Decomposition methods of formal contexts to construct concept lattices View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2017-02

AUTHORS

Ting Qian, Ling Wei, Jianjun Qi

ABSTRACT

As an important tool for data analysis and knowledge processing, formal concept analysis has been applied to many fields. In this paper, we introduce a decomposition method of a formal context to construct its corresponding concept lattice, which answers an open problem to some extent that how this decomposition method of a context translates into a decomposition method of its corresponding concept lattice. Firstly, based on subcontext, closed relation and pairwise noninclusion covering on the attribute set, we obtain the decomposition theory of a formal context, and then we provide the method and algorithm of constructing the corresponding concept lattice by using this decomposition theory. Moreover, we consider the similar decomposition theory and method of a formal context from the object set. Finally, we make another decomposition of a formal context by combining the above two results. More... »

PAGES

95-108

References to SciGraph publications

  • 2017-12. Toward an efficient fuzziness based instance selection methodology for intrusion detection system in INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS
  • 2015-02. Period-adding and spiral organization of the periodicity in a Hopfield neural network in INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS
  • 1999. Formal Concept Analysis, Mathematical Foundations in NONE
  • 2005. A Partitional View of Concept Lattice in ROUGH SETS, FUZZY SETS, DATA MINING, AND GRANULAR COMPUTING
  • 1982. Restructuring Lattice Theory: An Approach Based on Hierarchies of Concepts in ORDERED SETS
  • 2010-06. Parallel algorithm for computing fixpoints of Galois connections in ANNALS OF MATHEMATICS AND ARTIFICIAL INTELLIGENCE
  • 2015. Formal Concept Analysis and Information Retrieval – A Survey in FORMAL CONCEPT ANALYSIS
  • 2012. An Outline of a Theory of Three-Way Decisions in ROUGH SETS AND CURRENT TRENDS IN COMPUTING
  • 2014. Three-Way Formal Concept Analysis in ROUGH SETS AND KNOWLEDGE TECHNOLOGY
  • 2017-08. A data reduction method in formal fuzzy contexts in INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s13042-016-0578-z

