{"id":"https://openalex.org/W2066369370","doi":"https://doi.org/10.1145/2695664.2695857","title":"Parallel similarity search based on the dimensions value cardinalities of image descriptor vectors","display_name":"Parallel similarity search based on the dimensions value cardinalities of image descriptor vectors","publication_year":2015,"publication_date":"2015-04-13","ids":{"openalex":"https://openalex.org/W2066369370","doi":"https://doi.org/10.1145/2695664.2695857","mag":"2066369370"},"language":"en","primary_location":{"id":"doi:10.1145/2695664.2695857","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2695664.2695857","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th Annual ACM Symposium on Applied Computing","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/A5034151597","display_name":"Dimitrios Rafailidis","orcid":"https://orcid.org/0000-0002-7366-3716"},"institutions":[{"id":"https://openalex.org/I21370196","display_name":"Aristotle University of Thessaloniki","ror":"https://ror.org/02j61yw88","country_code":"GR","type":"education","lineage":["https://openalex.org/I21370196"]}],"countries":["GR"],"is_corresponding":true,"raw_author_name":"Dimitrios Rafailidis","raw_affiliation_strings":["Aristotle University, Thessaloniki, Greece"],"affiliations":[{"raw_affiliation_string":"Aristotle University, Thessaloniki, Greece","institution_ids":["https://openalex.org/I21370196"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010058559","display_name":"Yannis Manolopoulos","orcid":"https://orcid.org/0000-0003-4026-4329"},"institutions":[{"id":"https://openalex.org/I21370196","display_name":"Aristotle University of Thessaloniki","ror":"https://ror.org/02j61yw88","country_code":"GR","type":"education","lineage":["https://openalex.org/I21370196"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Yannis Manolopoulos","raw_affiliation_strings":["Aristotle University, Thessaloniki, Greece"],"affiliations":[{"raw_affiliation_string":"Aristotle University, Thessaloniki, Greece","institution_ids":["https://openalex.org/I21370196"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5034151597"],"corresponding_institution_ids":["https://openalex.org/I21370196"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.07426076,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1023","last_page":"1030"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":1.0,"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"}},{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.996999979019165,"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"}},{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9842000007629395,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.7841368317604065},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.7465344071388245},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7094470858573914},{"id":"https://openalex.org/keywords/nearest-neighbor-search","display_name":"Nearest neighbor search","score":0.645811915397644},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.645533561706543},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5836984515190125},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5317133069038391},{"id":"https://openalex.org/keywords/value","display_name":"Value (mathematics)","score":0.446664422750473},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4248255491256714},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41062241792678833},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.38525721430778503},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.14808565378189087}],"concepts":[{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.7841368317604065},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.7465344071388245},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7094470858573914},{"id":"https://openalex.org/C116738811","wikidata":"https://www.wikidata.org/wiki/Q608751","display_name":"Nearest neighbor search","level":2,"score":0.645811915397644},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.645533561706543},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5836984515190125},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5317133069038391},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.446664422750473},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4248255491256714},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41062241792678833},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.38525721430778503},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.14808565378189087}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/2695664.2695857","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2695664.2695857","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th Annual ACM Symposium on Applied Computing","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.727.4078","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.727.4078","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://delab.csd.auth.gr/papers/SAC2015rm.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7300000190734863,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1502916507","https://openalex.org/W1980090536","https://openalex.org/W1991660789","https://openalex.org/W1997994732","https://openalex.org/W2024562034","https://openalex.org/W2031444464","https://openalex.org/W2041878876","https://openalex.org/W2074594363","https://openalex.org/W2086504823","https://openalex.org/W2151103935","https://openalex.org/W2171572695","https://openalex.org/W2221852422","https://openalex.org/W4299828299"],"related_works":["https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2761785940","https://openalex.org/W1482209366","https://openalex.org/W2110523656","https://openalex.org/W2521627374","https://openalex.org/W2353456014"],"abstract_inverted_index":{"In":[0,90],"this":[1],"paper,":[2],"we":[3,104,126],"propose":[4],"a":[5],"parallel":[6,55,112],"similarity":[7,113],"search":[8,114,121],"strategy":[9,24],"based":[10],"on":[11],"the":[12,31,35,43,62,70,85,107],"dimensions":[13,47,63,75,86],"value":[14,48,78],"cardinalities,":[15],"an":[16,53],"inherit":[17],"characteristic":[18],"of":[19,34,64,76,87,97,118],"image":[20,65],"descriptor":[21],"vectors.":[22],"Our":[23],"has":[25],"low":[26,88],"preprocessing":[27,36,119],"requirements":[28],"by":[29],"dividing":[30],"computational":[32],"cost":[33],"steps":[37],"into":[38],"several":[39],"machines":[40],"and":[41,100,123],"locating":[42],"descriptors":[44,66],"with":[45,93],"similar":[46],"cardinalities":[49,79],"logically":[50],"close.":[51],"Additionally,":[52],"efficient":[54],"query":[56],"processing":[57],"algorithm":[58],"is":[59],"proposed,":[60],"where":[61],"are":[67],"prioritized":[68],"in":[69,116],"searching":[71],"strategy,":[72],"assuming":[73],"that":[74,106],"high":[77],"have":[80],"more":[81],"discriminative":[82],"power":[83],"than":[84],"ones.":[89],"our":[91,128],"experiments":[92],"publicly":[94,131],"available":[95],"datasets":[96],"80":[98],"million":[99],"1":[101],"billion":[102],"images,":[103],"show":[105],"proposed":[108],"method":[109],"outperforms":[110],"state-of-the-art":[111],"strategies,":[115],"terms":[117],"cost,":[120],"time":[122],"accuracy.":[124],"Finally,":[125],"made":[127],"source":[129],"code":[130],"available.":[132]},"counts_by_year":[],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
