{"id":"https://openalex.org/W7163516320","doi":"https://doi.org/10.48550/arxiv.2606.04610","title":"Selectivity Estimation for Semantic Filters on Image Data","display_name":"Selectivity Estimation for Semantic Filters on Image Data","publication_year":2026,"publication_date":"2026-06-03","ids":{"openalex":"https://openalex.org/W7163516320","doi":"https://doi.org/10.48550/arxiv.2606.04610"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.04610","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.04610","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.04610","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137850623","display_name":"Matthias Urban","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Urban, Matthias","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137870878","display_name":"V\u0169 Qu\u1ed1c Huy Nguy\u1ec5n","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nguyen, Vu Huy","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125184899","display_name":"Gabriele Sanmartino","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sanmartino, Gabriele","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137914438","display_name":"Paolo Papotti","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Papotti, Paolo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137817602","display_name":"Carsten Binnig","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Binnig, Carsten","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.4163999855518341,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.4163999855518341,"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":0.0723000019788742,"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/T10215","display_name":"Semantic Web and Ontologies","score":0.05810000002384186,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.613099992275238},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.46399998664855957},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.44179999828338623},{"id":"https://openalex.org/keywords/semantic-data-model","display_name":"Semantic data model","score":0.41839998960494995},{"id":"https://openalex.org/keywords/semantic-computing","display_name":"Semantic computing","score":0.39809998869895935},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.39250001311302185},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3813000023365021},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.3797000050544739},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.36809998750686646}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8258000016212463},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.613099992275238},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.46399998664855957},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.44179999828338623},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.42640000581741333},{"id":"https://openalex.org/C90312973","wikidata":"https://www.wikidata.org/wiki/Q7449052","display_name":"Semantic data model","level":2,"score":0.41839998960494995},{"id":"https://openalex.org/C511149849","wikidata":"https://www.wikidata.org/wiki/Q7449051","display_name":"Semantic computing","level":3,"score":0.39809998869895935},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.39250001311302185},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3813000023365021},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.3797000050544739},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.36809998750686646},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.367000013589859},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36629998683929443},{"id":"https://openalex.org/C2778493491","wikidata":"https://www.wikidata.org/wiki/Q7449072","display_name":"Semantic matching","level":3,"score":0.35679998993873596},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.334199994802475},{"id":"https://openalex.org/C157692150","wikidata":"https://www.wikidata.org/wiki/Q2919848","display_name":"Query optimization","level":2,"score":0.33340001106262207},{"id":"https://openalex.org/C2129575","wikidata":"https://www.wikidata.org/wiki/Q54837","display_name":"Semantic Web","level":2,"score":0.3264999985694885},{"id":"https://openalex.org/C2775955345","wikidata":"https://www.wikidata.org/wiki/Q7449071","display_name":"Semantic mapping","level":2,"score":0.3244999945163727},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.3172000050544739},{"id":"https://openalex.org/C103692084","wikidata":"https://www.wikidata.org/wiki/Q1765824","display_name":"Semantic grid","level":3,"score":0.3043999969959259},{"id":"https://openalex.org/C202708506","wikidata":"https://www.wikidata.org/wiki/Q7449050","display_name":"Semantic compression","level":5,"score":0.3018999993801117},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2919999957084656},{"id":"https://openalex.org/C17020691","wikidata":"https://www.wikidata.org/wiki/Q139677","display_name":"Operator (biology)","level":5,"score":0.2872999906539917},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.2809999883174896},{"id":"https://openalex.org/C136736807","wikidata":"https://www.wikidata.org/wiki/Q818943","display_name":"Range query (database)","level":5,"score":0.26489999890327454},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2572999894618988},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2567000091075897},{"id":"https://openalex.org/C93518851","wikidata":"https://www.wikidata.org/wiki/Q180160","display_name":"Metadata","level":2,"score":0.25290000438690186},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.2508000135421753}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.04610","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.04610","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.04610","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.04610","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"Preprint"},"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":{"Semantic":[0,63,149],"data":[1,74],"systems":[2,40],"integrate":[3],"Large":[4],"Language":[5],"Models":[6,10],"(LLMs)":[7],"and":[8,53,160],"Vision-Language":[9],"(VLMs)":[11],"directly":[12],"into":[13],"database":[14],"query":[15,158],"execution,":[16],"enabling":[17],"expressive":[18],"queries":[19,26],"on":[20,42,72],"multi-modal":[21],"data.":[22],"However,":[23],"optimizing":[24],"these":[25],"requires":[27],"accurate":[28],"selectivity":[29,67],"estimates":[30],"to":[31,80,132,164],"determine":[32],"the":[33,123,134,141,153],"most":[34],"efficient":[35],"operator":[36],"execution":[37,161],"order.":[38],"Contemporary":[39],"rely":[41],"online":[43],"sample-based":[44],"profiling,":[45],"a":[46,65,97,109,118],"process":[47],"that":[48,75,86,148],"incurs":[49],"severe":[50],"latency":[51],"overheads":[52],"struggles":[54],"with":[55,137],"low-selectivity":[56],"queries.":[57],"In":[58],"this":[59],"paper,":[60],"we":[61,128],"introduce":[62],"Histograms,":[64],"novel":[66],"estimator":[68],"for":[69],"semantic":[70,88],"filters":[71,89],"image":[73],"leverages":[76],"shared":[77],"embedding":[78],"spaces":[79],"bypass":[81],"traditional":[82],"profiling.":[83],"We":[84],"realize":[85],"all":[87],"are":[90,105,114],"implicit":[91,126],"range":[92,98],"queries,":[93],"as":[94],"they":[95],"match":[96],"of":[99,125,140,157],"different":[100],"images.":[101],"Some":[102],"filter":[103],"predicates":[104],"more":[106,115],"general,":[107],"yielding":[108,117],"wide":[110],"range,":[111],"while":[112],"others":[113],"specific,":[116],"smaller":[119],"range.":[120],"To":[121],"address":[122],"challenge":[124],"ranges,":[127],"propose":[129],"two":[130,142],"approaches":[131],"estimate":[133],"queries'":[135],"specificity,":[136],"an":[138],"ensemble":[139],"performing":[143],"best.":[144],"The":[145],"evaluation":[146],"shows":[147],"Histograms":[150],"can":[151],"reduce":[152],"end-to-end":[154],"runtime":[155],"overhead":[156],"optimization":[159],"by":[162],"up":[163],"86%.":[165]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-05T00:00:00"}