    DOI

    http://dx.doi.org/10.1007/s13042-016-0578-z

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1052468380


    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/2008/0802", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Computation Theory and Mathematics", 
            "type": "DefinedTerm"
          }, 
          {
            "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"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "Xi'an Shiyou University", 
              "id": "https://www.grid.ac/institutes/grid.440727.2", 
              "name": [
                "School of Mathematics, Northwest University, 710069, Xi\u2019an, China", 
                "College of Science, Xi\u2019an Shiyou University, 710065, Xi\u2019an, China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Qian", 
            "givenName": "Ting", 
            "id": "sg:person.014015240301.58", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014015240301.58"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Northwest University", 
              "id": "https://www.grid.ac/institutes/grid.412262.1", 
              "name": [
                "School of Mathematics, Northwest University, 710069, Xi\u2019an, China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Wei", 
            "givenName": "Ling", 
            "id": "sg:person.01014604234.27", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01014604234.27"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Xidian University", 
              "id": "https://www.grid.ac/institutes/grid.440736.2", 
              "name": [
                "School of Computer Science and Technology, Xidian University, 710071, Xi\u2019an, China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Qi", 
            "givenName": "Jianjun", 
            "id": "sg:person.013162526147.05", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013162526147.05"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "https://doi.org/10.1016/j.ins.2016.04.051", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1000952576"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1155/2014/136324", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1004072607"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.matcom.2014.08.004", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1005503374"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.knosys.2010.03.007", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1006222247"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ijar.2007.05.019", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1007616752"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ins.2008.07.004", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1008057596"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.knosys.2014.03.006", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1009792520"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.knosys.2015.07.024", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010862674"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.3233/fi-2015-1296", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1011023138"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s13042-015-0485-8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1013290015", 
              "https://doi.org/10.1007/s13042-015-0485-8"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s13042-015-0485-8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1013290015", 
              "https://doi.org/10.1007/s13042-015-0485-8"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-94-009-7798-3_15", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1014658433", 
              "https://doi.org/10.1007/978-94-009-7798-3_15"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://app.dimensions.ai/details/publication/pub.1015571330", 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-642-59830-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1015571330", 
              "https://doi.org/10.1007/978-3-642-59830-2"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-642-59830-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1015571330", 
              "https://doi.org/10.1007/978-3-642-59830-2"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s10472-010-9199-5", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1019411081", 
              "https://doi.org/10.1007/s10472-010-9199-5"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.jcss.2009.05.002", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1019618547"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.eswa.2015.04.044", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1022221411"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ins.2016.01.091", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1023566563"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.knosys.2014.11.020", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1024365251"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.scico.2008.09.015", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1024813191"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.3233/ifs-151729", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028283126"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-319-11740-9_67", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028668543", 
              "https://doi.org/10.1007/978-3-319-11740-9_67"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ijar.2013.04.011", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1029433344"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ijar.2012.07.005", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1031420384"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.knosys.2016.04.011", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1032580802"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-319-19545-2_4", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1032929897", 
              "https://doi.org/10.1007/978-3-319-19545-2_4"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.3233/ifs-141516", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1033276440"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-642-32115-3_1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1035740257", 
              "https://doi.org/10.1007/978-3-642-32115-3_1"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ins.2016.04.019", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1035921876"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s13042-013-0222-0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1035980735", 
              "https://doi.org/10.1007/s13042-013-0222-0"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s13042-016-0557-4", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1036157401", 
              "https://doi.org/10.1007/s13042-016-0557-4"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s13042-016-0557-4", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1036157401", 
              "https://doi.org/10.1007/s13042-016-0557-4"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ins.2014.12.010", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1038359230"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/11548669_8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1041411553", 
              "https://doi.org/10.1007/11548669_8"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/11548669_8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1041411553", 
              "https://doi.org/10.1007/11548669_8"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.eswa.2013.05.009", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1041619607"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ins.2010.07.007", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1042057113"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1515/amcs-2016-0035", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1045472714"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ins.2010.04.011", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1046778343"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1080/08839514.2012.648457", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1046972594"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ins.2011.09.023", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1047403392"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.eswa.2015.01.044", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1052512577"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/logcom/10.6.823", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1059875240"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/tcyb.2014.2361772", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061579833"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/tfuzz.2014.2371479", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061606941"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/tkde.2008.223", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061661900"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/tse.2003.1205178", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061788294"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1142/s0218339010003512", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1062974036"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/gcce.2015.7398625", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1093172689"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/fuzz-ieee.2015.7337990", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1093206226"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/icmlc.2012.6359557", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1095355726"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/icse.2007.54", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1095670947"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1017/cbo9780511809088", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1098730623"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2017-02", 
        "datePublishedReg": "2017-02-01", 
        "description": "As an important tool for data analysis and knowledge processing, formal concept analysis has been applied to many fields. In this paper, we introduce a decomposition method of a formal context to construct its corresponding concept lattice, which answers an open problem to some extent that how this decomposition method of a context translates into a decomposition method of its corresponding concept lattice. Firstly, based on subcontext, closed relation and pairwise noninclusion covering on the attribute set, we obtain the decomposition theory of a formal context, and then we provide the method and algorithm of constructing the corresponding concept lattice by using this decomposition theory. Moreover, we consider the similar decomposition theory and method of a formal context from the object set. Finally, we make another decomposition of a formal context by combining the above two results.", 
        "genre": "research_article", 
        "id": "sg:pub.10.1007/s13042-016-0578-z", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": false, 
        "isFundedItemOf": [
          {
            "id": "sg:grant.4984425", 
            "type": "MonetaryGrant"
          }
        ], 
        "isPartOf": [
          {
            "id": "sg:journal.1136696", 
            "issn": [
              "1868-8071", 
              "1868-808X"
            ], 
            "name": "International Journal of Machine Learning and Cybernetics", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "1", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "8"
          }
        ], 
        "name": "Decomposition methods of formal contexts to construct concept lattices", 
        "pagination": "95-108", 
        "productId": [
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "f9ec8505f984cb81e7fdd69607dba43fd5d019690f67ed4b68948bf42d7886f2"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1007/s13042-016-0578-z"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1052468380"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1007/s13042-016-0578-z", 
          "https://app.dimensions.ai/details/publication/pub.1052468380"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2019-04-11T12:38", 
        "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
        "sdPublisher": {
          "name": "Springer Nature - SN SciGraph project", 
          "type": "Organization"
        }, 
        "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000363_0000000363/records_70040_00000002.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "https://link.springer.com/10.1007%2Fs13042-016-0578-z"
      }
    ]
     

