{"id":"https://openalex.org/W7133335452","doi":"https://doi.org/10.48550/arxiv.2603.01525","title":"VectorMaton: Efficient Vector Search with Pattern Constraints via an Enhanced Suffix Automaton","display_name":"VectorMaton: Efficient Vector Search with Pattern Constraints via an Enhanced Suffix Automaton","publication_year":2026,"publication_date":"2026-03-02","ids":{"openalex":"https://openalex.org/W7133335452","doi":"https://doi.org/10.48550/arxiv.2603.01525"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.01525","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.01525","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.01525","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5069573030","display_name":"Haoxuan Xie","orcid":"https://orcid.org/0009-0006-9642-428X"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Xie, Haoxuan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Luo, Siqiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Luo, Siqiang","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5069573030"],"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.2777000069618225,"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":0.2777000069618225,"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":0.2401999980211258,"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/T11106","display_name":"Data Management and Algorithms","score":0.15600000321865082,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/nearest-neighbor-search","display_name":"Nearest neighbor search","score":0.5716999769210815},{"id":"https://openalex.org/keywords/substring","display_name":"Substring","score":0.5593000054359436},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5271999835968018},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.4837999939918518},{"id":"https://openalex.org/keywords/pattern-matching","display_name":"Pattern matching","score":0.4392000138759613},{"id":"https://openalex.org/keywords/categorical-variable","display_name":"Categorical variable","score":0.4253999888896942},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.42489999532699585},{"id":"https://openalex.org/keywords/bit-array","display_name":"Bit array","score":0.40389999747276306},{"id":"https://openalex.org/keywords/string","display_name":"String (physics)","score":0.3707999885082245},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.3628000020980835}],"concepts":[{"id":"https://openalex.org/C116738811","wikidata":"https://www.wikidata.org/wiki/Q608751","display_name":"Nearest neighbor search","level":2,"score":0.5716999769210815},{"id":"https://openalex.org/C182407805","wikidata":"https://www.wikidata.org/wiki/Q2626534","display_name":"Substring","level":3,"score":0.5593000054359436},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5536999702453613},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5271999835968018},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.4837999939918518},{"id":"https://openalex.org/C68859911","wikidata":"https://www.wikidata.org/wiki/Q1503724","display_name":"Pattern matching","level":2,"score":0.4392000138759613},{"id":"https://openalex.org/C5274069","wikidata":"https://www.wikidata.org/wiki/Q2285707","display_name":"Categorical variable","level":2,"score":0.4253999888896942},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.42489999532699585},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4174000024795532},{"id":"https://openalex.org/C150807984","wikidata":"https://www.wikidata.org/wiki/Q1992074","display_name":"Bit array","level":3,"score":0.40389999747276306},{"id":"https://openalex.org/C157486923","wikidata":"https://www.wikidata.org/wiki/Q1376436","display_name":"String (physics)","level":2,"score":0.3707999885082245},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.3628000020980835},{"id":"https://openalex.org/C42058472","wikidata":"https://www.wikidata.org/wiki/Q810214","display_name":"Base (topology)","level":2,"score":0.36149999499320984},{"id":"https://openalex.org/C143271835","wikidata":"https://www.wikidata.org/wiki/Q254515","display_name":"Similitude","level":2,"score":0.3587999939918518},{"id":"https://openalex.org/C130590232","wikidata":"https://www.wikidata.org/wiki/Q1671754","display_name":"Inverted index","level":3,"score":0.35010001063346863},{"id":"https://openalex.org/C125583679","wikidata":"https://www.wikidata.org/wiki/Q755673","display_name":"Search algorithm","level":2,"score":0.34540000557899475},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3416999876499176},{"id":"https://openalex.org/C75165309","wikidata":"https://www.wikidata.org/wiki/Q2258979","display_name":"Search engine indexing","level":2,"score":0.3273000121116638},{"id":"https://openalex.org/C7757238","wikidata":"https://www.wikidata.org/wiki/Q374040","display_name":"String searching algorithm","level":3,"score":0.32690000534057617},{"id":"https://openalex.org/C5655090","wikidata":"https://www.wikidata.org/wiki/Q192588","display_name":"Relational database","level":2,"score":0.3264000117778778},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.31949999928474426},{"id":"https://openalex.org/C157692150","wikidata":"https://www.wikidata.org/wiki/Q2919848","display_name":"Query