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dc.contributor.authorMin, Lingduo
dc.description.abstractAutomatic Knowledge Extraction system from unstructured Open Source data (AKEOS) is an artificial intelligent system utilizing machine learning techniques to help users summarize the knowledge and generate the relationships among the important entities to their queries. AKEOS is realized in forms of web application on Python Web framework Django. The web application executes user’s query by analyzing the data crawled from Google searched results, with the help of the implemented text-miming algorithm, hence summarizes the knowledge and constructs the relevant relationships between entities automatically. In the end, the system renders the entity relationships to user intuitively in terms of a diagram with captions. The AKEOS system is composed of six parts: URL Crawler, Sentence Extraction, Feature Words Generation, Relevant Sentence Selection, Entity Extraction and Knowledge Graph Generation. The individual parts works in tandem and eventually generate the graph based on the computed data.en_US
dc.format.extent65 p.en_US
dc.rightsNanyang Technological University
dc.subjectDRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systemsen_US
dc.titleAutomatic summarization of documentsen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorMao Kezhien_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeBachelor of Engineeringen_US
dc.contributor.organizationMinistry of Defence Singaporeen_US
dc.contributor.researchCentre for Computational Intelligenceen_US
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Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)
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