    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/s13042-016-0578-z'

    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/s13042-016-0578-z'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s13042-016-0578-z'

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

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s13042-016-0578-z'


     

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

    243 TRIPLES      21 PREDICATES      77 URIs      19 LITERALS      7 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1007/s13042-016-0578-z schema:about anzsrc-for:08
    2 anzsrc-for:0802
    3 schema:author Nc7bbf194949c4fa7b31ac0c876ab4620
    4 schema:citation sg:pub.10.1007/11548669_8
    5 sg:pub.10.1007/978-3-319-11740-9_67
    6 sg:pub.10.1007/978-3-319-19545-2_4
    7 sg:pub.10.1007/978-3-642-32115-3_1
    8 sg:pub.10.1007/978-3-642-59830-2
    9 sg:pub.10.1007/978-94-009-7798-3_15
    10 sg:pub.10.1007/s10472-010-9199-5
    11 sg:pub.10.1007/s13042-013-0222-0
    12 sg:pub.10.1007/s13042-015-0485-8
    13 sg:pub.10.1007/s13042-016-0557-4
    14 https://app.dimensions.ai/details/publication/pub.1015571330
    15 https://doi.org/10.1016/j.eswa.2013.05.009
    16 https://doi.org/10.1016/j.eswa.2015.01.044
    17 https://doi.org/10.1016/j.eswa.2015.04.044
    18 https://doi.org/10.1016/j.ijar.2007.05.019
    19 https://doi.org/10.1016/j.ijar.2012.07.005
    20 https://doi.org/10.1016/j.ijar.2013.04.011
    21 https://doi.org/10.1016/j.ins.2008.07.004
    22 https://doi.org/10.1016/j.ins.2010.04.011
    23 https://doi.org/10.1016/j.ins.2010.07.007
    24 https://doi.org/10.1016/j.ins.2011.09.023
    25 https://doi.org/10.1016/j.ins.2014.12.010
    26 https://doi.org/10.1016/j.ins.2016.01.091
    27 https://doi.org/10.1016/j.ins.2016.04.019
    28 https://doi.org/10.1016/j.ins.2016.04.051
    29 https://doi.org/10.1016/j.jcss.2009.05.002
    30 https://doi.org/10.1016/j.knosys.2010.03.007
    31 https://doi.org/10.1016/j.knosys.2014.03.006
    32 https://doi.org/10.1016/j.knosys.2014.11.020
    33 https://doi.org/10.1016/j.knosys.2015.07.024
    34 https://doi.org/10.1016/j.knosys.2016.04.011
    35 https://doi.org/10.1016/j.matcom.2014.08.004
    36 https://doi.org/10.1016/j.scico.2008.09.015
    37 https://doi.org/10.1017/cbo9780511809088
    38 https://doi.org/10.1080/08839514.2012.648457
    39 https://doi.org/10.1093/logcom/10.6.823
    40 https://doi.org/10.1109/fuzz-ieee.2015.7337990
    41 https://doi.org/10.1109/gcce.2015.7398625
    42 https://doi.org/10.1109/icmlc.2012.6359557
    43 https://doi.org/10.1109/icse.2007.54
    44 https://doi.org/10.1109/tcyb.2014.2361772
    45 https://doi.org/10.1109/tfuzz.2014.2371479
    46 https://doi.org/10.1109/tkde.2008.223
    47 https://doi.org/10.1109/tse.2003.1205178
    48 https://doi.org/10.1142/s0218339010003512
    49 https://doi.org/10.1155/2014/136324
    50 https://doi.org/10.1515/amcs-2016-0035
    51 https://doi.org/10.3233/fi-2015-1296
    52 https://doi.org/10.3233/ifs-141516
    53 https://doi.org/10.3233/ifs-151729
    54 schema:datePublished 2017-02
    55 schema:datePublishedReg 2017-02-01
    56 schema:description As an important tool for data analysis and knowledge processing, formal concept analysis has been applied to many fields. In this paper, we introduce a decomposition method of a formal context to construct its corresponding concept lattice, which answers an open problem to some extent that how this decomposition method of a context translates into a decomposition method of its corresponding concept lattice. Firstly, based on subcontext, closed relation and pairwise noninclusion covering on the attribute set, we obtain the decomposition theory of a formal context, and then we provide the method and algorithm of constructing the corresponding concept lattice by using this decomposition theory. Moreover, we consider the similar decomposition theory and method of a formal context from the object set. Finally, we make another decomposition of a formal context by combining the above two results.
