Special Issue on Knowledge Discovery
Knowledge Discovery is the creation of knowledge from structured (relational databases, XML) and unstructured (text, documents, images) sources. The resulting knowledge needs to be in a machine-readable and ma-chine-interpretable format and must represent knowledge in a manner that facilitates inferencing. Although it is methodically similar to Information Extraction (NLP) and ETL (Data Warehouse), the main criteria is that the extraction result goes beyond the creation of structured information or the transformation into a relational schema. It requires either the reuse of existing formal knowledge (reusing identifiers or ontologies) or the generation of a schema based on the source data.
The RDB2RDF W3C group is currently standardizing a language for extraction of RDF from relational databases. Another popular example for Knowledge Discovery is the transformation of Wikipedia into structured data and also the mapping to existing knowledge.
In this special issue, we intend to invite front-line researchers and authors to submit original research and review articles on exploring Knowledge Discovery.
Authors should read over the journal’s Author’s Guidelines carefully before submission, Prospective authors should submit an electronic copy of their complete manuscript through the journal Paper Submission System.
Please kindly notice that the “Special Issue’’ under your manuscript title is supposed to be specified and the research field “Special Issue-Knowledge Discovery” should be chosen during your submission.
According to the following timetable:
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Manuscript Due
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January 30th, 2013
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Publication Date
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March, 2013
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Editor-in-Chief
Prof. Zhongzhi Shi
Institute of Computing Technology, CAS, China
For further questions or inquiries
Please contact Editorial Assistant at
ijis@scirp.org