{"id":"https://openalex.org/W4417413325","doi":"https://doi.org/10.48550/arxiv.2509.03226","title":"BAMG: A Block-Aware Monotonic Graph Index for Disk-Based Approximate Nearest Neighbor Search","display_name":"BAMG: A Block-Aware Monotonic Graph Index for Disk-Based Approximate Nearest Neighbor Search","publication_year":2025,"publication_date":"2025-09-03","ids":{"openalex":"https://openalex.org/W4417413325","doi":"https://doi.org/10.48550/arxiv.2509.03226"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2509.03226","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2509.03226","pdf_url":"https://arxiv.org/pdf/2509.03226","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2509.03226","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100387055","display_name":"Huiling Li","orcid":"https://orcid.org/0000-0003-3465-4187"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Li, Huiling","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Huang, Xin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Xin","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Choi, Byron","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Choi, Byron","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Xu, Jianliang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Jianliang","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100387055"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.7962999939918518,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11106","display_name":"Data Management and Algorithms","score":0.7962999939918518,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12292","display_name":"Graph Theory and Algorithms","score":0.08030000329017639,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.03530000150203705,"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/graph-traversal","display_name":"Graph traversal","score":0.7781999707221985},{"id":"https://openalex.org/keywords/tree-traversal","display_name":"Tree traversal","score":0.5317000150680542},{"id":"https://openalex.org/keywords/search-engine-indexing","display_name":"Search engine indexing","score":0.5113000273704529},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.46000000834465027},{"id":"https://openalex.org/keywords/monotonic-function","display_name":"Monotonic function","score":0.42010000348091125},{"id":"https://openalex.org/keywords/strength-of-a-graph","display_name":"Strength of a graph","score":0.39010000228881836},{"id":"https://openalex.org/keywords/null-graph","display_name":"Null graph","score":0.3896999955177307},{"id":"https://openalex.org/keywords/graph-bandwidth","display_name":"Graph bandwidth","score":0.37790000438690186},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.373199999332428},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.3695000112056732}],"concepts":[{"id":"https://openalex.org/C96333769","wikidata":"https://www.wikidata.org/wiki/Q907955","display_name":"Graph traversal","level":3,"score":0.7781999707221985},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6103000044822693},{"id":"https://openalex.org/C140745168","wikidata":"https://www.wikidata.org/wiki/Q1210082","display_name":"Tree traversal","level":2,"score":0.5317000150680542},{"id":"https://openalex.org/C75165309","wikidata":"https://www.wikidata.org/wiki/Q2258979","display_name":"Search engine indexing","level":2,"score":0.5113000273704529},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4634999930858612},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.46000000834465027},{"id":"https://openalex.org/C72169020","wikidata":"https://www.wikidata.org/wiki/Q194404","display_name":"Monotonic function","level":2,"score":0.42010000348091125},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.40220001339912415},{"id":"https://openalex.org/C19332903","wikidata":"https://www.wikidata.org/wiki/Q7623247","display_name":"Strength of a graph","level":5,"score":0.39010000228881836},{"id":"https://openalex.org/C17169500","wikidata":"https://www.wikidata.org/wiki/Q3033506","display_name":"Null graph","level":5,"score":0.3896999955177307},{"id":"https://openalex.org/C134727501","wikidata":"https://www.wikidata.org/wiki/Q5597073","display_name":"Graph bandwidth","level":5,"score":0.37790000438690186},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.373199999332428},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.3695000112056732},{"id":"https://openalex.org/C204562854","wikidata":"https://www.wikidata.org/wiki/Q1397646","display_name":"Edge contraction","level":5,"score":0.3472000062465668},{"id":"https://openalex.org/C53052385","wikidata":"https://www.wikidata.org/wiki/Q17104046","display_name":"Mixed graph","level":5,"score":0.3301999866962433},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.3215999901294708},{"id":"https://openalex.org/C162319229","wikidata":"https://www.wikidata.org/wiki/Q175263","display_name":"Data structure","level":2,"score":0.3098999857902527},{"id":"https://openalex.org/C116738811","wikidata":"https://www.wikidata.org/wiki/Q608751","display_name":"Nearest neighbor search","level":2,"score":0.30640000104904175},{"id":"https://openalex.org/C101468663","wikidata":"https://www.wikidata.org/wiki/Q1620158","display_name":"Modular design","level":2,"score":0.2971999943256378},{"id":"https://openalex.org/C125583679","wikidata":"https://www.wikidata.org/wiki/Q755673","display_name":"Search algorithm","level":2,"score":0.29440000653266907},{"id":"https://openalex.org/C82687282","wikidata":"https://www.wikidata.org/wiki/Q66221","display_name":"Auxiliary memory","level":2,"score":0.29260000586509705},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2912999987602234},{"id":"https://openalex.org/C2911174283","wikidata":"https://www.wikidata.org/wiki/Q739462","display_name":"Graph