{"id":"https://openalex.org/W2065110301","doi":"https://doi.org/10.1145/2463676.2463716","title":"Indexing for subtree similarity-search using edit distance","display_name":"Indexing for subtree similarity-search using edit distance","publication_year":2013,"publication_date":"2013-06-22","ids":{"openalex":"https://openalex.org/W2065110301","doi":"https://doi.org/10.1145/2463676.2463716","mag":"2065110301"},"language":"en","primary_location":{"id":"doi:10.1145/2463676.2463716","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2463676.2463716","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data","raw_type":"proceedings-article"},"type":"article","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/A5006348713","display_name":"Sara Cohen","orcid":"https://orcid.org/0000-0002-8482-9435"},"institutions":[{"id":"https://openalex.org/I197251160","display_name":"Hebrew University of Jerusalem","ror":"https://ror.org/03qxff017","country_code":"IL","type":"education","lineage":["https://openalex.org/I197251160"]}],"countries":["IL"],"is_corresponding":true,"raw_author_name":"Sara Cohen","raw_affiliation_strings":["The Hebrew University of Jerusalem, Jerusalem, Israel","The Hebrew University of Jerusalem , Jerusalem , Israel"],"affiliations":[{"raw_affiliation_string":"The Hebrew University of Jerusalem, Jerusalem, Israel","institution_ids":["https://openalex.org/I197251160"]},{"raw_affiliation_string":"The Hebrew University of Jerusalem , Jerusalem , Israel","institution_ids":["https://openalex.org/I197251160"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5006348713"],"corresponding_institution_ids":["https://openalex.org/I197251160"],"apc_list":null,"apc_paid":null,"fwci":7.5233,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":{"value":0.96821426,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"49","last_page":"60"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12016","display_name":"Web Data Mining and Analysis","score":0.9916999936103821,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T12016","display_name":"Web Data Mining and Analysis","score":0.9916999936103821,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10015","display_name":"Genomics and Phylogenetic Studies","score":0.9883000254631042,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10836","display_name":"Metabolomics and Mass Spectrometry Studies","score":0.9869999885559082,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/tree-traversal","display_name":"Tree traversal","score":0.7759581804275513},{"id":"https://openalex.org/keywords/search-engine-indexing","display_name":"Search engine indexing","score":0.7327730059623718},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.724493682384491},{"id":"https://openalex.org/keywords/edit-distance","display_name":"Edit distance","score":0.684084951877594},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.6571938991546631},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6505611538887024},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.595346212387085},{"id":"https://openalex.org/keywords/nearest-neighbor-search","display_name":"Nearest neighbor search","score":0.5749973058700562},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.568047285079956},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5140036940574646},{"id":"https://openalex.org/keywords/index","display_name":"Index (typography)","score":0.4495042562484741},{"id":"https://openalex.org/keywords/metric-space","display_name":"Metric space","score":0.42395684123039246},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3862370252609253},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2871437072753906},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.25804781913757324},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.24522215127944946},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.1951088309288025},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.11756062507629395}],"concepts":[{"id":"https://openalex.org/C140745168","wikidata":"https://www.wikidata.org/wiki/Q1210082","display_name":"Tree traversal","level":2,"score":0.7759581804275513},{"id":"https://openalex.org/C75165309","wikidata":"https://www.wikidata.org/wiki/Q2258979","display_name":"Search engine indexing","level":2,"score":0.7327730059623718},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.724493682384491},{"id":"https://openalex.org/C44359876","wikidata":"https://www.wikidata.org/wiki/Q5338467","display_name":"Edit distance","level":2,"score":0.684084951877594},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.6571938991546631},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6505611538887024},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.595346212387085},{"id":"https://openalex.org/C116738811","wikidata":"https://www.wikidata.org/wiki/Q608751","display_name":"Nearest neighbor search","level":2,"score":0.5749973058700562},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.568047285079956},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5140036940574646},{"id":"https://openalex.org/C2777382242","wikidata":"https://www.wikidata.org/wiki/Q6017816","display_name":"Index (typography)","level":2,"score":0.4495042562484741},{"id":"https://openalex.org/C198043062","wikidata":"https://www.wikidata.org/wiki/Q180953","display_name":"Metric space","level":2,"score":0.42395684123039246},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3862370252609253},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2871437072753906},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.25804781913757324},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.24522215127944946},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.1951088309288025},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.11756062507629395},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2463676.2463716","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2463676.2463716","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322252","display_name":"Israel Science Foundation","ror":"https://ror.org/04sazxf24"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1488987874","https://openalex.org/W1541106661","https://openalex.org/W1543796220","https://openalex.org/W1774857219","https://openalex.org/W1970479141","https://openalex.org/W1973828215","https://openalex.org/W1975009259","https://openalex.org/W1976373002","https://openalex.org/W1978478796","https://openalex.org/W1986037284","https://openalex.org/W1988714735","https://openalex.org/W2003889154","https://openalex.org/W2024936222","https://openalex.org/W2033629528","https://openalex.org/W2048861113","https://openalex.org/W2092057784","https://openalex.org/W2093727387","https://openalex.org/W2097156061","https://openalex.org/W2122092469","https://openalex.org/W2127210827","https://openalex.org/W2129595335","https://openalex.org/W2171643895","https://openalex.org/W2230830246","https://openalex.org/W6988149078"],"related_works":["https://openalex.org/W2487311615","https://openalex.org/W1949910768","https://openalex.org/W1480566255","https://openalex.org/W2387685849","https://openalex.org/W2254397067","https://openalex.org/W2013685631","https://openalex.org/W1610355325","https://openalex.org/W1516985461","https://openalex.org/W1882921205","https://openalex.org/W2129925734"],"abstract_inverted_index":{"Given":[0],"a":[1,5,50,73],"tree":[2,35,42],"Q":[3],"and":[4,103,119],"large":[6],"set":[7],"of":[8,19,23,52,67,69],"trees":[9,24],"T":[10,26,80],"=":[11],"{T1,...,Tn},":[12],"the":[13,21,34,62,86,95,109,115],"subtree":[14,56,91],"similarity-search":[15,57],"problem":[16],"is":[17,99],"that":[18,27,94],"finding":[20],"subtrees":[22],"among":[25],"are":[28],"most":[29],"similar":[30],"to":[31,105],"Q,":[32],"using":[33,41,114],"edit":[36,43],"distance":[37,44],"metric.":[38],"Determining":[39],"similarity":[40],"has":[45,58],"been":[46,59],"proven":[47],"useful":[48],"in":[49,61,76],"variety":[51],"application":[53],"areas.":[54],"While":[55],"studied":[60],"past,":[63],"solutions":[64],"required":[65],"traversal":[66],"all":[68],"T,":[70],"which":[71],"poses":[72],"severe":[74],"bottleneck":[75],"processing":[77,120],"time,":[78],"as":[79],"grows":[81],"larger.":[82],"This":[83],"paper":[84],"proposes":[85],"first":[87],"index":[88,117],"structure":[89,118],"for":[90],"similarity-search,":[92],"provided":[93],"unit":[96],"cost":[97],"function":[98],"used.":[100],"Extensive":[101],"experimentation":[102],"comparison":[104],"previous":[106],"work":[107],"shows":[108],"huge":[110],"improvement":[111],"gained":[112],"when":[113],"proposed":[116],"algorithm.":[121]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
