{"id":"https://openalex.org/W2558969613","doi":"https://doi.org/10.1145/2975167.2985641","title":"Metric-space Positioning Systems (MPS) for Machine Learning","display_name":"Metric-space Positioning Systems (MPS) for Machine Learning","publication_year":2016,"publication_date":"2016-10-02","ids":{"openalex":"https://openalex.org/W2558969613","doi":"https://doi.org/10.1145/2975167.2985641","mag":"2558969613"},"language":"en","primary_location":{"id":"doi:10.1145/2975167.2985641","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2975167.2985641","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 7th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5018306128","display_name":"Richard C. Tillquist","orcid":"https://orcid.org/0000-0002-8032-945X"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Richard C. Tillquist","raw_affiliation_strings":["Department of Computer Science, Engineering Dr, Boulder, Colorado"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Engineering Dr, Boulder, Colorado","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002500363","display_name":"Manuel E. Lladser","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Manuel E. Lladser","raw_affiliation_strings":["Department of Applied Mathematics, UCB Boulder, Colorado"],"affiliations":[{"raw_affiliation_string":"Department of Applied Mathematics, UCB Boulder, Colorado","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5018306128"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.08274725,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":93},"biblio":{"volume":null,"issue":null,"first_page":"479","last_page":"479"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9814000129699707,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9814000129699707,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.9797000288963318,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9211000204086304,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/multilateration","display_name":"Multilateration","score":0.7667919993400574},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.6353817582130432},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6301225423812866},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.6186544299125671},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.6056104302406311},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5673388242721558},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5382084846496582},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5086713433265686},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.4686647653579712},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4557456970214844},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.4497168958187103},{"id":"https://openalex.org/keywords/metric-space","display_name":"Metric space","score":0.424888014793396},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3955288231372833},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32307887077331543},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24872785806655884},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.1049337089061737}],"concepts":[{"id":"https://openalex.org/C104037064","wikidata":"https://www.wikidata.org/wiki/Q1640884","display_name":"Multilateration","level":3,"score":0.7667919993400574},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.6353817582130432},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6301225423812866},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.6186544299125671},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6056104302406311},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5673388242721558},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5382084846496582},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5086713433265686},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.4686647653579712},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4557456970214844},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.4497168958187103},{"id":"https://openalex.org/C198043062","wikidata":"https://www.wikidata.org/wiki/Q180953","display_name":"Metric space","level":2,"score":0.424888014793396},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3955288231372833},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32307887077331543},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24872785806655884},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.1049337089061737},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C159737794","wikidata":"https://www.wikidata.org/wiki/Q124274","display_name":"Azimuth","level":2,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2975167.2985641","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2975167.2985641","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 7th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2380293945","https://openalex.org/W1500522817","https://openalex.org/W1974812937","https://openalex.org/W3095239554","https://openalex.org/W3212409750","https://openalex.org/W1972023576","https://openalex.org/W2072053180","https://openalex.org/W1541088746","https://openalex.org/W2023873321","https://openalex.org/W1983936910"],"abstract_inverted_index":{"Many":[0],"machine":[1,150],"learning":[2,42,151],"techniques":[3,176],"such":[4],"as":[5],"k-nearest":[6],"neighbors":[7],"(KNNs)":[8],"and":[9,107,146,161],"support":[10],"vector":[11],"machines":[12],"(SVMs)":[13],"require":[14,48],"examples":[15,35,87],"to":[16,19,36,115,125],"be":[17],"mapped":[18],"numerical":[20],"feature":[21,81],"vectors.":[22],"Principal":[23],"coordinate":[24],"analysis":[25],"(PCoA)":[26],"accomplishes":[27],"this":[28],"by":[29],"mapping":[30],"a":[31,79,89,99,109],"set":[32,82,102],"of":[33,53,66,78,97,120,149,154,163,173],"n":[34,37],"points":[38],"in":[39,105,142],"Rn-1.":[40],"However,":[41],"from":[43],"these":[44],"high-dimensional":[45],"vectors":[46],"may":[47],"an":[49,58,147],"astronomically":[50],"large":[51],"number":[52],"examples.":[54,135],"Here":[55],"we":[56,122],"present":[57,108],"intuitive,":[59],"novel":[60],"method":[61],"for":[62,112],"uniquely":[63,84],"representing":[64],"sequences":[65],"symbolic":[67,158],"features":[68,140,159],"with":[69],"the":[70,76,95],"fewest":[71],"dimensions":[72],"via":[73],"\"multi-lateration\"":[74],"(i.e.":[75],"selection":[77],"minimal":[80,100],"that":[83,94,169],"distinguishes":[85],"all":[86],"under":[88],"reference":[90],"metric).":[91],"We":[92,136],"show":[93],"problem":[96],"determining":[98],"multilateration":[101,124,170],"is":[103],"NP-complete":[104],"general,":[106],"randomized":[110],"algorithm":[111],"finding":[113],"close":[114],"optimal":[116],"subsets.":[117],"As":[118],"proof":[119],"concept,":[121],"apply":[123],"learn":[126],"12-mers":[127],"centered":[128],"at":[129],"intron-exon":[130],"boundaries":[131],"using":[132,139,181],"human":[133],"annotated":[134],"compare":[137],"results":[138],"derived":[141],"several":[143],"different":[144],"ways":[145],"array":[148],"techniques,":[152],"some":[153,162],"which":[155,164],"can":[156],"handle":[157],"directly":[160],"cannot.":[165],"Our":[166],"experiments":[167],"indicate":[168],"improves":[171],"performance":[172,180],"non-symbolic":[174],"classification":[175],"without":[177],"significantly":[178],"altering":[179],"other":[182],"techniques.":[183]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}