{"id":"https://openalex.org/W2077236746","doi":"https://doi.org/10.1145/2452376.2452421","title":"Selectivity estimation for hybrid queries over text-rich data graphs","display_name":"Selectivity estimation for hybrid queries over text-rich data graphs","publication_year":2013,"publication_date":"2013-03-18","ids":{"openalex":"https://openalex.org/W2077236746","doi":"https://doi.org/10.1145/2452376.2452421","mag":"2077236746"},"language":"en","primary_location":{"id":"doi:10.1145/2452376.2452421","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2452376.2452421","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 16th International Conference on Extending Database Technology","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/A5046291935","display_name":"Andreas Wagner","orcid":"https://orcid.org/0000-0003-4015-236X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Andreas Wagner","raw_affiliation_strings":["AIFB, KIT Karlsruhe, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AIFB, KIT Karlsruhe, Germany","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066386874","display_name":"Veli Bi\u00e7er","orcid":null},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Veli Bicer","raw_affiliation_strings":["IBM Research, Smarter Cities Technology Centre Dublin, Ireland","IBM Research, Smarter Cities Technology Centre Dublin, Ireland#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research, Smarter Cities Technology Centre Dublin, Ireland","institution_ids":[]},{"raw_affiliation_string":"IBM Research, Smarter Cities Technology Centre Dublin, Ireland#TAB#","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5106665005","display_name":"Thanh D. Tran","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Thanh D. Tran","raw_affiliation_strings":["AIFB, KIT Karlsruhe, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AIFB, KIT Karlsruhe, Germany","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.9386,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.74763774,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"383","last_page":"394"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9993000030517578,"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":0.9993000030517578,"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/T10317","display_name":"Advanced Database Systems and Queries","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T11719","display_name":"Data Quality and Management","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.819381833076477},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.7583958506584167},{"id":"https://openalex.org/keywords/string","display_name":"String (physics)","score":0.6883730888366699},{"id":"https://openalex.org/keywords/semi-structured-data","display_name":"Semi-structured data","score":0.5506250858306885},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.50799161195755},{"id":"https://openalex.org/keywords/string-searching-algorithm","display_name":"String searching algorithm","score":0.4868621230125427},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4250416159629822},{"id":"https://openalex.org/keywords/pattern-matching","display_name":"Pattern matching","score":0.4108017683029175},{"id":"https://openalex.org/keywords/relational-database","display_name":"Relational database","score":0.3712632656097412},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36973702907562256},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2906237244606018},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08915179967880249}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.819381833076477},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.7583958506584167},{"id":"https://openalex.org/C157486923","wikidata":"https://www.wikidata.org/wiki/Q1376436","display_name":"String (physics)","level":2,"score":0.6883730888366699},{"id":"https://openalex.org/C40077939","wikidata":"https://www.wikidata.org/wiki/Q2336004","display_name":"Semi-structured data","level":3,"score":0.5506250858306885},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.50799161195755},{"id":"https://openalex.org/C7757238","wikidata":"https://www.wikidata.org/wiki/Q374040","display_name":"String searching algorithm","level":3,"score":0.4868621230125427},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4250416159629822},{"id":"https://openalex.org/C68859911","wikidata":"https://www.wikidata.org/wiki/Q1503724","display_name":"Pattern matching","level":2,"score":0.4108017683029175},{"id":"https://openalex.org/C5655090","wikidata":"https://www.wikidata.org/wiki/Q192588","display_name":"Relational