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dc.contributor.authorJain, Shubham
dc.contributor.authorde Buitléir, Amy
dc.contributor.authorFallon, Enda
dc.identifier.citationJain, S., de Buitléir, A., Fallon, E. (2020). A review of unstructured data analysis and parsing methods. In 2020 International Conference on Emerging Smart Computing and Informatics (ESCI), Pune, India, 2020, pp. 164-169, doi: 10.1109/ESCI48226.2020.9167588.en_US
dc.identifier.otherConferences - Software Research Institute - AITen_US
dc.description.abstractComputer applications generate an enormous amount of data every day through their logs, system-generated files or other reports. This generated data depicts the state of the running system and contains abundant information that can be used for system diagnostics and monitoring. Network monitoring systems produce a wide variety of unstructured information, so there is a need for an automated way to extract the relevant data, which currently requires multitude of custom parsers. Developing and testing custom parsers can be time-consuming. Instead, data can be automatically processed and parsed into a machine-readable format, building a generic model for standard or vendor-specific data, and generating insights for analytics, anomaly detection, intrusion detection, node failures and various other applications. This paper reviews some existing approaches for unstructured data mining and parsing and discusses the challenges in information extraction, creation of knowledge bases and presents a generic framework for automatic parsing.en_US
dc.relation.ispartof2020 International Conference on Emerging Smart Computing and Informatics (ESCI)en_US
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Ireland*
dc.subjectData miningen_US
dc.subjectKnowledge baseen_US
dc.titleA review of unstructured data analysis and parsing methodsen_US
dc.contributor.sponsorIrish Research Council Enterprise Partnership Scheme Postgraduate Scholarship 2020 under Project EPSPG/2020/7en_US
dc.identifier.conference2020 International Conference on Emerging Smart Computing and Informatics (ESCI)
dc.identifier.doidoi: 10.1109/ESCI48226.2020.9167588.
dc.rights.accessOpen Accessen_US
dc.subject.departmentSoftware Research Institute AITen_US

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Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 Ireland