Interactive Workflow Mining View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2004

AUTHORS

Markus Hammori , Joachim Herbst , Niko Kleiner

ABSTRACT

Workflow or process mining is concerned with deriving a workflow model from observed behavior described in a workflow log. Experience from applying our workflow mining system InWoLvE in experiments and practical applications has shown that workflow mining is a highly interactive process. The mining expert iteratively approaches the result by varying the parameters of the mining tool and verifying the mined models. Our tool InWoLvE was not designed for intensive interactive usage making practical usage more than difficult. In this contribution we describe the main requirements for an interactive workflow mining system and how we derived these. We outline two selected concepts: a special layout algorithm that is stable against small changes of the model thus allowing the workflow mining expert to maintain a mental map of the workflow and a validation procedure helping the mining expert in his decision for the final result. These and other important concepts have been implemented in the first prototype of an interactive workflow mining system called ProTo. More... »

PAGES

211-226

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-540-25970-1_14

DOI

http://dx.doi.org/10.1007/978-3-540-25970-1_14

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1021827576


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/08", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Information and Computing Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0801", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Artificial Intelligence and Image Processing", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0806", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Information Systems", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "DaimlerChrysler AG, Research & Technology, P.O. Box 2360, 89013, Ulm, Germany", 
          "id": "http://www.grid.ac/institutes/grid.5433.1", 
          "name": [
            "DaimlerChrysler AG, Research & Technology, P.O. Box 2360, 89013, Ulm, Germany"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Hammori", 
        "givenName": "Markus", 
        "id": "sg:person.011277125151.75", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011277125151.75"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "DaimlerChrysler AG, Research & Technology, P.O. Box 2360, 89013, Ulm, Germany", 
          "id": "http://www.grid.ac/institutes/grid.5433.1", 
          "name": [
            "DaimlerChrysler AG, Research & Technology, P.O. Box 2360, 89013, Ulm, Germany"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Herbst", 
        "givenName": "Joachim", 
        "id": "sg:person.014727747331.21", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014727747331.21"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Ulm, Faculty for Computer Science, 89069, Ulm, Germany", 
          "id": "http://www.grid.ac/institutes/grid.6582.9", 
          "name": [
            "University of Ulm, Faculty for Computer Science, 89069, Ulm, Germany"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kleiner", 
        "givenName": "Niko", 
        "id": "sg:person.014265027151.58", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014265027151.58"
        ], 
        "type": "Person"
      }
    ], 
    "datePublished": "2004", 
    "datePublishedReg": "2004-01-01", 
    "description": "Workflow or process mining is concerned with deriving a workflow model from observed behavior described in a workflow log. Experience from applying our workflow mining system InWoLvE in experiments and practical applications has shown that workflow mining is a highly interactive process. The mining expert iteratively approaches the result by varying the parameters of the mining tool and verifying the mined models. Our tool InWoLvE was not designed for intensive interactive usage making practical usage more than difficult. In this contribution we describe the main requirements for an interactive workflow mining system and how we derived these. We outline two selected concepts: a special layout algorithm that is stable against small changes of the model thus allowing the workflow mining expert to maintain a mental map of the workflow and a validation procedure helping the mining expert in his decision for the final result. These and other important concepts have been implemented in the first prototype of an interactive workflow mining system called ProTo.", 
    "editor": [
      {
        "familyName": "Desel", 
        "givenName": "J\u00f6rg", 
        "type": "Person"
      }, 
      {
        "familyName": "Pernici", 
        "givenName": "Barbara", 
        "type": "Person"
      }, 
      {
        "familyName": "Weske", 
        "givenName": "Mathias", 
        "type": "Person"
      }
    ], 
    "genre": "chapter", 
    "id": "sg:pub.10.1007/978-3-540-25970-1_14", 
    "inLanguage": "en", 
    "isAccessibleForFree": false, 
    "isPartOf": {
      "isbn": [
        "978-3-540-22235-4", 
        "978-3-540-25970-1"
      ], 
      "name": "Business Process Management", 
      "type": "Book"
    }, 
    "keywords": [
      "workflow mining system", 
      "mining experts", 
      "mining system", 
      "workflow mining", 
      "process mining", 
      "workflow logs", 
      "workflow model", 
      "mining tools", 
      "interactive usage", 
      "layout algorithm", 
      "mining", 
      "first prototype", 
      "main requirements", 
      "practical usage", 
      "interactive process", 
      "mental maps", 
      "experts", 
      "final results", 
      "usage", 
      "important concepts", 
      "validation procedure", 
      "practical applications", 
      "workflow", 
      "algorithm", 
      "system", 
      "prototype", 
      "concept", 
      "requirements", 
      "model", 
      "logs", 
      "tool", 
      "applications", 
      "decisions", 
      "maps", 
      "experiments", 
      "results", 
      "process", 
      "experience", 
      "observed behavior", 
      "contribution", 
      "parameters", 
      "behavior", 
      "small changes", 
      "procedure", 
      "proto", 
      "changes"
    ], 
    "name": "Interactive Workflow Mining", 
    "pagination": "211-226", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1021827576"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/978-3-540-25970-1_14"
        ]
      }
    ], 
    "publisher": {
      "name": "Springer Nature", 
      "type": "Organisation"
    }, 
    "sameAs": [
      "https://doi.org/10.1007/978-3-540-25970-1_14", 
      "https://app.dimensions.ai/details/publication/pub.1021827576"
    ], 
    "sdDataset": "chapters", 
    "sdDatePublished": "2022-05-20T07:48", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20220519/entities/gbq_results/chapter/chapter_417.jsonl", 
    "type": "Chapter", 
    "url": "https://doi.org/10.1007/978-3-540-25970-1_14"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/978-3-540-25970-1_14'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-3-540-25970-1_14'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-3-540-25970-1_14'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-3-540-25970-1_14'