database","level":2,"score":0.3712632656097412},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36973702907562256},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2906237244606018},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08915179967880249},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/2452376.2452421","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2452376.2452421","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 16th International Conference on Extending Database Technology","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.308.9461","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.308.9461","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.edbt.org/Proceedings/2013-Genova/papers/edbt/a35-wagner.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2408841099","display_name":null,"funder_award_id":"01ME12013","funder_id":"https://openalex.org/F4320321469","funder_display_name":"Bundesministerium f\u00fcr Wirtschaft und Technologie"}],"funders":[{"id":"https://openalex.org/F4320321469","display_name":"Bundesministerium f\u00fcr Wirtschaft und Technologie","ror":"https://ror.org/02vgg2808"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W29172951","https://openalex.org/W1501299699","https://openalex.org/W1578664299","https://openalex.org/W1585529040","https://openalex.org/W1800493452","https://openalex.org/W1860880244","https://openalex.org/W1984248370","https://openalex.org/W1992735711","https://openalex.org/W2020584928","https://openalex.org/W2021850646","https://openalex.org/W2062304368","https://openalex.org/W2077236746","https://openalex.org/W2097880962","https://openalex.org/W2100913274","https://openalex.org/W2103013841","https://openalex.org/W2108475322","https://openalex.org/W2112056262","https://openalex.org/W2117461391","https://openalex.org/W2126185296","https://openalex.org/W2140613126","https://openalex.org/W2143124645","https://openalex.org/W2144416276","https://openalex.org/W2147440220","https://openalex.org/W2163166770","https://openalex.org/W2167439683","https://openalex.org/W2168865746","https://openalex.org/W2171903035","https://openalex.org/W2396635388","https://openalex.org/W2803316390","https://openalex.org/W4241185933","https://openalex.org/W4246006899","https://openalex.org/W4285719527","https://openalex.org/W6601147126","https://openalex.org/W6751661959"],"related_works":["https://openalex.org/W3145288231","https://openalex.org/W2163934370","https://openalex.org/W2371263218","https://openalex.org/W4398785990","https://openalex.org/W2092552144","https://openalex.org/W2354196777","https://openalex.org/W2257399947","https://openalex.org/W2965473297","https://openalex.org/W2386746909","https://openalex.org/W2108265183"],"abstract_inverted_index":{"Many":[0],"databases":[1,15],"today":[2],"are":[3,76],"text-rich,":[4],"comprising":[5],"not":[6],"only":[7],"structured,":[8],"but":[9],"also":[10],"textual":[11,26,154],"data.":[12,98],"Querying":[13],"such":[14,47],"involves":[16],"predicates":[17,24,65,75,137],"matching":[18],"structured":[19,63,105,134,152],"data":[20,106,155],"combined":[21],"with":[22],"string":[23,60,136],"featuring":[25],"constraints.":[27],"Based":[28],"on":[29,54,59,62,78,143],"selectivity":[30,55,93,120,164],"estimates":[31,165],"for":[32,95,125],"these":[33],"predicates,":[34],"query":[35,64],"processing":[36],"as":[37,39],"well":[38],"other":[40],"tasks":[41],"that":[42,148],"can":[43,49,122],"be":[44,50,112,123],"solved":[45],"through":[46],"queries":[48,126],"optimized.":[51],"Existing":[52],"work":[53],"estimation":[56,94],"focuses":[57],"either":[58],"or":[61],"alone.":[66],"Further,":[67],"probabilistic":[68,89,100,117],"models":[69],"proposed":[70],"to":[71,111],"incorporate":[72],"dependencies":[73,103,150],"between":[74,104,151],"focused":[77],"the":[79,161,168],"relational":[80],"setting.":[81],"In":[82,140],"this":[83,115,157],"work,":[84],"we":[85,146],"propose":[86],"a":[87],"template-based":[88],"model,":[90],"which":[91,131],"enables":[92],"general":[96,116],"graph-structured":[97,129],"Our":[99],"model":[101],"allows":[102],"and":[107,135,153],"its":[108],"text-rich":[109,128],"parts":[110],"captured.":[113],"With":[114],"solution,":[118],"BN+,":[119],"estimations":[121],"obtained":[124],"over":[127],"data,":[130,145],"may":[132],"contain":[133],"(hybrid":[138],"queries).":[139],"our":[141],"experiments":[142],"real-world":[144],"show":[147],"capturing":[149],"in":[156],"way":[158],"greatly":[159],"improves":[160],"accuracy":[162],"of":[163],"without":[166],"compromising":[167],"efficiency.":[169]},"counts_by_year":[{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":3}],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2025-10-10T00:00:00"}
