World’s Best Universities and Personalized Rankings View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2017

AUTHORS

Mario Inostroza-Ponta , Natalie Jane de Vries , Pablo Moscato

ABSTRACT

This chapter presents a heuristic for a multi-objective ranking problem using a dataset of international interest as an example of its application, namely, the ranking of the world’s top educational institutions. The problem of ranking academic institutions is a subject of keen interest for administrators, consumers, and research policy makers. From a mathematical perspective, the proposed heuristic addresses the need for more transparent models and associated methods related to the problem of identifying sound relative rankings of objects with multiple attributes. The low complexity of the method allows software implementations that scale well for thousands of objects as well as permitting reasonable visualization. It is shown that a simple and multi-objective-aware ranking system can easily be implemented, which naturally leads to intuitive research policies resulting from varying scenarios presented within. The only assumption that this method relies on is the ability to sort the candidate objects according to each given attribute. Thus the attributes could be numerical or ordinal in nature. This helps to avoid the selection of an ad hoc single score based on an arbitrary assignment of attributes’ weights as other heuristics do. To illustrate the use of this proposed methodology, results are presented and obtained using the dataset on the ranking of world universities (of the years 2007–2012), by academic performance, published annually by ARWU. More... »

PAGES

1-37

References to SciGraph publications

  • 1987-08. Evaluating natural areas using multiple criteria: Theory and practice in ENVIRONMENTAL MANAGEMENT
  • 2007-12. International ranking systems for universities and institutions: a critical appraisal in BMC MEDICINE
  • 2001-07-06. Evolutionary Multi-objective Ranking with Uncertainty and Noise in EVOLUTIONARY MULTI-CRITERION OPTIMIZATION
  • 2007-07. Irreproducibility of the results of the Shanghai academic ranking of world universities in SCIENTOMETRICS
  • 2016. Evolution of Ideas About Rating and Ranking in Sports in HANDBOOK OF RATINGS
  • 2007. A Multi-criteria Service Ranking Approach Based on Non-Functional Properties Rules Evaluation in SERVICE-ORIENTED COMPUTING – ICSOC 2007
  • 2013-02. Reproducibility of the Shanghai academic ranking of world universities results in SCIENTOMETRICS
  • 2011-06. A fresh approach to evaluating the academic ranking of world universities in SCIENTOMETRICS
  • 2007-06. Comparative study of international academic rankings of universities in SCIENTOMETRICS
  • 2005. Pareto-Front Exploitation in Symbolic Regression in GENETIC PROGRAMMING THEORY AND PRACTICE II
  • 2012. Score Transformation in Linear Combination for Multi-criteria Relevance Ranking in ADVANCES IN INFORMATION RETRIEVAL
  • 2003-12. Funding, resource allocation, and performance in higher education systems in HIGHER EDUCATION
  • 2004. Economics, Management and Optimization in Sports in NONE
  • 2013-10. A strategy of multi-criteria decision-making task ranking in social-networks in THE JOURNAL OF SUPERCOMPUTING
  • 2012-08. A multiple criteria ranking method based on game cross-evaluation approach in ANNALS OF OPERATIONS RESEARCH
  • 2005. A Multiobjective Evolutionary Algorithm for Deriving Final Ranking from a Fuzzy Outranking Relation in EVOLUTIONARY MULTI-CRITERION OPTIMIZATION
  • Book

