Ontology type: schema:ScholarlyArticle
2002-03
AUTHORSMissae Yamamoto, Gilberto Camara, Luiz Antonio Nogueira Lorena
ABSTRACTThe generation of better label placement configurations in maps is a problem that comes up in automated cartographic production. The objective of a good label placement is to display the geographic position of the features with their corresponding label in a clear and harmonious fashion, following accepted cartographic conventions. In this work, we have approached this problem from a combinatorial optimization point of view, and our research consisted of the evaluation of the tabu search (TS) heuristic applied to cartographic label placement. When compared, in real and random test cases, with techniques such as simulated annealing and genetic algorithm (GA), TS has proven to be an efficient choice, with the best performance in quality. We concluded that TS is a recommended method to solve cartographic label placement problem of point features, due to its simplicity, practicality, efficiency and good performance along with its ability to generate quality solutions in acceptable computational time. More... »
PAGES77-90
http://scigraph.springernature.com/pub.10.1023/a:1013720231747
DOIhttp://dx.doi.org/10.1023/a:1013720231747
DIMENSIONShttps://app.dimensions.ai/details/publication/pub.1032925812
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": {
"alternateName": "National Institute for Space Research",
"id": "https://www.grid.ac/institutes/grid.419222.e",
"name": [
"Brazilian Institute of Space Research (INPE), SP, BR"
],
"type": "Organization"
},
"familyName": "Yamamoto",
"givenName": "Missae",
"id": "sg:person.010111137365.52",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010111137365.52"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "National Institute for Space Research",
"id": "https://www.grid.ac/institutes/grid.419222.e",
"name": [
"Brazilian Institute of Space Research (INPE), SP, BR"
],
"type": "Organization"
},
"familyName": "Camara",
"givenName": "Gilberto",
"id": "sg:person.012450113021.58",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012450113021.58"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "National Institute for Space Research",
"id": "https://www.grid.ac/institutes/grid.419222.e",
"name": [
"Brazilian Institute of Space Research (INPE), SP, BR"
],
"type": "Organization"
},
"familyName": "Lorena",
"givenName": "Luiz Antonio Nogueira",
"id": "sg:person.013705300747.26",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013705300747.26"
],
"type": "Person"
}
],
"citation": [
{
"id": "https://doi.org/10.1016/0097-8493(96)00008-8",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1018244423"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1559/152304082783948367",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1023233495"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1145/212332.212334",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1028621212"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/b978-0-12-336156-1.50064-1",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1034901284"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1287/ijoc.1.3.190",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1064706391"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1287/ijoc.2.1.4",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1064707137"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1287/ijoc.9.3.266",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1064707635"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1287/inte.20.4.74",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1064709328"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1287/opre.38.5.752",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1064730153"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.3138/9258-63ql-3988-110h",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1070998900"
],
"type": "CreativeWork"
}
],
"datePublished": "2002-03",
"datePublishedReg": "2002-03-01",
"description": "The generation of better label placement configurations in maps is a problem that comes up in automated cartographic production. The objective of a good label placement is to display the geographic position of the features with their corresponding label in a clear and harmonious fashion, following accepted cartographic conventions. In this work, we have approached this problem from a combinatorial optimization point of view, and our research consisted of the evaluation of the tabu search (TS) heuristic applied to cartographic label placement. When compared, in real and random test cases, with techniques such as simulated annealing and genetic algorithm (GA), TS has proven to be an efficient choice, with the best performance in quality. We concluded that TS is a recommended method to solve cartographic label placement problem of point features, due to its simplicity, practicality, efficiency and good performance along with its ability to generate quality solutions in acceptable computational time.",
"genre": "research_article",
"id": "sg:pub.10.1023/a:1013720231747",
"inLanguage": [
"en"
],
"isAccessibleForFree": false,
"isPartOf": [
{
"id": "sg:journal.1043850",
"issn": [
"1384-6175",
"1573-7624"
],
"name": "GeoInformatica",
"type": "Periodical"
},
{
"issueNumber": "1",
"type": "PublicationIssue"
},
{
"type": "PublicationVolume",
"volumeNumber": "6"
}
],
"name": "Tabu Search Heuristic for Point-Feature Cartographic Label Placement",
"pagination": "77-90",
"productId": [
{
"name": "readcube_id",
"type": "PropertyValue",
"value": [
"9cdacd0d01c11618624e5282e2c9add7080e465f55aa25664a2f3573943ca960"
]
},
{
"name": "doi",
"type": "PropertyValue",
"value": [
"10.1023/a:1013720231747"
]
},
{
"name": "dimensions_id",
"type": "PropertyValue",
"value": [
"pub.1032925812"
]
}
],
"sameAs": [
"https://doi.org/10.1023/a:1013720231747",
"https://app.dimensions.ai/details/publication/pub.1032925812"
],
"sdDataset": "articles",
"sdDatePublished": "2019-04-10T19:06",
"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_8678_00000500.jsonl",
"type": "ScholarlyArticle",
"url": "http://link.springer.com/10.1023/A:1013720231747"
}
]Download the RDF metadata as: json-ld nt turtle xml License info
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.10.1023/a:1013720231747'
N-Triples is a line-based linked data format ideal for batch operations.
curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1023/a:1013720231747'
Turtle is a human-readable linked data format.
curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1023/a:1013720231747'
RDF/XML is a standard XML format for linked data.
curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1023/a:1013720231747'
This table displays all metadata directly associated to this object as RDF triples.
105 TRIPLES
21 PREDICATES
37 URIs
19 LITERALS
7 BLANK NODES