optimization","level":2,"score":0.3167000114917755},{"id":"https://openalex.org/C99016210","wikidata":"https://www.wikidata.org/wiki/Q5488129","display_name":"Query expansion","level":2,"score":0.3082999885082245},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3052999973297119},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.3034000098705292},{"id":"https://openalex.org/C177292542","wikidata":"https://www.wikidata.org/wiki/Q440959","display_name":"Vector map","level":2,"score":0.3003000020980835},{"id":"https://openalex.org/C2777382242","wikidata":"https://www.wikidata.org/wiki/Q6017816","display_name":"Index (typography)","level":2,"score":0.2976999878883362},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.2937000095844269},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.29339998960494995},{"id":"https://openalex.org/C59276292","wikidata":"https://www.wikidata.org/wiki/Q580427","display_name":"Database index","level":3,"score":0.2930999994277954},{"id":"https://openalex.org/C192028432","wikidata":"https://www.wikidata.org/wiki/Q845739","display_name":"Query language","level":2,"score":0.2922999858856201},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.2793999910354614},{"id":"https://openalex.org/C2779804580","wikidata":"https://www.wikidata.org/wiki/Q102047","display_name":"Suffix","level":2,"score":0.27869999408721924},{"id":"https://openalex.org/C162319229","wikidata":"https://www.wikidata.org/wiki/Q175263","display_name":"Data structure","level":2,"score":0.27730000019073486},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.27320000529289246},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2712000012397766},{"id":"https://openalex.org/C120098539","wikidata":"https://www.wikidata.org/wiki/Q141001","display_name":"Longest common subsequence problem","level":2,"score":0.26989999413490295},{"id":"https://openalex.org/C110484373","wikidata":"https://www.wikidata.org/wiki/Q264398","display_name":"Adjacency list","level":2,"score":0.2651999890804291},{"id":"https://openalex.org/C44359876","wikidata":"https://www.wikidata.org/wiki/Q5338467","display_name":"Edit distance","level":2,"score":0.25850000977516174},{"id":"https://openalex.org/C41584329","wikidata":"https://www.wikidata.org/wiki/Q175902","display_name":"Sequence database","level":3,"score":0.2578999996185303}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.01525","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.01525","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.01525","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.01525","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Approximate":[0],"nearest":[1,145],"neighbor":[2],"search":[3,51,122],"(ANNS)":[4],"has":[5],"become":[6],"a":[7,15,24,130,134,141,150],"cornerstone":[8],"in":[9,210],"modern":[10],"vector":[11,50,101,120,170],"database":[12],"systems.":[13],"Given":[14],"query":[16,106,152,199],"vector,":[17],"ANNS":[18],"retrieves":[19],"the":[20,46,144,179,202],"closest":[21],"vectors":[22,32,137,146],"from":[23],"set":[25,135],"of":[26,136],"base":[27],"vectors.":[28],"In":[29,81,125],"real-world":[30,185],"applications,":[31],"are":[33,90],"often":[34],"accompanied":[35],"by":[36],"additional":[37],"information,":[38],"such":[39,85],"as":[40,86],"sequences":[41,148],"or":[42,63],"structured":[43],"attributes,":[44,70],"motivating":[45],"need":[47],"for":[48,93],"fine-grained":[49],"with":[52,140,168],"constraints":[53],"on":[54,66,97,184],"this":[55,126,156],"auxiliary":[56],"data.":[57],"Existing":[58],"methods":[59],"support":[60,75],"attribute-based":[61],"filtering":[62,65,94,167],"range-based":[64],"categorical":[67],"and":[68,88,116,205],"numerical":[69],"but":[71],"they":[72],"do":[73],"not":[74],"pattern":[76,109,166],"predicates":[77,84,110],"over":[78,111],"sequence":[79,112],"attributes.":[80],"relational":[82],"databases,":[83],"LIKE":[87],"CONTAINS":[89],"fundamental":[91],"operators":[92],"records":[95],"based":[96],"substring":[98],"patterns.":[99],"As":[100],"databases":[102],"increasingly":[103],"adopt":[104],"SQL-style":[105],"interfaces,":[107],"enabling":[108],"attributes":[113],"(e.g.,":[114],"texts":[115],"biological":[117],"sequences)":[118],"alongside":[119],"similarity":[121],"becomes":[123],"essential.":[124],"paper,":[127],"we":[128,158],"formulate":[129],"novel":[131],"problem:":[132],"given":[133,151],"each":[138],"associated":[139],"sequence,":[142],"retrieve":[143],"whose":[147],"contain":[149],"pattern.":[153],"To":[154],"address":[155],"challenge,":[157],"propose":[159],"VectorMaton,":[160],"an":[161,174],"automaton-based":[162],"index":[163,175,211],"that":[164,188],"integrates":[165],"efficient":[169],"search,":[171],"while":[172],"maintaining":[173],"size":[176],"comparable":[177],"to":[178,196,207],"dataset":[180],"size.":[181,212],"Extensive":[182],"experiments":[183],"datasets":[186],"demonstrate":[187],"VectorMaton":[189],"consistently":[190],"outperforms":[191],"all":[192],"baselines,":[193],"achieving":[194],"up":[195,206],"10x":[197],"higher":[198],"throughput":[200],"at":[201],"same":[203],"accuracy":[204],"18x":[208],"reduction":[209]},"counts_by_year":[],"updated_date":"2026-03-25T23:56:10.502304","created_date":"2026-03-04T00:00:00"}