    57 schema:genre research_article
    58 schema:inLanguage en
    59 schema:isAccessibleForFree false
    60 schema:isPartOf N2121399d438b455bbaa7f9f0e4e2ea6a
    61 Na49386a1194d406194f604626bf7b906
    62 sg:journal.1136696
    63 schema:name Decomposition methods of formal contexts to construct concept lattices
    64 schema:pagination 95-108
    65 schema:productId N5b956021daf542a487f375645fee2fe4
    66 N974f88e6574f4e91b60dbbaa919007d3
    67 Na306dbcaf4e9467b9325dee3c4a1dfef
    68 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052468380
    69 https://doi.org/10.1007/s13042-016-0578-z
    70 schema:sdDatePublished 2019-04-11T12:38
    71 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    72 schema:sdPublisher N1cddadd3bdc742a5bd930b0781d06409
    73 schema:url https://link.springer.com/10.1007%2Fs13042-016-0578-z
    74 sgo:license sg:explorer/license/
    75 sgo:sdDataset articles
    76 rdf:type schema:ScholarlyArticle
    77 N1cddadd3bdc742a5bd930b0781d06409 schema:name Springer Nature - SN SciGraph project
    78 rdf:type schema:Organization
    79 N2121399d438b455bbaa7f9f0e4e2ea6a schema:issueNumber 1
    80 rdf:type schema:PublicationIssue
    81 N5b956021daf542a487f375645fee2fe4 schema:name dimensions_id
    82 schema:value pub.1052468380
    83 rdf:type schema:PropertyValue
    84 N974f88e6574f4e91b60dbbaa919007d3 schema:name readcube_id
    85 schema:value f9ec8505f984cb81e7fdd69607dba43fd5d019690f67ed4b68948bf42d7886f2
    86 rdf:type schema:PropertyValue
    87 N9d1e8dde55a044c6a7d4289bb24aabdb rdf:first sg:person.013162526147.05
    88 rdf:rest rdf:nil
    89 Na306dbcaf4e9467b9325dee3c4a1dfef schema:name doi
    90 schema:value 10.1007/s13042-016-0578-z
    91 rdf:type schema:PropertyValue
    92 Na49386a1194d406194f604626bf7b906 schema:volumeNumber 8
    93 rdf:type schema:PublicationVolume
    94 Nc7bbf194949c4fa7b31ac0c876ab4620 rdf:first sg:person.014015240301.58
    95 rdf:rest Nf6036234db6843fd9e79530e350f9b0a
    96 Nf6036234db6843fd9e79530e350f9b0a rdf:first sg:person.01014604234.27
    97 rdf:rest N9d1e8dde55a044c6a7d4289bb24aabdb
    98 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
    99 schema:name Information and Computing Sciences
    100 rdf:type schema:DefinedTerm
    101 anzsrc-for:0802 schema:inDefinedTermSet anzsrc-for:
    102 schema:name Computation Theory and Mathematics
    103 rdf:type schema:DefinedTerm
    104 sg:grant.4984425 http://pending.schema.org/fundedItem sg:pub.10.1007/s13042-016-0578-z
    105 rdf:type schema:MonetaryGrant
    106 sg:journal.1136696 schema:issn 1868-8071
    107 1868-808X
    108 schema:name International Journal of Machine Learning and Cybernetics
    109 rdf:type schema:Periodical
    110 sg:person.01014604234.27 schema:affiliation https://www.grid.ac/institutes/grid.412262.1
    111 schema:familyName Wei
    112 schema:givenName Ling
    113 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01014604234.27
    114 rdf:type schema:Person
    115 sg:person.013162526147.05 schema:affiliation https://www.grid.ac/institutes/grid.440736.2
    116 schema:familyName Qi
    117 schema:givenName Jianjun
    118 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013162526147.05
    119 rdf:type schema:Person
    120 sg:person.014015240301.58 schema:affiliation https://www.grid.ac/institutes/grid.440727.2
    121 schema:familyName Qian
    122 schema:givenName Ting
    123 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014015240301.58
    124 rdf:type schema:Person
    125 sg:pub.10.1007/11548669_8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041411553
    126 https://doi.org/10.1007/11548669_8
    127 rdf:type schema:CreativeWork
    128 sg:pub.10.1007/978-3-319-11740-9_67 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028668543
    129 https://doi.org/10.1007/978-3-319-11740-9_67
    130 rdf:type schema:CreativeWork
    131 sg:pub.10.1007/978-3-319-19545-2_4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032929897
    132 https://doi.org/10.1007/978-3-319-19545-2_4
    133 rdf:type schema:CreativeWork