    TITLE

    Handbook of Heuristics

    ISBN

    978-3-319-07153-4
    978-3-319-07153-4

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-319-07153-4_60-2

    DOI

    http://dx.doi.org/10.1007/978-3-319-07153-4_60-2

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1090953390


    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/2008/0801", 
            "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/2008/08", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Information and Computing Sciences", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "name": [
                "Departamento de Ingenier\u00eda Inform\u00e1tica, Universidad de Santiago"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Inostroza-Ponta", 
            "givenName": "Mario", 
            "id": "sg:person.0730727503.52", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0730727503.52"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "name": [
                "School of Electrical Engineering and Computing, Faculty of Engineering and Built Environment"
              ], 
              "type": "Organization"
            }, 
            "familyName": "de Vries", 
            "givenName": "Natalie Jane", 
            "id": "sg:person.014443204615.56", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014443204615.56"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "name": [
                "School of Electrical Engineering and Computing, Faculty of Engineering and Built Environment"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Moscato", 
            "givenName": "Pablo", 
            "id": "sg:person.01051225363.23", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01051225363.23"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "https://doi.org/10.1093/bioinformatics/btg399", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1000324523"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s10479-010-0817-8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1000783283", 
              "https://doi.org/10.1007/s10479-010-0817-8"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s10479-010-0817-8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1000783283", 
              "https://doi.org/10.1007/s10479-010-0817-8"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1080/03797720500260124", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1004320991"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-540-24734-0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1007978563", 
              "https://doi.org/10.1007/978-3-540-24734-0"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-540-24734-0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1007978563", 
              "https://doi.org/10.1007/978-3-540-24734-0"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-540-31880-4_17", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1009451792", 
              "https://doi.org/10.1007/978-3-540-31880-4_17"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-540-31880-4_17", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1009451792", 
              "https://doi.org/10.1007/978-3-540-31880-4_17"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ejor.2007.08.013", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1009454530"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0377-2217(02)00705-1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1009684341"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0377-2217(02)00705-1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1009684341"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.procs.2012.09.043", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016533680"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-540-74974-5_40", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1017416807", 
              "https://doi.org/10.1007/978-3-540-74974-5_40"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-540-74974-5_40", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1017416807", 
              "https://doi.org/10.1007/978-3-540-74974-5_40"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-642-28997-2_22", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1018864752", 
              "https://doi.org/10.1007/978-3-642-28997-2_22"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1741-7015-5-30", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1019535416", 
              "https://doi.org/10.1186/1741-7015-5-30"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.aap.2006.12.001", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1020687804"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1145/1871437.1871763", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021184676"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.eswa.2014.03.036", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021802364"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.landurbplan.2007.10.004", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1025102387"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.dss.2013.10.001", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1027711283"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0006-3207(75)90033-6", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028043255"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0006-3207(75)90033-6", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028043255"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0377-2217(00)00101-6", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028206081"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1080/0260293930180102", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1033069362"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1145/2187836.2187894", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1034409330"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/3-540-44719-9_23", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1034472889", 
              "https://doi.org/10.1007/3-540-44719-9_23"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/3-540-44719-9_23", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1034472889", 
              "https://doi.org/10.1007/3-540-44719-9_23"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1179/bjo.22.3.259", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1036310366"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/bf01867653", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1037607813", 
              "https://doi.org/10.1007/bf01867653"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/bf01867653", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1037607813", 
              "https://doi.org/10.1007/bf01867653"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1023/a:1027381906977", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1038819394", 
              "https://doi.org/10.1023/a:1027381906977"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11192-007-1653-8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1039544241", 
              "https://doi.org/10.1007/s11192-007-1653-8"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11192-007-1712-1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1040102798", 
              "https://doi.org/10.1007/s11192-007-1712-1"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11227-013-0934-7", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1040629539", 
