Visualizing IKAT Co-Authorship Networks by Text Mining MICC-IKAT Annual Reports 1993–2005
نویسنده
چکیده
This short paper presents two experiments that address visualization of correlated authors which have been obtained through text mining IKAT annual reports. By generating a 2-dimensional topology that reflects the structure underlying the extracted features, a person investigating this information can oversee the information more efficiently. Similar techniques can be used in financial fraud investigations supporting investigators with electronic discovery when searching for relevant documents in e-mail archives and suspicious transactions in financial databases.
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