Attribute reduction via local conditional entropy View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-04-04

AUTHORS

Yibo Wang, Xiangjian Chen, Kai Dong

ABSTRACT

N/A

References to SciGraph publications

  • 2012-11. Hierarchical Structures on Multigranulation Spaces in JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY
  • 2018-06. A survey on online feature selection with streaming features in FRONTIERS OF COMPUTER SCIENCE
  • 2016-02. Feature and instance reduction for PNN classifiers based on fuzzy rough sets in INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s13042-019-00948-z

    DOI

    http://dx.doi.org/10.1007/s13042-019-00948-z

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1113234184


    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", 
        "author": [
          {
            "familyName": "Wang", 
            "givenName": "Yibo", 
            "type": "Person"
          }, 
          {
            "familyName": "Chen", 
            "givenName": "Xiangjian", 
            "type": "Person"
          }, 
          {
            "familyName": "Dong", 
            "givenName": "Kai", 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "https://doi.org/10.1016/j.fss.2009.12.010", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1000484518"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11390-012-1294-0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1002978815", 
              "https://doi.org/10.1007/s11390-012-1294-0"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.knosys.2014.08.030", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1004326664"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ins.2011.04.039", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1007740063"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ins.2016.09.012", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1009891547"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ins.2016.09.012", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1009891547"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ins.2016.09.012", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1009891547"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ins.2016.09.012", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1009891547"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ijar.2016.08.007", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1012087303"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.knosys.2015.09.011", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1013031835"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.patcog.2011.02.020", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1013531072"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ins.2013.06.057", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1013576443"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/tfuzz.2015.2393391", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1018878727"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.knosys.2012.10.018", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1020386828"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ijar.2013.04.003", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1024127550"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ins.2016.03.019", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1024415548"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s13042-014-0232-6", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1025591792", 
              "https://doi.org/10.1007/s13042-014-0232-6"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.patcog.2016.02.013", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028810245"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.artint.2010.04.018", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1029260350"
            ], 
            "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.2014.03.021", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1034075745"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ins.2007.09.019", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1035147250"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ijar.2013.02.010", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1039204825"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ins.2011.07.010", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1041001392"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.knosys.2016.04.012", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1041694911"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ijar.2010.01.004", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1044636061"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.asoc.2016.04.003", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1046776537"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/tfuzz.2005.864086", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061605898"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/tfuzz.2011.2167235", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061606503"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/tkde.2011.149", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061662346"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/tkde.2011.89", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061662498"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/tsmcb.2009.2024166", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061797096"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1142/s0218488508005121", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1062977098"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/tnnls.2017.2710422", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1086385715"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11704-016-5489-3", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1091049132", 
              "https://doi.org/10.1007/s11704-016-5489-3"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ins.2017.08.038", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1091117634"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ins.2017.08.053", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1091219263"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.knosys.2017.09.006", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1091500910"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.knosys.2017.09.009", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1091504837"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/tfuzz.2017.2768044", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1092448177"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/tfuzz.2017.2718492", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1093744758"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ijar.2018.01.008", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1103173437"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.knosys.2018.05.020", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1104152032"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.asoc.2018.05.013", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1104161303"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ijar.2018.11.010", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1110009943"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ijar.2018.11.010", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1110009943"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.knosys.2018.11.034", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1110275347"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2019-04-04", 
        "datePublishedReg": "2019-04-04", 
        "genre": "research_article", 
        "id": "sg:pub.10.1007/s13042-019-00948-z", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": false, 
        "isPartOf": [
          {
            "id": "sg:journal.1136696", 
            "issn": [
              "1868-8071", 
              "1868-808X"
            ], 
            "name": "International Journal of Machine Learning and Cybernetics", 
            "type": "Periodical"
          }
        ], 
        "name": "Attribute reduction via local conditional entropy", 
        "productId": [
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1007/s13042-019-00948-z"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1113234184"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1007/s13042-019-00948-z", 
          "https://app.dimensions.ai/details/publication/pub.1113234184"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2019-04-11T13:58", 
        "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/v90/0000000371_0000000371/records_130820_00000007.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "http://link.springer.com/10.1007/s13042-019-00948-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/s13042-019-00948-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/s13042-019-00948-z'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s13042-019-00948-z'