              "https://doi.org/10.1007/s11227-013-0934-7"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1145/321526.321534", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1040716654"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.eswa.2010.07.029", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1042383608"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pone.0102768", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1042449689"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ejor.2011.09.032", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043199421"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ejor.2011.09.032", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043199421"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.eswa.2010.12.119", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043292148"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.mcm.2010.10.001", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043939043"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1111/exsy.12108", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1044737960"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1080/03797720500260116", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1045576367"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11192-012-0801-y", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1046144816", 
              "https://doi.org/10.1007/s11192-012-0801-y"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/ajmg.b.30743", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1046480422"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.respol.2010.09.003", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1046782563"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.sigpro.2012.04.020", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1048081280"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-319-39261-5_7", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1048582171", 
              "https://doi.org/10.1007/978-3-319-39261-5_7"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pone.0017249", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1050436686"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1080/13600800701351660", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1050935033"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ejor.2013.01.022", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1051466867"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ejor.2003.06.007", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1051728693"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ejor.2003.06.007", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1051728693"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11192-011-0361-6", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1052343240", 
              "https://doi.org/10.1007/s11192-011-0361-6"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/0-387-23254-0_17", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1052612226", 
              "https://doi.org/10.1007/0-387-23254-0_17"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1021/ci010268p", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1055401240"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1021/ci010268p", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1055401240"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1021/ci800023x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1055404460"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1021/ci800023x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1055404460"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/tevc.2006.876362", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061604747"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.5465/amle.2009.37012181", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1072896359"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://app.dimensions.ai/details/publication/pub.1077208591", 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/iembs.2006.260896", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1077506544"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/iembs.2006.260896", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1077506544"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://app.dimensions.ai/details/publication/pub.1082702070", 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/iccsa.2013.44", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1093497785"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/mcdm.2014.7007184", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1093804440"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2017", 
        "datePublishedReg": "2017-01-01", 
        "description": "This chapter presents a heuristic for a multi-objective ranking problem using a dataset of international interest as an example of its application, namely, the ranking of the world\u2019s top educational institutions. The problem of ranking academic institutions is a subject of keen interest for administrators, consumers, and research policy makers. From a mathematical perspective, the proposed heuristic addresses the need for more transparent models and associated methods related to the problem of identifying sound relative rankings of objects with multiple attributes. The low complexity of the method allows software implementations that scale well for thousands of objects as well as permitting reasonable visualization. It is shown that a simple and multi-objective-aware ranking system can easily be implemented, which naturally leads to intuitive research policies resulting from varying scenarios presented within. The only assumption that this method relies on is the ability to sort the candidate objects according to each given attribute. Thus the attributes could be numerical or ordinal in nature. This helps to avoid the selection of an ad hoc single score based on an arbitrary assignment of attributes\u2019 weights as other heuristics do. To illustrate the use of this proposed methodology, results are presented and obtained using the dataset on the ranking of world universities (of the years 2007\u20132012), by academic performance, published annually by ARWU.", 
        "editor": [
          {
            "familyName": "Mart\u00ed", 
            "givenName": "Rafael", 
            "type": "Person"
          }, 
          {
            "familyName": "Panos", 
            "givenName": "Pardalos", 
            "type": "Person"
          }, 
          {
            "familyName": "Resende", 
            "givenName": "Mauricio G. C.", 
            "type": "Person"
          }
        ], 
        "genre": "chapter", 
        "id": "sg:pub.10.1007/978-3-319-07153-4_60-2", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": false, 
        "isFundedItemOf": [
          {
            "id": "sg:grant.3566083", 
            "type": "MonetaryGrant"
          }, 
          {
            "id": "sg:grant.3567935", 
            "type": "MonetaryGrant"
          }, 
          {
            "id": "sg:grant.3931445", 
            "type": "MonetaryGrant"
          }
        ], 
        "isPartOf": {
          "isbn": [
            "978-3-319-07153-4", 
            "978-3-319-07153-4"
          ], 
          "name": "Handbook of Heuristics", 
          "type": "Book"
        }, 
        "name": "World\u2019s Best Universities and Personalized Rankings", 
        "pagination": "1-37", 
        "productId": [
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1007/978-3-319-07153-4_60-2"
            ]
          }, 
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "58f8d9bc37d58d0bc38fe4a6842e1c08ef585dd918d376d3146333b111e4ccff"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1090953390"
            ]
          }
        ], 
        "publisher": {
          "location": "Cham", 
          "name": "Springer International Publishing", 
          "type": "Organisation"
        }, 
        "sameAs": [
          "https://doi.org/10.1007/978-3-319-07153-4_60-2", 
          "https://app.dimensions.ai/details/publication/pub.1090953390"
        ], 
        "sdDataset": "chapters", 
        "sdDatePublished": "2019-04-15T18:52", 
        "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/v90/0000000001_0000000264/records_8681_00000601.jsonl", 
        "type": "Chapter", 
        "url": "http://link.springer.com/10.1007/978-3-319-07153-4_60-2"
      }
    ]
     

