Rule based ETL (RETL) approach for GEO spatial data warehouse by Nordin, Norhaira, Yasin, Azman, Omar, Mazni

“…ETL will transform data to schematic format and loading data into the Geo spatial data warehouse.By using a rule-based technique, the distribution of parallel ETL pipeline will enhance and perform more efficient in large scale of data and overcome data bottleneck and performance overhead. …”
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Transforming customer postal address into spatial address for demographic analysis: A case of non-contractual customers in Seberang Perai, Pulau Pinang of Malaysia by Bohari, Abdul Manaf, Rainis, Ruslan, Marimuthu, Malliga

“…Postal address is one of important data that potentially used for trace, capture and used together with customer demographic, such as location, residential, income level, education level, transportation, and so on.The customer postal address is a touch point to analyzing demographic where it is vital important to the business, especially to prospecting their profitable customer.From literature review survey, the business has been used survey intensively as main sources for gathering demographic infomation about customer, including non-contractual customer, also called non-database customer.However, some problem will rise during joins used of home postal address, specifically, refers to un-match problems between home postal address of non-contractual customer (from the survey) with spatial data address (road and street data). These un-match problems may create un-accurate value in analyzing customer demographic background when current location, of customer takes into account. …”
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The evolution of Geography Markup Language (GML) compression model by Mahmud, Muhammad, Yasin, Azman, Omar, Mazni

“…This paper will discuss about the evolution of Geography Markup Language (compression model.GML is a type of XML files normally used to store spatial data from database.However due to the huge size processing and transferring this type of file will cost performance and storage issue. …”
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Data acquisition and discretization for flood correlation model by Ahmad Azami, Nor Idayu, Yusoff, Nooraini, Ku-Mahamud, Ku Ruhana

“…Therefore, in this study, a model has been developed to find the association between the factors that cause flood.In particular, a Bayesian Network-based method is proposed to quantify the dependency patterns in spatial data. It has been shown that although many factors may be important with respect to the flood for a particular region, the same factors may not be important for other regions.The probabilistic model has been successfully used in problems in which the dependency between the factors is of interest.Furthermore, the effect of the proposed fuzzy discretization on the association performance has also been investigated. …”
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Effect of fuzzy discretization in the association performance with continuous attributes by Ahmad Azami, Nor Idayu, Yusoff, Nooraini, Ku-Mahamud, Ku Ruhana

“…Flood is one of the natural disasters caused by complex factors such as natural, breeding and environmental.The variability of such factors on multiple heterogeneous spatial scales may cause difficulties in finding correlation or association between regions.The interaction between these factors has resulted in provision of either diverse or repeated information which can be detrimental to prediction accuracy.The complex and diverse available database has triggered this study to incorporate multi source heterogeneous data source in finding association between regions.Bayesian Network based method has been used to quantify dependency patterns in spatial data.However, a group of variables may be relevant for a particular region but may not be relevant to other region.To overcome the weakness of Bayesian network in handling continuous variable, this study has proposed data discretization technique to produce spatial correlation model.The effect of the proposed fuzzy discretization on the association performance is investigated.The comparison between different data discretization techniques proved that the proposed fuzzy discretization method gives better result with high precision, good F-measure, and a better receiver operating characteristic area compared with other methods.The results of correlation between the spatial patterns gives detailed information that may help the government, planners, decision makers, and researchers to perform actions that help to prevent and mitigate flood events in the future.…”
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