    134 sg:pub.10.1007/978-3-642-32115-3_1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035740257
    135 https://doi.org/10.1007/978-3-642-32115-3_1
    136 rdf:type schema:CreativeWork
    137 sg:pub.10.1007/978-3-642-59830-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015571330
    138 https://doi.org/10.1007/978-3-642-59830-2
    139 rdf:type schema:CreativeWork
    140 sg:pub.10.1007/978-94-009-7798-3_15 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014658433
    141 https://doi.org/10.1007/978-94-009-7798-3_15
    142 rdf:type schema:CreativeWork
    143 sg:pub.10.1007/s10472-010-9199-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019411081
    144 https://doi.org/10.1007/s10472-010-9199-5
    145 rdf:type schema:CreativeWork
    146 sg:pub.10.1007/s13042-013-0222-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035980735
    147 https://doi.org/10.1007/s13042-013-0222-0
    148 rdf:type schema:CreativeWork
    149 sg:pub.10.1007/s13042-015-0485-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013290015
    150 https://doi.org/10.1007/s13042-015-0485-8
    151 rdf:type schema:CreativeWork
    152 sg:pub.10.1007/s13042-016-0557-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036157401
    153 https://doi.org/10.1007/s13042-016-0557-4
    154 rdf:type schema:CreativeWork
    155 https://app.dimensions.ai/details/publication/pub.1015571330 schema:CreativeWork
    156 https://doi.org/10.1016/j.eswa.2013.05.009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041619607
    157 rdf:type schema:CreativeWork
    158 https://doi.org/10.1016/j.eswa.2015.01.044 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052512577
    159 rdf:type schema:CreativeWork
    160 https://doi.org/10.1016/j.eswa.2015.04.044 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022221411
    161 rdf:type schema:CreativeWork
    162 https://doi.org/10.1016/j.ijar.2007.05.019 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007616752
    163 rdf:type schema:CreativeWork
    164 https://doi.org/10.1016/j.ijar.2012.07.005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031420384
    165 rdf:type schema:CreativeWork
    166 https://doi.org/10.1016/j.ijar.2013.04.011 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029433344
    167 rdf:type schema:CreativeWork
    168 https://doi.org/10.1016/j.ins.2008.07.004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008057596
    169 rdf:type schema:CreativeWork
    170 https://doi.org/10.1016/j.ins.2010.04.011 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046778343
    171 rdf:type schema:CreativeWork
    172 https://doi.org/10.1016/j.ins.2010.07.007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042057113
    173 rdf:type schema:CreativeWork
    174 https://doi.org/10.1016/j.ins.2011.09.023 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047403392
    175 rdf:type schema:CreativeWork
    176 https://doi.org/10.1016/j.ins.2014.12.010 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038359230
    177 rdf:type schema:CreativeWork
    178 https://doi.org/10.1016/j.ins.2016.01.091 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023566563
    179 rdf:type schema:CreativeWork
    180 https://doi.org/10.1016/j.ins.2016.04.019 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035921876
    181 rdf:type schema:CreativeWork
    182 https://doi.org/10.1016/j.ins.2016.04.051 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000952576
    183 rdf:type schema:CreativeWork
    184 https://doi.org/10.1016/j.jcss.2009.05.002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019618547
    185 rdf:type schema:CreativeWork
    186 https://doi.org/10.1016/j.knosys.2010.03.007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006222247
    187 rdf:type schema:CreativeWork
    188 https://doi.org/10.1016/j.knosys.2014.03.006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009792520
    189 rdf:type schema:CreativeWork
    190 https://doi.org/10.1016/j.knosys.2014.11.020 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024365251