    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.10.1007/978-3-319-07153-4_60-2'

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

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-07153-4_60-2'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-07153-4_60-2'

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

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-07153-4_60-2'


     

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

    276 TRIPLES      23 PREDICATES      82 URIs      20 LITERALS      8 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1007/978-3-319-07153-4_60-2 schema:about anzsrc-for:08
    2 anzsrc-for:0801
    3 schema:author Nb2984227732546578ab0e41f7ecdb554
    4 schema:citation sg:pub.10.1007/0-387-23254-0_17
    5 sg:pub.10.1007/3-540-44719-9_23
    6 sg:pub.10.1007/978-3-319-39261-5_7
    7 sg:pub.10.1007/978-3-540-24734-0
    8 sg:pub.10.1007/978-3-540-31880-4_17
    9 sg:pub.10.1007/978-3-540-74974-5_40
    10 sg:pub.10.1007/978-3-642-28997-2_22
    11 sg:pub.10.1007/bf01867653
    12 sg:pub.10.1007/s10479-010-0817-8
    13 sg:pub.10.1007/s11192-007-1653-8
    14 sg:pub.10.1007/s11192-007-1712-1
    15 sg:pub.10.1007/s11192-011-0361-6
    16 sg:pub.10.1007/s11192-012-0801-y
    17 sg:pub.10.1007/s11227-013-0934-7
    18 sg:pub.10.1023/a:1027381906977
    19 sg:pub.10.1186/1741-7015-5-30
    20 https://app.dimensions.ai/details/publication/pub.1077208591
    21 https://app.dimensions.ai/details/publication/pub.1082702070
    22 https://doi.org/10.1002/ajmg.b.30743
    23 https://doi.org/10.1016/0006-3207(75)90033-6
    24 https://doi.org/10.1016/j.aap.2006.12.001
    25 https://doi.org/10.1016/j.dss.2013.10.001
    26 https://doi.org/10.1016/j.ejor.2003.06.007
    27 https://doi.org/10.1016/j.ejor.2007.08.013
    28 https://doi.org/10.1016/j.ejor.2011.09.032
    29 https://doi.org/10.1016/j.ejor.2013.01.022
    30 https://doi.org/10.1016/j.eswa.2010.07.029
    31 https://doi.org/10.1016/j.eswa.2010.12.119
    32 https://doi.org/10.1016/j.eswa.2014.03.036
    33 https://doi.org/10.1016/j.landurbplan.2007.10.004
    34 https://doi.org/10.1016/j.mcm.2010.10.001
    35 https://doi.org/10.1016/j.procs.2012.09.043
    36 https://doi.org/10.1016/j.respol.2010.09.003
    37 https://doi.org/10.1016/j.sigpro.2012.04.020
    38 https://doi.org/10.1016/s0377-2217(00)00101-6
    39 https://doi.org/10.1016/s0377-2217(02)00705-1
    40 https://doi.org/10.1021/ci010268p
    41 https://doi.org/10.1021/ci800023x
    42 https://doi.org/10.1080/0260293930180102
    43 https://doi.org/10.1080/03797720500260116
    44 https://doi.org/10.1080/03797720500260124
    45 https://doi.org/10.1080/13600800701351660
    46 https://doi.org/10.1093/bioinformatics/btg399
    47 https://doi.org/10.1109/iccsa.2013.44
    48 https://doi.org/10.1109/iembs.2006.260896
    49 https://doi.org/10.1109/mcdm.2014.7007184
    50 https://doi.org/10.1109/tevc.2006.876362
    51 https://doi.org/10.1111/exsy.12108
    52 https://doi.org/10.1145/1871437.1871763
    53 https://doi.org/10.1145/2187836.2187894
    54 https://doi.org/10.1145/321526.321534
    55 https://doi.org/10.1179/bjo.22.3.259
    56 https://doi.org/10.1371/journal.pone.0017249
    57 https://doi.org/10.1371/journal.pone.0102768
    58 https://doi.org/10.5465/amle.2009.37012181
    59 schema:datePublished 2017
    60 schema:datePublishedReg 2017-01-01