 

This table displays all metadata directly associated to this object as RDF triples.

137 TRIPLES      23 PREDICATES      73 URIs      65 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/978-3-540-25970-1_14 schema:about anzsrc-for:08
2 anzsrc-for:0801
3 anzsrc-for:0806
4 schema:author N36ac84df474644bfa1a257a13464f275
5 schema:datePublished 2004
6 schema:datePublishedReg 2004-01-01
7 schema:description Workflow or process mining is concerned with deriving a workflow model from observed behavior described in a workflow log. Experience from applying our workflow mining system InWoLvE in experiments and practical applications has shown that workflow mining is a highly interactive process. The mining expert iteratively approaches the result by varying the parameters of the mining tool and verifying the mined models. Our tool InWoLvE was not designed for intensive interactive usage making practical usage more than difficult. In this contribution we describe the main requirements for an interactive workflow mining system and how we derived these. We outline two selected concepts: a special layout algorithm that is stable against small changes of the model thus allowing the workflow mining expert to maintain a mental map of the workflow and a validation procedure helping the mining expert in his decision for the final result. These and other important concepts have been implemented in the first prototype of an interactive workflow mining system called ProTo.
8 schema:editor N6b7ed0c55f9f4594a020f41d1f1db89c
9 schema:genre chapter
10 schema:inLanguage en
11 schema:isAccessibleForFree false
12 schema:isPartOf N876e2785720a41a6b9bbac61e22d3c29
13 schema:keywords algorithm
14 applications
15 behavior
16 changes
17 concept
18 contribution
19 decisions
20 experience
21 experiments
22 experts
23 final results
24 first prototype
25 important concepts
26 interactive process
27 interactive usage
28 layout algorithm
29 logs
30 main requirements
31 maps
32 mental maps
33 mining
34 mining experts
35 mining system
36 mining tools
37 model
38 observed behavior
39 parameters
40 practical applications
41 practical usage
42 procedure
43 process
44 process mining
45 proto
46 prototype
47 requirements
48 results
49 small changes
50 system
51 tool
52 usage
53 validation procedure
54 workflow
55 workflow logs
56 workflow mining
57 workflow mining system
58 workflow model
59 schema:name Interactive Workflow Mining
60 schema:pagination 211-226
61 schema:productId N5ca3a6d0c8114fd2874650b980b54419
62 N6d54177a5d5a445d8dbae8febb73c422
63 schema:publisher Na661d13e992e43689764963deb087751
64 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021827576
65 https://doi.org/10.1007/978-3-540-25970-1_14
66 schema:sdDatePublished 2022-05-20T07:48
67 schema:sdLicense https://scigraph.springernature.com/explorer/license/
68 schema:sdPublisher Na6a7a7cc3e5c4b469c89559fef99fea8
69 schema:url https://doi.org/10.1007/978-3-540-25970-1_14
70 sgo:license sg:explorer/license/
71 sgo:sdDataset chapters
72 rdf:type schema:Chapter
73 N187d4986452246e0a2297dee734564a9 rdf:first N65e995a368fe4b3ca6c606d12af566a9
74 rdf:rest N8262d5a7f3b041288e175e9f26a4ff50