Layout","level":4,"score":0.2904999852180481},{"id":"https://openalex.org/C48903430","wikidata":"https://www.wikidata.org/wiki/Q491370","display_name":"Graph partition","level":3,"score":0.2879999876022339},{"id":"https://openalex.org/C168291704","wikidata":"https://www.wikidata.org/wiki/Q902252","display_name":"Complement graph","level":5,"score":0.2874000072479248},{"id":"https://openalex.org/C90988772","wikidata":"https://www.wikidata.org/wiki/Q2855103","display_name":"Nearest neighbor graph","level":3,"score":0.28610000014305115},{"id":"https://openalex.org/C146380142","wikidata":"https://www.wikidata.org/wiki/Q1137726","display_name":"Directed graph","level":2,"score":0.28459998965263367},{"id":"https://openalex.org/C311688","wikidata":"https://www.wikidata.org/wiki/Q2393193","display_name":"Time complexity","level":2,"score":0.2818000018596649},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.2800000011920929},{"id":"https://openalex.org/C136643341","wikidata":"https://www.wikidata.org/wiki/Q1361526","display_name":"Reachability","level":2,"score":0.2791000008583069},{"id":"https://openalex.org/C831591","wikidata":"https://www.wikidata.org/wiki/Q59750","display_name":"Bidirectional search","level":5,"score":0.2754000127315521},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.2639000117778778},{"id":"https://openalex.org/C5737132","wikidata":"https://www.wikidata.org/wiki/Q1101814","display_name":"Clique-width","level":5,"score":0.26260000467300415},{"id":"https://openalex.org/C76444178","wikidata":"https://www.wikidata.org/wiki/Q72897900","display_name":"Connectivity","level":3,"score":0.2624000012874603},{"id":"https://openalex.org/C148764684","wikidata":"https://www.wikidata.org/wiki/Q621751","display_name":"Approximation algorithm","level":2,"score":0.25999999046325684},{"id":"https://openalex.org/C203776342","wikidata":"https://www.wikidata.org/wiki/Q1378376","display_name":"Line graph","level":3,"score":0.2551000118255615},{"id":"https://openalex.org/C184720557","wikidata":"https://www.wikidata.org/wiki/Q7825049","display_name":"Topology (electrical circuits)","level":2,"score":0.2549999952316284},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.2535000145435333},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.25110000371932983}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2509.03226","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2509.03226","pdf_url":"https://arxiv.org/pdf/2509.03226","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2509.03226","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2509.03226","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2509.03226","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2509.03226","pdf_url":"https://arxiv.org/pdf/2509.03226","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Approximate":[0],"Nearest":[1],"Neighbor":[2],"Search":[3],"(ANNS)":[4],"over":[5],"high-dimensional":[6],"vectors":[7,38,177],"is":[8,106],"a":[9,62,139,157,170,194,206],"foundational":[10],"problem":[11],"in":[12,153,233],"databases,":[13],"where":[14,35],"disk":[15,189,218],"I/O":[16,99,219],"often":[17],"emerges":[18],"as":[19],"the":[20,42,45,58,67,71,87,96,109,113,130,144,161,179],"dominant":[21],"performance":[22],"bottleneck":[23],"at":[24],"scale.":[25],"To":[26,128],"accelerate":[27],"search,":[28],"graph-based":[29],"indexes":[30],"rely":[31],"on":[32,223],"proximity":[33],"graph,":[34],"nodes":[36],"represent":[37],"and":[39,122,141,186,200],"edges":[40],"guide":[41],"traversal":[43,213],"toward":[44],"target.":[46],"However,":[47],"existing":[48],"graph":[49,64,68,110,159,180,197],"indexing":[50],"solutions":[51],"for":[52,61,125,198],"disk-based":[53],"ANNS":[54],"typically":[55],"either":[56],"optimize":[57],"storage":[59,72,123,162,172],"layout":[60,124],"given":[63],"or":[65],"construct":[66],"independently":[69],"of":[70,98,133],"layout,":[73],"thus":[74],"overlooking":[75],"their":[76],"interaction.":[77],"In":[78],"this":[79,83],"paper,":[80],"we":[81,136,192],"bridge":[82],"gap":[84],"by":[85,116],"proposing":[86],"Block-aware":[88],"Monotonic":[89,146],"Relative":[90],"Neighborhood":[91],"Graph":[92,147],"(BMRNG),":[93],"theoretically":[94],"guaranteeing":[95],"existence":[97],"monotonic":[100,158],"search":[101,208,234],"paths.":[102],"The":[103],"core":[104],"idea":[105],"to":[107,214],"align":[108],"topology":[111],"with":[112,169,205],"data":[114],"placement":[115],"jointly":[117],"considering":[118,160],"both":[119],"geometric":[120],"distance":[121],"edge":[126,167],"selection.":[127],"address":[129],"scalability":[131],"challenge":[132],"BMRNG":[134],"construction,":[135],"further":[137],"develop":[138],"practical":[140],"efficient":[142,201],"variant,":[143],"Block-Aware":[145],"(BAMG),":[148],"which":[149],"can":[150,229],"be":[151],"constructed":[152],"linear":[154],"time":[155],"from":[156,178],"layout.":[163],"BAMG":[164,228],"integrates":[165],"block-aware":[166],"pruning":[168],"decoupled":[171],"design":[173,193],"that":[174,210,227],"separates":[175],"raw":[176],"index,":[181],"thereby":[182],"maximizing":[183],"block":[184],"utilization":[185],"minimizing":[187],"redundant":[188],"reads.":[190],"Additionally,":[191],"multi-layer":[195],"navigation":[196],"adaptive":[199],"query":[202],"entry,":[203],"along":[204],"block-first":[207],"algorithm":[209],"prioritizes":[211],"intra-block":[212],"fully":[215],"exploit":[216],"each":[217],"operation.":[220],"Extensive":[221],"experiments":[222],"real-world":[224],"datasets":[225],"show":[226],"outperform":[230],"state-of-the-art":[231],"methods":[232],"performance.":[235]},"counts_by_year":[],"updated_date":"2026-03-25T23:56:10.502304","created_date":"2025-10-10T00:00:00"}