    61 schema:description This chapter presents a heuristic for a multi-objective ranking problem using a dataset of international interest as an example of its application, namely, the ranking of the world’s top educational institutions. The problem of ranking academic institutions is a subject of keen interest for administrators, consumers, and research policy makers. From a mathematical perspective, the proposed heuristic addresses the need for more transparent models and associated methods related to the problem of identifying sound relative rankings of objects with multiple attributes. The low complexity of the method allows software implementations that scale well for thousands of objects as well as permitting reasonable visualization. It is shown that a simple and multi-objective-aware ranking system can easily be implemented, which naturally leads to intuitive research policies resulting from varying scenarios presented within. The only assumption that this method relies on is the ability to sort the candidate objects according to each given attribute. Thus the attributes could be numerical or ordinal in nature. This helps to avoid the selection of an ad hoc single score based on an arbitrary assignment of attributes’ weights as other heuristics do. To illustrate the use of this proposed methodology, results are presented and obtained using the dataset on the ranking of world universities (of the years 2007–2012), by academic performance, published annually by ARWU.
    62 schema:editor Nd5d167a1c1fc4a2ba2d25cf22ce50251
    63 schema:genre chapter
    64 schema:inLanguage en
    65 schema:isAccessibleForFree false
    66 schema:isPartOf N5f7447c35b56426cb912465550d64045
    67 schema:name World’s Best Universities and Personalized Rankings
    68 schema:pagination 1-37
    69 schema:productId N170a565e70814319ba9f1d81d9ea1f58
    70 N2879a0ba67cc45f1b2eaeffdcd65177d
    71 N78009224ab704ce781710008fa777f3f
    72 schema:publisher N2419548eb15b418b9c539ba488aca302
    73 schema:sameAs https://app.dimensions.ai/details/publication/pub.1090953390
    74 https://doi.org/10.1007/978-3-319-07153-4_60-2
    75 schema:sdDatePublished 2019-04-15T18:52
    76 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    77 schema:sdPublisher N4491585ca3c7438c93529c1c5045fa64
    78 schema:url http://link.springer.com/10.1007/978-3-319-07153-4_60-2
    79 sgo:license sg:explorer/license/
    80 sgo:sdDataset chapters
    81 rdf:type schema:Chapter
    82 N0308c4934d014cdab5d813a375c36461 rdf:first sg:person.01051225363.23
    83 rdf:rest rdf:nil
    84 N08d29d02d31847cf9cc818f10967176f schema:name School of Electrical Engineering and Computing, Faculty of Engineering and Built Environment
    85 rdf:type schema:Organization
    86 N13714764963e470ca34dc0aa7f5a1fb7 schema:familyName Panos
    87 schema:givenName Pardalos
    88 rdf:type schema:Person
    89 N170a565e70814319ba9f1d81d9ea1f58 schema:name readcube_id
    90 schema:value 58f8d9bc37d58d0bc38fe4a6842e1c08ef585dd918d376d3146333b111e4ccff
    91 rdf:type schema:PropertyValue
    92 N2419548eb15b418b9c539ba488aca302 schema:location Cham
    93 schema:name Springer International Publishing
    94 rdf:type schema:Organisation
    95 N2879a0ba67cc45f1b2eaeffdcd65177d schema:name doi
    96 schema:value 10.1007/978-3-319-07153-4_60-2
    97 rdf:type schema:PropertyValue
    98 N3f26f7d1f635435f8232e5a1997066a7 schema:familyName Martí
    99 schema:givenName Rafael
    100 rdf:type schema:Person
    101 N4491585ca3c7438c93529c1c5045fa64 schema:name Springer Nature - SN SciGraph project
    102 rdf:type schema:Organization
    103 N5f7447c35b56426cb912465550d64045 schema:isbn 978-3-319-07153-4
    104 schema:name Handbook of Heuristics
    105 rdf:type schema:Book
    106 N779d562617ca4e7db19d3011caeb6e33 schema:familyName Resende
    107 schema:givenName Mauricio G. C.
    108 rdf:type schema:Person
    109 N78009224ab704ce781710008fa777f3f schema:name dimensions_id
    110 schema:value pub.1090953390
    111 rdf:type schema:PropertyValue
    112 Nb2984227732546578ab0e41f7ecdb554 rdf:first sg:person.0730727503.52
