Detail Process Mining as First-Order Classification Learning on Logs with Negative Events Bibliografi Author: Goedertier, Stijn ; Baesens, Bart ; Haesen, Raf ; Martens, David ; Vanthienen, Jan Bahasa: (EN )     Penerbit: Springer-Verlag Berlin Heidelberg     Tempat Terbit: Heidelberg    Tahun Terbit: 2008     Jenis: Papers/Makalah Fulltext: Process Mining as First-Order Classification.pdf (406.08KB; 0 download) Abstract Process mining is the automated construction of process models from information system event logs. In this paper we identify three fundamental difficulties related to process mining: the lack of negative information, the presence of history-dependent behavior and the presence of noise. These difficulties can elegantly dealt with when process mining is represented as first-order classification learning on event logs supplemented with negative events. A first set of process discovery experiments indicates the feasibility of this learning technique. Opini Anda Klik untuk menuliskan opini Anda tentang koleksi ini! Lihat Sejarah Pengadaan  Konversi Metadata   Kembali

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