd Jaya, Mohd Izham, Sidi, Fatimah, Affendey, Lilly Suriani, Ishak, Iskandar, A. Jabar, Marzanah

“…The problem of missing values also led to a data quality problem which then resulted inaccurate decisions. …”
Get full text
Get full text

Skyline queries computation on crowdsourced- enabled incomplete database by Swidan, Marwa B., Alwan, Ali A., Turaev, Sherzod, Ibrahim, Hamidah, Abualkishik, Abedallah Zaid, Gulzar, Yonis

“…This paper proposes an approach for estimating the missing values of the skylines by first exploiting the available data and utilizes the implicit relationships between the attributes in order to impute the missing values of the skylines. …”
Get full text
Get full text

An enhanced robust association rules method for missing values imputation in Arabic language data set by Salem, Awsan Thabet

“…In data quality, missing values is one form of data completeness problem faced by people who deal with data. …”
Get full text
Get full text
Get full text
Get full text

Development of an imputation technique - INI for software metric database with incomplete data by Wasito, Ito, Olanrewaju, Rashidah F.

“…This technique was used for estimating missing data in a software engineering database (PROMISE). …”
Get full text
Get full text
Get full text

Data prediction and recalculation of missing data in soft set / Muhammad Sadiq Khan by Muhammad Sadiq , Khan

“…Uncertain data cannot be processed by using the regular tools and techniques of clear data. …”
Get full text
Get full text
Get full text

Skyline queries computation on crowdsourced- enabled incomplete database by Swidan, Marwa, Aljuboori, Ali A.Alwan, Turaev, Sherzod, Ibrahim, Hamidah, Zaid Abualkishik, Abedallah, Gulzar, Yonis

“…This paper proposes an approach for estimating the missing values of the skylines by first exploiting the available data and utilizes the implicit relationships between the attributes in order to impute the missing values of the skylines. …”
Get full text
Get full text
Get full text
Get full text

A systematic review of recurrent neural network adoption in missing data imputation by Nur Aqilah, Fadzil Akbar, Mohd Izham, Mohd Jaya, Mohd Faizal, Ab Razak, Nurul Aqilah, Zamri

“…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. …”
Get full text
Get full text
Get full text

Data Cleaning in Knowledge Discovery Database (KDD)-Data Mining by Fauziah Abdul Rahman, Mohammad Ishak Desa, Antoni Wibowo, Norhaidah Abu Haris

Development Of Output-Based Decision Support Maintenance Model (OBDSMM) For Production Machines by Ahmad, Rosmaini

“…This literature finding can be argued according to the three application criteria; data required and collection, data analysis/modelling and decision process. …”
Get full text
Get full text

Efficient skyline query processing in incomplete graph databases using machine learning techniques by Noor, Ubair, Hassan, Raini, Dwi Handayani, Dini Oktarina

“…Processing skyline queries in such massive, incomplete graphs is computationally intensive due to missing values and high-dimensional data. …”
Get full text
Get full text
Get full text

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 by Badrul Kahar, An Nur Misha, Samsuddin, Nur Ain, Salihin, Nur Syakirah

“…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. …”
Get full text
Get full text

GNN-based skyline query processing for large-scale and incomplete graphs by Adzman, Hasan Khair, Hassan, Raini, Dwi Handayani, Dini Oktarina

“…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. …”
Get full text
Get full text
Get full text
Get full text
Get full text

Towards personalized intensive care decision support using a Bayesian network: A multicenter glycemic control study by Abu-Samah A., Razak N.N.A., Suhaimi F.M., Jamaludin U.K., Chase J.G.

A Study on determinants of Customer Satisfaction Towards Broadband Services in Songkhla Province by Laeheem, Miss Fateemoh

“…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. …”
Get full text
Get full text
Get full text

Performance analysis of machine learning algorithms for missing value imputation by Ismail, Amelia Ritahani, Zainal Abidin, Nadzurah, Emran, Nurul Akmar

“…Data mining requires a pre-processing task in which the data are prepared,cleaned,integrated,transformed,reduced and discretized for ensuring the quality.Missing values is a universal problem in many research domains that is commonly encountered in the data cleaning process.Missing values usually occur when a value of stored data absent for a variable of an observation.Missing values problem imposes undesirable effect on analysis results,especially when it leads to biased parameter estimates.Data imputation is a common way to deal with missing values where the missing value’s substitutes are discovered through statistical or machine learning techniques. …”
Get full text
Get full text
Get full text

Petroleum reservoir analogues by Ganat, T.A.-A.O.

“…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. …”
Get full text
Get full text

BMSP-ML: big mart sales prediction using different machine learning techniques by Ali, R.F., Muneer, A., Almaghthawi, A., Alghamdi, A., Fati, S.M., Ghaleb, E.A.A.

“…This process gets the data and beautifies the data by imputing the missing values and feature engineering. …”
Get full text
Get full text

Diagnosis of Coronary Artery Disease Using Artificial Intelligence Based Decision Support System by SETIAWAN, NOOR AKHMAD

“…RST rule inq'u ction is applied to ANNRST imputed data sets. Numerical values are discretized using Boolean reasoning method. …”
Get full text
Get full text

Novel mechanism to improve Hadith classifier performance by Aldhlan, Kawther A., Zeki, Akram M., Zeki, Ahmed M., Alreshidi, Hamad

“…Whilst some attributes were indicated as null values, or missing values. A novel mechanism called missing data detector (MDD) was employed to handle these missing data. …”
Get full text
Get full text
Get full text