    113 rdf:rest Need874e3e95d4539ac6b8510d5dbccd7
    114 Nc6ba1986d62749c18b22224108f997eb rdf:first N779d562617ca4e7db19d3011caeb6e33
    115 rdf:rest rdf:nil
    116 Nd2c4f60b0c5543c684220ba5974a995a schema:name School of Electrical Engineering and Computing, Faculty of Engineering and Built Environment
    117 rdf:type schema:Organization
    118 Nd3dd73ce099e477c93cb016b776ae786 schema:name Departamento de Ingeniería Informática, Universidad de Santiago
    119 rdf:type schema:Organization
    120 Nd5d167a1c1fc4a2ba2d25cf22ce50251 rdf:first N3f26f7d1f635435f8232e5a1997066a7
    121 rdf:rest Ndf86b56f9b21475198b89456ec68592f
    122 Ndf86b56f9b21475198b89456ec68592f rdf:first N13714764963e470ca34dc0aa7f5a1fb7
    123 rdf:rest Nc6ba1986d62749c18b22224108f997eb
    124 Need874e3e95d4539ac6b8510d5dbccd7 rdf:first sg:person.014443204615.56
    125 rdf:rest N0308c4934d014cdab5d813a375c36461
    126 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
    127 schema:name Information and Computing Sciences
    128 rdf:type schema:DefinedTerm
    129 anzsrc-for:0801 schema:inDefinedTermSet anzsrc-for:
    130 schema:name Artificial Intelligence and Image Processing
    131 rdf:type schema:DefinedTerm
    132 sg:grant.3566083 http://pending.schema.org/fundedItem sg:pub.10.1007/978-3-319-07153-4_60-2
    133 rdf:type schema:MonetaryGrant
    134 sg:grant.3567935 http://pending.schema.org/fundedItem sg:pub.10.1007/978-3-319-07153-4_60-2
    135 rdf:type schema:MonetaryGrant
    136 sg:grant.3931445 http://pending.schema.org/fundedItem sg:pub.10.1007/978-3-319-07153-4_60-2
    137 rdf:type schema:MonetaryGrant
    138 sg:person.01051225363.23 schema:affiliation Nd2c4f60b0c5543c684220ba5974a995a
    139 schema:familyName Moscato
    140 schema:givenName Pablo
    141 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01051225363.23
    142 rdf:type schema:Person
    143 sg:person.014443204615.56 schema:affiliation N08d29d02d31847cf9cc818f10967176f
    144 schema:familyName de Vries
    145 schema:givenName Natalie Jane
    146 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014443204615.56
    147 rdf:type schema:Person
    148 sg:person.0730727503.52 schema:affiliation Nd3dd73ce099e477c93cb016b776ae786
    149 schema:familyName Inostroza-Ponta
    150 schema:givenName Mario
    151 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0730727503.52
    152 rdf:type schema:Person
    153 sg:pub.10.1007/0-387-23254-0_17 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052612226
    154 https://doi.org/10.1007/0-387-23254-0_17
    155 rdf:type schema:CreativeWork
    156 sg:pub.10.1007/3-540-44719-9_23 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034472889
    157 https://doi.org/10.1007/3-540-44719-9_23
    158 rdf:type schema:CreativeWork
    159 sg:pub.10.1007/978-3-319-39261-5_7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048582171
    160 https://doi.org/10.1007/978-3-319-39261-5_7
    161 rdf:type schema:CreativeWork
    162 sg:pub.10.1007/978-3-540-24734-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007978563
    163 https://doi.org/10.1007/978-3-540-24734-0
    164 rdf:type schema:CreativeWork
    165 sg:pub.10.1007/978-3-540-31880-4_17 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009451792
    166 https://doi.org/10.1007/978-3-540-31880-4_17
    167 rdf:type schema:CreativeWork
    168 sg:pub.10.1007/978-3-540-74974-5_40 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017416807
    169 https://doi.org/10.1007/978-3-540-74974-5_40
    170 rdf:type schema:CreativeWork
    171 sg:pub.10.1007/978-3-642-28997-2_22 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018864752
    172 https://doi.org/10.1007/978-3-642-28997-2_22
    173 rdf:type schema:CreativeWork