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

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s13042-019-00948-z'


     

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

    178 TRIPLES      18 PREDICATES      62 URIs      13 LITERALS      4 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1007/s13042-019-00948-z schema:author N327d0d8c3f734b58b0017ba18a224798
    2 schema:citation sg:pub.10.1007/s11390-012-1294-0
    3 sg:pub.10.1007/s11704-016-5489-3
    4 sg:pub.10.1007/s13042-014-0232-6
    5 https://doi.org/10.1016/j.artint.2010.04.018
    6 https://doi.org/10.1016/j.asoc.2016.04.003
    7 https://doi.org/10.1016/j.asoc.2018.05.013
    8 https://doi.org/10.1016/j.fss.2009.12.010
    9 https://doi.org/10.1016/j.ijar.2010.01.004
    10 https://doi.org/10.1016/j.ijar.2012.07.005
    11 https://doi.org/10.1016/j.ijar.2013.02.010
    12 https://doi.org/10.1016/j.ijar.2013.04.003
    13 https://doi.org/10.1016/j.ijar.2016.08.007
    14 https://doi.org/10.1016/j.ijar.2018.01.008
    15 https://doi.org/10.1016/j.ijar.2018.11.010
    16 https://doi.org/10.1016/j.ins.2007.09.019
    17 https://doi.org/10.1016/j.ins.2011.04.039
    18 https://doi.org/10.1016/j.ins.2011.07.010
    19 https://doi.org/10.1016/j.ins.2013.06.057
    20 https://doi.org/10.1016/j.ins.2016.03.019
    21 https://doi.org/10.1016/j.ins.2016.09.012
    22 https://doi.org/10.1016/j.ins.2017.08.038
    23 https://doi.org/10.1016/j.ins.2017.08.053
    24 https://doi.org/10.1016/j.knosys.2012.10.018
    25 https://doi.org/10.1016/j.knosys.2014.03.021
    26 https://doi.org/10.1016/j.knosys.2014.08.030
    27 https://doi.org/10.1016/j.knosys.2015.09.011
    28 https://doi.org/10.1016/j.knosys.2016.04.012
    29 https://doi.org/10.1016/j.knosys.2017.09.006
    30 https://doi.org/10.1016/j.knosys.2017.09.009
    31 https://doi.org/10.1016/j.knosys.2018.05.020
    32 https://doi.org/10.1016/j.knosys.2018.11.034
    33 https://doi.org/10.1016/j.patcog.2011.02.020
    34 https://doi.org/10.1016/j.patcog.2016.02.013
    35 https://doi.org/10.1109/tfuzz.2005.864086
    36 https://doi.org/10.1109/tfuzz.2011.2167235
    37 https://doi.org/10.1109/tfuzz.2015.2393391
    38 https://doi.org/10.1109/tfuzz.2017.2718492
    39 https://doi.org/10.1109/tfuzz.2017.2768044
    40 https://doi.org/10.1109/tkde.2011.149
    41 https://doi.org/10.1109/tkde.2011.89
    42 https://doi.org/10.1109/tnnls.2017.2710422
    43 https://doi.org/10.1109/tsmcb.2009.2024166
    44 https://doi.org/10.1142/s0218488508005121
    45 schema:datePublished 2019-04-04
    46 schema:datePublishedReg 2019-04-04
    47 schema:genre research_article
    48 schema:inLanguage en
    49 schema:isAccessibleForFree false
    50 schema:isPartOf sg:journal.1136696
    51 schema:name Attribute reduction via local conditional entropy
    52 schema:productId N1c59970e6022460dad4c3a740e117e6c
    53 Nea8af176a86247278bae01ea8529e29f
    54 schema:sameAs https://app.dimensions.ai/details/publication/pub.1113234184
    55 https://doi.org/10.1007/s13042-019-00948-z
    56 schema:sdDatePublished 2019-04-11T13:58
    57 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    58 schema:sdPublisher N69fdb55339bf4becb0d77aa7e3432404
    59 schema:url http://link.springer.com/10.1007/s13042-019-00948-z
    60 sgo:license sg:explorer/license/
    61 sgo:sdDataset articles
    62 rdf:type schema:ScholarlyArticle
    63 N1c59970e6022460dad4c3a740e117e6c schema:name doi
    64 schema:value 10.1007/s13042-019-00948-z
    65 rdf:type schema:PropertyValue
    66 N327d0d8c3f734b58b0017ba18a224798 rdf:first N578aa7e4a25e423abd7323a09b0af8f5
    67 rdf:rest Nd8ed109f9d784751ae6ac3731428ec29
    68 N578aa7e4a25e423abd7323a09b0af8f5 schema:familyName Wang
    69 schema:givenName Yibo
    70 rdf:type schema:Person
    71 N69fdb55339bf4becb0d77aa7e3432404 schema:name Springer Nature - SN SciGraph project