    191 rdf:type schema:CreativeWork
    192 https://doi.org/10.1016/j.knosys.2015.07.024 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010862674
    193 rdf:type schema:CreativeWork
    194 https://doi.org/10.1016/j.knosys.2016.04.011 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032580802
    195 rdf:type schema:CreativeWork
    196 https://doi.org/10.1016/j.matcom.2014.08.004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005503374
    197 rdf:type schema:CreativeWork
    198 https://doi.org/10.1016/j.scico.2008.09.015 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024813191
    199 rdf:type schema:CreativeWork
    200 https://doi.org/10.1017/cbo9780511809088 schema:sameAs https://app.dimensions.ai/details/publication/pub.1098730623
    201 rdf:type schema:CreativeWork
    202 https://doi.org/10.1080/08839514.2012.648457 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046972594
    203 rdf:type schema:CreativeWork
    204 https://doi.org/10.1093/logcom/10.6.823 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059875240
    205 rdf:type schema:CreativeWork
    206 https://doi.org/10.1109/fuzz-ieee.2015.7337990 schema:sameAs https://app.dimensions.ai/details/publication/pub.1093206226
    207 rdf:type schema:CreativeWork
    208 https://doi.org/10.1109/gcce.2015.7398625 schema:sameAs https://app.dimensions.ai/details/publication/pub.1093172689
    209 rdf:type schema:CreativeWork
    210 https://doi.org/10.1109/icmlc.2012.6359557 schema:sameAs https://app.dimensions.ai/details/publication/pub.1095355726
    211 rdf:type schema:CreativeWork
    212 https://doi.org/10.1109/icse.2007.54 schema:sameAs https://app.dimensions.ai/details/publication/pub.1095670947
    213 rdf:type schema:CreativeWork
    214 https://doi.org/10.1109/tcyb.2014.2361772 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061579833
    215 rdf:type schema:CreativeWork
    216 https://doi.org/10.1109/tfuzz.2014.2371479 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061606941
    217 rdf:type schema:CreativeWork
    218 https://doi.org/10.1109/tkde.2008.223 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061661900
    219 rdf:type schema:CreativeWork
    220 https://doi.org/10.1109/tse.2003.1205178 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061788294
    221 rdf:type schema:CreativeWork
    222 https://doi.org/10.1142/s0218339010003512 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062974036
    223 rdf:type schema:CreativeWork
    224 https://doi.org/10.1155/2014/136324 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004072607
    225 rdf:type schema:CreativeWork
    226 https://doi.org/10.1515/amcs-2016-0035 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045472714
    227 rdf:type schema:CreativeWork
    228 https://doi.org/10.3233/fi-2015-1296 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011023138
    229 rdf:type schema:CreativeWork
    230 https://doi.org/10.3233/ifs-141516 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033276440
    231 rdf:type schema:CreativeWork
    232 https://doi.org/10.3233/ifs-151729 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028283126
    233 rdf:type schema:CreativeWork
    234 https://www.grid.ac/institutes/grid.412262.1 schema:alternateName Northwest University
    235 schema:name School of Mathematics, Northwest University, 710069, Xi’an, China
    236 rdf:type schema:Organization
    237 https://www.grid.ac/institutes/grid.440727.2 schema:alternateName Xi'an Shiyou University
    238 schema:name College of Science, Xi’an Shiyou University, 710065, Xi’an, China
    239 School of Mathematics, Northwest University, 710069, Xi’an, China
    240 rdf:type schema:Organization
    241 https://www.grid.ac/institutes/grid.440736.2 schema:alternateName Xidian University
    242 schema:name School of Computer Science and Technology, Xidian University, 710071, Xi’an, China
    243 rdf:type schema:Organization
     




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


    ...