@article{MAKHILLJEAS2018131016210,
    title = {Analysis of Different Methods in Data Linkage Data Presentation with
Anomaly and Redundant in Data Sources},
    journal = {Journal of Engineering and Applied Sciences},
    volume = {13},
    number = {10},
    pages = {3450-3457},
    year = {2018},
    issn = {1816-949x},
    doi = {jeasci.2018.3450.3457},
    url = {https://makhillpublications.co/view-article.php?issn=1816-949x&doi=jeasci.2018.3450.3457},
    author = {T. and},
    keywords = {Data linkage,data mining,scalability,entity resolution,attribute matching,duplication row matching,Intrusion Detection (ID)},
    abstract = {Combining data in data mining (known as information linkage, entity resolution and object
identification and attribute matching) is a complex task of finding, matching and combining rows (which contain
same attributes) from different data bases or even within single data base. For providing effective data linkage
in reliable data source management traditionally some of the data mining techniques/methods and other
proceedings may present in dedupplication and miss usability in data matching from different sources. In this
study, we analyze basic issues in data linkage in data representation and anomaly presentation from different
data sources with duplication results. By increase the index databases related to different attributes, complexity
of matching processes is a major challenge in row linkage and redundant from different data sources.
Traditionally there is more index approaches have been developed in recent years for data linkage. We analyzed
survey of various indexing/matching methods in reliable multi database systems. We analyze the scalability,
flexibility of various entity relations in row collection from various data base sources.}
    }