{"id":"https://openalex.org/W2579798231","doi":"https://doi.org/10.1201/b19567-14","title":"High-Dimensional Computational Geometry","display_name":"High-Dimensional Computational Geometry","publication_year":2016,"publication_date":"2016-02-22","ids":{"openalex":"https://openalex.org/W2579798231","doi":"https://doi.org/10.1201/b19567-14","mag":"2579798231"},"language":"en","primary_location":{"id":"doi:10.1201/b19567-14","is_oa":false,"landing_page_url":"https://doi.org/10.1201/b19567-14","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Handbook of Big Data","raw_type":"book-chapter"},"type":"book-chapter","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/A5088346829","display_name":"Alexandr Andoni","orcid":"https://orcid.org/0009-0004-8042-0976"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Alexandr Andoni","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5088346829"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.14886656,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"121","last_page":"140"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10996","display_name":"Computational Geometry and Mesh Generation","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9962999820709229,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/geometry","display_name":"Geometry","score":0.6122704744338989},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.376869261264801},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21467921137809753}],"concepts":[{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.6122704744338989},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.376869261264801},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21467921137809753}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1201/b19567-14","is_oa":false,"landing_page_url":"https://doi.org/10.1201/b19567-14","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Handbook of Big Data","raw_type":"book-chapter"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W19838944","https://openalex.org/W1539682630","https://openalex.org/W1598302191","https://openalex.org/W1606712848","https://openalex.org/W1653844607","https://openalex.org/W1957963525","https://openalex.org/W1964775192","https://openalex.org/W1970630090","https://openalex.org/W1980155175","https://openalex.org/W1983172570","https://openalex.org/W1983415430","https://openalex.org/W2009813398","https://openalex.org/W2013451793","https://openalex.org/W2014036420","https://openalex.org/W2018925011","https://openalex.org/W2026244324","https://openalex.org/W2032083353","https://openalex.org/W2038521541","https://openalex.org/W2050516752","https://openalex.org/W2053913299","https://openalex.org/W2066717841","https://openalex.org/W2073966617","https://openalex.org/W2075328466","https://openalex.org/W2083706862","https://openalex.org/W2102942501","https://openalex.org/W2109330224","https://openalex.org/W2112551191","https://openalex.org/W2115458940","https://openalex.org/W2116953739","https://openalex.org/W2126000837","https://openalex.org/W2128087748","https://openalex.org/W2132467825","https://openalex.org/W2133311553","https://openalex.org/W2138134196","https://openalex.org/W2140566134","https://openalex.org/W2146382457","https://openalex.org/W2296292655","https://openalex.org/W2401610261","https://openalex.org/W2913586686","https://openalex.org/W2914539165","https://openalex.org/W2949466244","https://openalex.org/W2952208743","https://openalex.org/W2952664231","https://openalex.org/W3004537778"],"related_works":["https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W2382290278","https://openalex.org/W2350741829","https://openalex.org/W2130043461","https://openalex.org/W2530322880"],"abstract_inverted_index":{"Consider":[0],"the":[1,26,35,71,74],"following":[2],"common":[3],"similarity":[4],"search":[5],"scenario.":[6],"We":[7],"are":[8],"given":[9],"a":[10,45,54,60],"new":[11],"image,":[12],"and":[13],"we":[14,33,51,68],"need":[15],"to":[16,22,43],"determine":[17],"whether":[18],"it":[19],"is":[20,42],"similar":[21],"some":[23],"image":[24,58],"in":[25,77],"existing":[27],"database,":[28],"preprocessed":[29],"beforehand.":[30],"How":[31],"do":[32],"capture":[34],"notion":[36],"of":[37],"similar?":[38],"The":[39],"standard":[40],"approach":[41],"use":[44],"suitable":[46],"distance":[47,76],"metric.":[48],"For":[49],"example,":[50],"can":[52,69],"represent":[53],"20":[55],"\u00d7":[56],"20-pixel":[57],"as":[59],"400dimensional":[61],"vector,":[62],"one":[63],"coordinate":[64],"per":[65],"pixel.":[66],"Then":[67],"measure":[70],"(dis)similarity":[72],"using":[73],"Euclidean":[75],"R400.":[78]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2017-01-26T00:00:00"}