    174 sg:pub.10.1007/bf01867653 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037607813
    175 https://doi.org/10.1007/bf01867653
    176 rdf:type schema:CreativeWork
    177 sg:pub.10.1007/s10479-010-0817-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000783283
    178 https://doi.org/10.1007/s10479-010-0817-8
    179 rdf:type schema:CreativeWork
    180 sg:pub.10.1007/s11192-007-1653-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039544241
    181 https://doi.org/10.1007/s11192-007-1653-8
    182 rdf:type schema:CreativeWork
    183 sg:pub.10.1007/s11192-007-1712-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040102798
    184 https://doi.org/10.1007/s11192-007-1712-1
    185 rdf:type schema:CreativeWork
    186 sg:pub.10.1007/s11192-011-0361-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052343240
    187 https://doi.org/10.1007/s11192-011-0361-6
    188 rdf:type schema:CreativeWork
    189 sg:pub.10.1007/s11192-012-0801-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1046144816
    190 https://doi.org/10.1007/s11192-012-0801-y
    191 rdf:type schema:CreativeWork
    192 sg:pub.10.1007/s11227-013-0934-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040629539
    193 https://doi.org/10.1007/s11227-013-0934-7
    194 rdf:type schema:CreativeWork
    195 sg:pub.10.1023/a:1027381906977 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038819394
    196 https://doi.org/10.1023/a:1027381906977
    197 rdf:type schema:CreativeWork
    198 sg:pub.10.1186/1741-7015-5-30 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019535416
    199 https://doi.org/10.1186/1741-7015-5-30
    200 rdf:type schema:CreativeWork
    201 https://app.dimensions.ai/details/publication/pub.1077208591 schema:CreativeWork
    202 https://app.dimensions.ai/details/publication/pub.1082702070 schema:CreativeWork
    203 https://doi.org/10.1002/ajmg.b.30743 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046480422
    204 rdf:type schema:CreativeWork
    205 https://doi.org/10.1016/0006-3207(75)90033-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028043255
    206 rdf:type schema:CreativeWork
    207 https://doi.org/10.1016/j.aap.2006.12.001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020687804
    208 rdf:type schema:CreativeWork
    209 https://doi.org/10.1016/j.dss.2013.10.001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027711283
    210 rdf:type schema:CreativeWork
    211 https://doi.org/10.1016/j.ejor.2003.06.007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051728693
    212 rdf:type schema:CreativeWork
    213 https://doi.org/10.1016/j.ejor.2007.08.013 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009454530
    214 rdf:type schema:CreativeWork
    215 https://doi.org/10.1016/j.ejor.2011.09.032 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043199421
    216 rdf:type schema:CreativeWork
    217 https://doi.org/10.1016/j.ejor.2013.01.022 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051466867
    218 rdf:type schema:CreativeWork
    219 https://doi.org/10.1016/j.eswa.2010.07.029 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042383608
    220 rdf:type schema:CreativeWork
    221 https://doi.org/10.1016/j.eswa.2010.12.119 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043292148
    222 rdf:type schema:CreativeWork
    223 https://doi.org/10.1016/j.eswa.2014.03.036 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021802364
    224 rdf:type schema:CreativeWork
    225 https://doi.org/10.1016/j.landurbplan.2007.10.004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025102387
    226 rdf:type schema:CreativeWork
    227 https://doi.org/10.1016/j.mcm.2010.10.001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043939043
