{"id":"https://openalex.org/W2189396012","doi":"https://doi.org/10.1109/wocc.2015.7346205","title":"A novel feature selection method for nearest neighbor search in binary embedding codes","display_name":"A novel feature selection method for nearest neighbor search in binary embedding codes","publication_year":2015,"publication_date":"2015-10-01","ids":{"openalex":"https://openalex.org/W2189396012","doi":"https://doi.org/10.1109/wocc.2015.7346205","mag":"2189396012"},"language":"en","primary_location":{"id":"doi:10.1109/wocc.2015.7346205","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wocc.2015.7346205","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 24th Wireless and Optical Communication Conference (WOCC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5004144189","display_name":"Chih\u2010Yi Chiu","orcid":"https://orcid.org/0000-0002-2859-6120"},"institutions":[{"id":"https://openalex.org/I183570559","display_name":"National Chiayi University","ror":"https://ror.org/04gknbs13","country_code":"TW","type":"education","lineage":["https://openalex.org/I183570559"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chih-Yi Chiu","raw_affiliation_strings":["Department of Computer Science, National Chiayi University, Chiayi City, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, National Chiayi University, Chiayi City, Taiwan","institution_ids":["https://openalex.org/I183570559"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068764331","display_name":"Yu-Cyuan Liou","orcid":null},"institutions":[{"id":"https://openalex.org/I183570559","display_name":"National Chiayi University","ror":"https://ror.org/04gknbs13","country_code":"TW","type":"education","lineage":["https://openalex.org/I183570559"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Yu-Cyuan Liou","raw_affiliation_strings":["Department of Computer Science, National Chiayi University, Chiayi City, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, National Chiayi University, Chiayi City, Taiwan","institution_ids":["https://openalex.org/I183570559"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I183570559"],"apc_list":null,"apc_paid":null,"fwci":0.1352,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.43715959,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"201","last_page":"205"},"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":0.9995999932289124,"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":0.9995999932289124,"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/T11269","display_name":"Algorithms and Data Compression","score":0.9775999784469604,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9641000032424927,"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/computer-science","display_name":"Computer science","score":0.6776044368743896},{"id":"https://openalex.org/keywords/search-engine-indexing","display_name":"Search engine indexing","score":0.619232714176178},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.614853024482727},{"id":"https://openalex.org/keywords/nearest-neighbor-search","display_name":"Nearest neighbor search","score":0.5176423192024231},{"id":"https://openalex.org/keywords/binary-code","display_name":"Binary code","score":0.5038551688194275},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.5025067329406738},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4970102608203888},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.49088984727859497},{"id":"https://openalex.org/keywords/hash-function","display_name":"Hash function","score":0.48865631222724915},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.4466087818145752},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.44258803129196167},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.426146924495697},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.39844438433647156},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2941015362739563},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2519044280052185}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6776044368743896},{"id":"https://openalex.org/C75165309","wikidata":"https://www.wikidata.org/wiki/Q2258979","display_name":"Search engine indexing","level":2,"score":0.619232714176178},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.614853024482727},{"id":"https://openalex.org/C116738811","wikidata":"https://www.wikidata.org/wiki/Q608751","display_name":"Nearest neighbor search","level":2,"score":0.5176423192024231},{"id":"https://openalex.org/C63435697","wikidata":"https://www.wikidata.org/wiki/Q864135","display_name":"Binary code","level":3,"score":0.5038551688194275},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.5025067329406738},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4970102608203888},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.49088984727859497},{"id":"https://openalex.org/C99138194","wikidata":"https://www.wikidata.org/wiki/Q183427","display_name":"Hash function","level":2,"score":0.48865631222724915},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.4466087818145752},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.44258803129196167},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.426146924495697},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.39844438433647156},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2941015362739563},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2519044280052185},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"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/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wocc.2015.7346205","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wocc.2015.7346205","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 24th Wireless and Optical Communication Conference (WOCC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W89155778","https://openalex.org/W189214596","https://openalex.org/W305053096","https://openalex.org/W2016273390","https://openalex.org/W2029205712","https://openalex.org/W2034865485","https://openalex.org/W2041878876","https://openalex.org/W2057644096","https://openalex.org/W2124509324","https://openalex.org/W2128873747","https://openalex.org/W2132234208","https://openalex.org/W2251864938","https://openalex.org/W6603628041","https://openalex.org/W6607669822","https://openalex.org/W6679081597","https://openalex.org/W6691474080"],"related_works":["https://openalex.org/W2148008870","https://openalex.org/W2381195555","https://openalex.org/W2368606575","https://openalex.org/W4246757943","https://openalex.org/W1949910768","https://openalex.org/W2085998272","https://openalex.org/W2132753198","https://openalex.org/W2369874856","https://openalex.org/W2182477562","https://openalex.org/W2792185758"],"abstract_inverted_index":{"We":[0],"address":[1],"the":[2,50,96,100,116,120,127],"issue":[3,70],"of":[4],"search":[5],"nearest":[6],"neighbors":[7],"in":[8],"binary":[9,58,97],"embedding":[10],"codes":[11],"by":[12],"asymmetric":[13,17,40,73],"distance":[14,18,28,41,74],"computation.":[15,42,75],"Although":[16],"computation":[19],"can":[20,38,91,104],"obtain":[21],"a":[22,63,68,81,108],"more":[23,46],"accurate":[24],"result":[25],"than":[26],"symmetric":[27],"computation,":[29],"its":[30],"speed":[31],"is":[32,67],"much":[33],"slower.":[34],"Applying":[35],"multi-index":[36],"hashing":[37],"accelerate":[39],"However,":[43],"it":[44],"takes":[45],"memory":[47,65],"to":[48,55,71,123],"store":[49],"index":[51,89],"tables.":[52],"Thus,":[53],"how":[54],"select":[56],"appropriate":[57],"features":[59,98],"for":[60,110],"indexing":[61],"under":[62],"certain":[64],"constraint":[66],"key":[69],"improve":[72],"In":[76],"this":[77],"paper,":[78],"we":[79],"propose":[80],"novel":[82],"feature":[83,133],"selection":[84,134],"method.":[85],"When":[86],"only":[87],"partial":[88],"tables":[90],"be":[92,105],"loaded":[93],"into":[94],"memory,":[95],"with":[99],"lowest":[101],"quantization":[102],"error":[103],"selected":[106],"as":[107],"representative":[109],"indexing.":[111],"Experimental":[112],"results":[113],"show":[114],"that":[115],"proposed":[117],"method":[118],"improves":[119],"accuracy":[121],"up":[122],"8.35%":[124],"and":[125,131],"outperforms":[126],"linear":[128],"scan":[129],"approach":[130],"other":[132],"methods.":[135]},"counts_by_year":[{"year":2016,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}