    72 rdf:type schema:Organization
    73 Nbf21de7cf68d4049ac7693af8a1f5058 rdf:first Nd1e91070c64c4fc4ace2b3f70ac3b1a5
    74 rdf:rest rdf:nil
    75 Nd1e91070c64c4fc4ace2b3f70ac3b1a5 schema:familyName Dong
    76 schema:givenName Kai
    77 rdf:type schema:Person
    78 Nd8ed109f9d784751ae6ac3731428ec29 rdf:first Nfbe5255828f948a29abacfe9bea090f9
    79 rdf:rest Nbf21de7cf68d4049ac7693af8a1f5058
    80 Nea8af176a86247278bae01ea8529e29f schema:name dimensions_id
    81 schema:value pub.1113234184
    82 rdf:type schema:PropertyValue
    83 Nfbe5255828f948a29abacfe9bea090f9 schema:familyName Chen
    84 schema:givenName Xiangjian
    85 rdf:type schema:Person
    86 sg:journal.1136696 schema:issn 1868-8071
    87 1868-808X
    88 schema:name International Journal of Machine Learning and Cybernetics
    89 rdf:type schema:Periodical
    90 sg:pub.10.1007/s11390-012-1294-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002978815
    91 https://doi.org/10.1007/s11390-012-1294-0
    92 rdf:type schema:CreativeWork
    93 sg:pub.10.1007/s11704-016-5489-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1091049132
    94 https://doi.org/10.1007/s11704-016-5489-3
    95 rdf:type schema:CreativeWork
    96 sg:pub.10.1007/s13042-014-0232-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025591792
    97 https://doi.org/10.1007/s13042-014-0232-6
    98 rdf:type schema:CreativeWork
    99 https://doi.org/10.1016/j.artint.2010.04.018 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029260350
    100 rdf:type schema:CreativeWork
    101 https://doi.org/10.1016/j.asoc.2016.04.003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046776537
    102 rdf:type schema:CreativeWork
    103 https://doi.org/10.1016/j.asoc.2018.05.013 schema:sameAs https://app.dimensions.ai/details/publication/pub.1104161303
    104 rdf:type schema:CreativeWork
    105 https://doi.org/10.1016/j.fss.2009.12.010 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000484518
    106 rdf:type schema:CreativeWork
    107 https://doi.org/10.1016/j.ijar.2010.01.004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044636061
    108 rdf:type schema:CreativeWork
    109 https://doi.org/10.1016/j.ijar.2012.07.005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031420384
    110 rdf:type schema:CreativeWork
    111 https://doi.org/10.1016/j.ijar.2013.02.010 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039204825
    112 rdf:type schema:CreativeWork
    113 https://doi.org/10.1016/j.ijar.2013.04.003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024127550
    114 rdf:type schema:CreativeWork
    115 https://doi.org/10.1016/j.ijar.2016.08.007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012087303
    116 rdf:type schema:CreativeWork
    117 https://doi.org/10.1016/j.ijar.2018.01.008 schema:sameAs https://app.dimensions.ai/details/publication/pub.1103173437
    118 rdf:type schema:CreativeWork
    119 https://doi.org/10.1016/j.ijar.2018.11.010 schema:sameAs https://app.dimensions.ai/details/publication/pub.1110009943
    120 rdf:type schema:CreativeWork
    121 https://doi.org/10.1016/j.ins.2007.09.019 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035147250
    122 rdf:type schema:CreativeWork
    123 https://doi.org/10.1016/j.ins.2011.04.039 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007740063
    124 rdf:type schema:CreativeWork
    125 https://doi.org/10.1016/j.ins.2011.07.010 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041001392
    126 rdf:type schema:CreativeWork
    127 https://doi.org/10.1016/j.ins.2013.06.057 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013576443
    128 rdf:type schema:CreativeWork
    129 https://doi.org/10.1016/j.ins.2016.03.019 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024415548