    228 rdf:type schema:CreativeWork
    229 https://doi.org/10.1016/j.procs.2012.09.043 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016533680
    230 rdf:type schema:CreativeWork
    231 https://doi.org/10.1016/j.respol.2010.09.003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046782563
    232 rdf:type schema:CreativeWork
    233 https://doi.org/10.1016/j.sigpro.2012.04.020 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048081280
    234 rdf:type schema:CreativeWork
    235 https://doi.org/10.1016/s0377-2217(00)00101-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028206081
    236 rdf:type schema:CreativeWork
    237 https://doi.org/10.1016/s0377-2217(02)00705-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009684341
    238 rdf:type schema:CreativeWork
    239 https://doi.org/10.1021/ci010268p schema:sameAs https://app.dimensions.ai/details/publication/pub.1055401240
    240 rdf:type schema:CreativeWork
    241 https://doi.org/10.1021/ci800023x schema:sameAs https://app.dimensions.ai/details/publication/pub.1055404460
    242 rdf:type schema:CreativeWork
    243 https://doi.org/10.1080/0260293930180102 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033069362
    244 rdf:type schema:CreativeWork
    245 https://doi.org/10.1080/03797720500260116 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045576367
    246 rdf:type schema:CreativeWork
    247 https://doi.org/10.1080/03797720500260124 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004320991
    248 rdf:type schema:CreativeWork
    249 https://doi.org/10.1080/13600800701351660 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050935033
    250 rdf:type schema:CreativeWork
    251 https://doi.org/10.1093/bioinformatics/btg399 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000324523
    252 rdf:type schema:CreativeWork
    253 https://doi.org/10.1109/iccsa.2013.44 schema:sameAs https://app.dimensions.ai/details/publication/pub.1093497785
    254 rdf:type schema:CreativeWork
    255 https://doi.org/10.1109/iembs.2006.260896 schema:sameAs https://app.dimensions.ai/details/publication/pub.1077506544
    256 rdf:type schema:CreativeWork
    257 https://doi.org/10.1109/mcdm.2014.7007184 schema:sameAs https://app.dimensions.ai/details/publication/pub.1093804440
    258 rdf:type schema:CreativeWork
    259 https://doi.org/10.1109/tevc.2006.876362 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061604747
    260 rdf:type schema:CreativeWork
    261 https://doi.org/10.1111/exsy.12108 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044737960
    262 rdf:type schema:CreativeWork
    263 https://doi.org/10.1145/1871437.1871763 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021184676
    264 rdf:type schema:CreativeWork
    265 https://doi.org/10.1145/2187836.2187894 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034409330
    266 rdf:type schema:CreativeWork
    267 https://doi.org/10.1145/321526.321534 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040716654
    268 rdf:type schema:CreativeWork
    269 https://doi.org/10.1179/bjo.22.3.259 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036310366
    270 rdf:type schema:CreativeWork
    271 https://doi.org/10.1371/journal.pone.0017249 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050436686
    272 rdf:type schema:CreativeWork
    273 https://doi.org/10.1371/journal.pone.0102768 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042449689
    274 rdf:type schema:CreativeWork
    275 https://doi.org/10.5465/amle.2009.37012181 schema:sameAs https://app.dimensions.ai/details/publication/pub.1072896359
    276 rdf:type schema:CreativeWork
     




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


    ...