75 N36ac84df474644bfa1a257a13464f275 rdf:first sg:person.011277125151.75
76 rdf:rest N700346602d704cc0883292ffaada3b5d
77 N5ca3a6d0c8114fd2874650b980b54419 schema:name doi
78 schema:value 10.1007/978-3-540-25970-1_14
79 rdf:type schema:PropertyValue
80 N6575704278024c58855c8cf51651986d schema:familyName Desel
81 schema:givenName Jörg
82 rdf:type schema:Person
83 N65e995a368fe4b3ca6c606d12af566a9 schema:familyName Pernici
84 schema:givenName Barbara
85 rdf:type schema:Person
86 N6b7ed0c55f9f4594a020f41d1f1db89c rdf:first N6575704278024c58855c8cf51651986d
87 rdf:rest N187d4986452246e0a2297dee734564a9
88 N6d54177a5d5a445d8dbae8febb73c422 schema:name dimensions_id
89 schema:value pub.1021827576
90 rdf:type schema:PropertyValue
91 N700346602d704cc0883292ffaada3b5d rdf:first sg:person.014727747331.21
92 rdf:rest Ne77d4aca14544feabbba848b03d6fbd9
93 N8262d5a7f3b041288e175e9f26a4ff50 rdf:first Nafb94d26290e4fe68f1ab25fc0d4af9e
94 rdf:rest rdf:nil
95 N876e2785720a41a6b9bbac61e22d3c29 schema:isbn 978-3-540-22235-4
96 978-3-540-25970-1
97 schema:name Business Process Management
98 rdf:type schema:Book
99 Na661d13e992e43689764963deb087751 schema:name Springer Nature
100 rdf:type schema:Organisation
101 Na6a7a7cc3e5c4b469c89559fef99fea8 schema:name Springer Nature - SN SciGraph project
102 rdf:type schema:Organization
103 Nafb94d26290e4fe68f1ab25fc0d4af9e schema:familyName Weske
104 schema:givenName Mathias
105 rdf:type schema:Person
106 Ne77d4aca14544feabbba848b03d6fbd9 rdf:first sg:person.014265027151.58
107 rdf:rest rdf:nil
108 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
109 schema:name Information and Computing Sciences
110 rdf:type schema:DefinedTerm
111 anzsrc-for:0801 schema:inDefinedTermSet anzsrc-for:
112 schema:name Artificial Intelligence and Image Processing
113 rdf:type schema:DefinedTerm
114 anzsrc-for:0806 schema:inDefinedTermSet anzsrc-for:
115 schema:name Information Systems
116 rdf:type schema:DefinedTerm
117 sg:person.011277125151.75 schema:affiliation grid-institutes:grid.5433.1
118 schema:familyName Hammori
119 schema:givenName Markus
120 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011277125151.75
121 rdf:type schema:Person
122 sg:person.014265027151.58 schema:affiliation grid-institutes:grid.6582.9
123 schema:familyName Kleiner
124 schema:givenName Niko
125 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014265027151.58
126 rdf:type schema:Person
127 sg:person.014727747331.21 schema:affiliation grid-institutes:grid.5433.1
128 schema:familyName Herbst
129 schema:givenName Joachim
130 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014727747331.21
131 rdf:type schema:Person
132 grid-institutes:grid.5433.1 schema:alternateName DaimlerChrysler AG, Research & Technology, P.O. Box 2360, 89013, Ulm, Germany
133 schema:name DaimlerChrysler AG, Research & Technology, P.O. Box 2360, 89013, Ulm, Germany
134 rdf:type schema:Organization
135 grid-institutes:grid.6582.9 schema:alternateName University of Ulm, Faculty for Computer Science, 89069, Ulm, Germany
136 schema:name University of Ulm, Faculty for Computer Science, 89069, Ulm, Germany
137 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...