    130 rdf:type schema:CreativeWork
    131 https://doi.org/10.1016/j.ins.2016.09.012 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009891547
    132 rdf:type schema:CreativeWork
    133 https://doi.org/10.1016/j.ins.2017.08.038 schema:sameAs https://app.dimensions.ai/details/publication/pub.1091117634
    134 rdf:type schema:CreativeWork
    135 https://doi.org/10.1016/j.ins.2017.08.053 schema:sameAs https://app.dimensions.ai/details/publication/pub.1091219263
    136 rdf:type schema:CreativeWork
    137 https://doi.org/10.1016/j.knosys.2012.10.018 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020386828
    138 rdf:type schema:CreativeWork
    139 https://doi.org/10.1016/j.knosys.2014.03.021 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034075745
    140 rdf:type schema:CreativeWork
    141 https://doi.org/10.1016/j.knosys.2014.08.030 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004326664
    142 rdf:type schema:CreativeWork
    143 https://doi.org/10.1016/j.knosys.2015.09.011 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013031835
    144 rdf:type schema:CreativeWork
    145 https://doi.org/10.1016/j.knosys.2016.04.012 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041694911
    146 rdf:type schema:CreativeWork
    147 https://doi.org/10.1016/j.knosys.2017.09.006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1091500910
    148 rdf:type schema:CreativeWork
    149 https://doi.org/10.1016/j.knosys.2017.09.009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1091504837
    150 rdf:type schema:CreativeWork
    151 https://doi.org/10.1016/j.knosys.2018.05.020 schema:sameAs https://app.dimensions.ai/details/publication/pub.1104152032
    152 rdf:type schema:CreativeWork
    153 https://doi.org/10.1016/j.knosys.2018.11.034 schema:sameAs https://app.dimensions.ai/details/publication/pub.1110275347
    154 rdf:type schema:CreativeWork
    155 https://doi.org/10.1016/j.patcog.2011.02.020 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013531072
    156 rdf:type schema:CreativeWork
    157 https://doi.org/10.1016/j.patcog.2016.02.013 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028810245
    158 rdf:type schema:CreativeWork
    159 https://doi.org/10.1109/tfuzz.2005.864086 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061605898
    160 rdf:type schema:CreativeWork
    161 https://doi.org/10.1109/tfuzz.2011.2167235 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061606503
    162 rdf:type schema:CreativeWork
    163 https://doi.org/10.1109/tfuzz.2015.2393391 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018878727
    164 rdf:type schema:CreativeWork
    165 https://doi.org/10.1109/tfuzz.2017.2718492 schema:sameAs https://app.dimensions.ai/details/publication/pub.1093744758
    166 rdf:type schema:CreativeWork
    167 https://doi.org/10.1109/tfuzz.2017.2768044 schema:sameAs https://app.dimensions.ai/details/publication/pub.1092448177
    168 rdf:type schema:CreativeWork
    169 https://doi.org/10.1109/tkde.2011.149 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061662346
    170 rdf:type schema:CreativeWork
    171 https://doi.org/10.1109/tkde.2011.89 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061662498
    172 rdf:type schema:CreativeWork
    173 https://doi.org/10.1109/tnnls.2017.2710422 schema:sameAs https://app.dimensions.ai/details/publication/pub.1086385715
    174 rdf:type schema:CreativeWork
    175 https://doi.org/10.1109/tsmcb.2009.2024166 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061797096
    176 rdf:type schema:CreativeWork
    177 https://doi.org/10.1142/s0218488508005121 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062977098
    178 rdf:type schema:CreativeWork
     




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


    ...