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"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "School of Software, Tsinghua University, 100084, Beijing, China", 
          "id": "http://www.grid.ac/institutes/grid.12527.33", 
          "name": [
            "School of Software, Tsinghua University, 100084, Beijing, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Zheng", 
        "givenName": "Canbin", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "School of Software, Tsinghua University, 100084, Beijing, China", 
          "id": "http://www.grid.ac/institutes/grid.12527.33", 
          "name": [
            "School of Software, Tsinghua University, 100084, Beijing, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Wen", 
        "givenName": "Lijie", 
        "id": "sg:person.013640554311.55", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013640554311.55"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "School of Software, Tsinghua University, 100084, Beijing, China", 
          "id": "http://www.grid.ac/institutes/grid.12527.33", 
          "name": [
            "School of Software, Tsinghua University, 100084, Beijing, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Wang", 
        "givenName": "Jianmin", 
        "id": "sg:person.012303351315.43", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012303351315.43"
        ], 
        "type": "Person"
      }
    ], 
    "datePublished": "2017-10-20", 
    "datePublishedReg": "2017-10-20", 
    "description": "Traditional process discovery algorithms assume processes to be in a steady state. However, process models tend to be dynamic due to various factors, which has brought challenges such as change point detection, change localization and change process discovery. Existing techniques to identify change points are sensitive to parameters and the accuracy is not satisfactory. This paper proposes a novel approach to deal with such concept drift phenomenon. Event logs can be characterized by the relationships between activities, which motivates us to transform a log into a relation matrix. By detecting the always and never intervals in each row of the relation matrix, we obtain candidate change points for each relation. Finally, all the candidate change points are combined into an overall result. The approach is also able to localize the changes between different phases. Experiments on synthetic logs show that our approach is accurate and performs better than the state of the art in detecting sudden drift.", 
    "editor": [
      {
        "familyName": "Panetto", 
        "givenName": "Herv\u00e9", 
        "type": "Person"
      }, 
      {
        "familyName": "Debruyne", 
        "givenName": "Christophe", 
        "type": "Person"
      }, 
      {
        "familyName": "Gaaloul", 
        "givenName": "Walid", 
        "type": "Person"
      }, 
      {
        "familyName": "Papazoglou", 
        "givenName": "Mike", 
        "type": "Person"
      }, 
      {
        "familyName": "Paschke", 
        "givenName": "Adrian", 
        "type": "Person"
      }, 
      {
        "familyName": "Ardagna", 
        "givenName": "Claudio Agostino", 
        "type": "Person"
      }, 
      {
        "familyName": "Meersman", 
        "givenName": "Robert", 
        "type": "Person"
      }
    ], 
    "genre": "chapter", 
    "id": "sg:pub.10.1007/978-3-319-69462-7_33", 
    "inLanguage": "en", 
    "isAccessibleForFree": false, 
    "isPartOf": {
      "isbn": [
        "978-3-319-69461-0", 
        "978-3-319-69462-7"
      ], 
      "name": "On the Move to Meaningful Internet Systems. OTM 2017 Conferences", 
      "type": "Book"
    }, 
    "keywords": [
      "event logs", 
      "traditional process discovery algorithms", 
      "candidate change points", 
      "process discovery algorithms", 
      "concept drift phenomenon", 
      "discovery algorithm", 
      "process discovery", 
      "relation matrix", 
      "concept drift", 
      "change point detection", 
      "point detection", 
      "process model", 
      "synthetic logs", 
      "sudden drift", 
      "change points", 
      "novel approach", 
      "log", 
      "algorithm", 
      "drift phenomenon", 
      "change localization", 
      "accuracy", 
      "challenges", 
      "detection", 
      "technique", 
      "point", 
      "art", 
      "discovery", 
      "different phases", 
      "process", 
      "state", 
      "model", 
      "localization", 
      "matrix", 
      "experiments", 
      "drift", 
      "parameters", 
      "rows", 
      "overall results", 
      "results", 
      "relation", 
      "phase", 
      "steady state", 
      "phenomenon", 
      "relationship", 
      "factors", 
      "activity", 
      "changes", 
      "approach", 
      "paper", 
      "change process discovery", 
      "such concept drift phenomenon", 
      "Process Concept Drifts"
    ], 
    "name": "Detecting Process Concept Drifts from Event Logs", 
    "pagination": "524-542", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1092291581"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/978-3-319-69462-7_33"
        ]
      }
    ], 
    "publisher": {
      "name": "Springer Nature", 
      "type": "Organisation"
    }, 
    "sameAs": [
      "https://doi.org/10.1007/978-3-319-69462-7_33", 
      "https://app.dimensions.ai/details/publication/pub.1092291581"
    ], 
    "sdDataset": "chapters", 
    "sdDatePublished": "2022-01-01T19:11", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20220101/entities/gbq_results/chapter/chapter_199.jsonl", 
    "type": "Chapter", 
    "url": "https://doi.org/10.1007/978-3-319-69462-7_33"
  }
]

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

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

155 TRIPLES      23 PREDICATES      77 URIs      70 LITERALS      7 BLANK NODES