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020			_a9783030966553
024	7		_a10.1007/978-3-030-96655-3 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aT57.67 _b2022 EB
100	1		_aLeemans, Sander J. J. _eautor _0(orcid)0000-0002-5201-7125 _1https://orcid.org/0000-0002-5201-7125 _4aut _4http://id.loc.gov/vocabulary/relators/aut _9685223
245	1	0	_aRobust Process Mining with Guarantees : _bProcess Discovery, Conformance Checking and Enhancement _cby Sander J. J. Leemans
250			_aFirst edition 2022
264		1	_aCham _bSpringer International Publising _c2022
300			_a1 recurso en línea (XIX, 467 páginas) _b201 ilustraciones, 100 ilustraciones a color
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aLecture Notes in Business Information Processing _x1865-1356 _v440
505	0		_aIntroduction -- Preliminaries -- Process Mining -- Recursive Process Discovery -- Abstractions -- Discovery Algorithms -- Conformance Checking -- Evaluation -- Enhancement and inductive visual miner -- Conclusion -- index.
520			_aThis book presents techniques for process discovery, conformance checking and enhancement. For process discovery, it introduces the Inductive Miner framework: a recursive skeleton for discovery techniques that in itself provides several guarantees. The framework is instantiated in several concrete discovery techniques, each of which targets a specific challenge of process discovery, such as incompleteness of information or noisy behavior. For conformance checking, it introduces the Projected Conformance Checking framework, which focuses on speed, but nevertheless provides several guarantees, such as that for certain classes of models, it can decide language equivalence. For enhancement, it introduces the Inductive visual Miner, a well-polished end-user focused tool that includes process discovery, conformance checking and that can visualize performance on a discovered model, all without any user input.
988			_aSpringer_Computer_2022
650		7	_2embne _9162648 _aData mining
650		7	_2embne _9684912 _aAutómatas matemáticos
650		7	_2embne _9151819 _aAlgoritmos computacionales
776	0	8	_iPrinted edition: _z9783030966546
776	0	8	_iPrinted edition: _z9783030966560
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-96655-3 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b11/2022 _dz _esc _zSI