{"id":"https://openalex.org/W3030153168","doi":"https://doi.org/10.1145/3374135.3385266","title":"A Fast Filtering Algorithm for Massive Context-free Grammars","display_name":"A Fast Filtering Algorithm for Massive Context-free Grammars","publication_year":2020,"publication_date":"2020-04-02","ids":{"openalex":"https://openalex.org/W3030153168","doi":"https://doi.org/10.1145/3374135.3385266","mag":"3030153168"},"language":"en","primary_location":{"id":"doi:10.1145/3374135.3385266","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3374135.3385266","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3374135.3385266","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 ACM Southeast Conference","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3374135.3385266","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5074721846","display_name":"Jeremy Dohmann","orcid":null},"institutions":[{"id":"https://openalex.org/I4210106258","display_name":"Harvard College Observatory","ror":"https://ror.org/01mcvy510","country_code":"US","type":"facility","lineage":["https://openalex.org/I103187081","https://openalex.org/I136199984","https://openalex.org/I4210106258","https://openalex.org/I4210124175"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jeremy Dohmann","raw_affiliation_strings":["Harvard College, Cambridge, MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harvard College, Cambridge, MA, USA","institution_ids":["https://openalex.org/I4210106258"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044944791","display_name":"Kyle Deeds","orcid":"https://orcid.org/0000-0003-2267-3276"},"institutions":[{"id":"https://openalex.org/I4210106258","display_name":"Harvard College Observatory","ror":"https://ror.org/01mcvy510","country_code":"US","type":"facility","lineage":["https://openalex.org/I103187081","https://openalex.org/I136199984","https://openalex.org/I4210106258","https://openalex.org/I4210124175"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kyle Deeds","raw_affiliation_strings":["Harvard College, Cambridge, MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harvard College, Cambridge, MA, USA","institution_ids":["https://openalex.org/I4210106258"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5074721846"],"corresponding_institution_ids":["https://openalex.org/I4210106258"],"apc_list":null,"apc_paid":null,"fwci":0.136,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.54129444,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"62","last_page":"70"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9998999834060669,"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/T10028","display_name":"Topic Modeling","score":0.9980999827384949,"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/T12031","display_name":"Speech and dialogue systems","score":0.9902999997138977,"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/computer-science","display_name":"Computer science","score":0.8652788400650024},{"id":"https://openalex.org/keywords/parsing","display_name":"Parsing","score":0.7821521759033203},{"id":"https://openalex.org/keywords/context-free-grammar","display_name":"Context-free grammar","score":0.5728128552436829},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5727603435516357},{"id":"https://openalex.org/keywords/rule-based-machine-translation","display_name":"Rule-based machine translation","score":0.5340491533279419},{"id":"https://openalex.org/keywords/parsing-expression-grammar","display_name":"Parsing expression grammar","score":0.5114620923995972},{"id":"https://openalex.org/keywords/grammar","display_name":"Grammar","score":0.49571382999420166},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46290409564971924},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.4592665433883667},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.43678414821624756},{"id":"https://openalex.org/keywords/l-attributed-grammar","display_name":"L-attributed grammar","score":0.34586265683174133},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3307533860206604},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.13177692890167236}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8652788400650024},{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.7821521759033203},{"id":"https://openalex.org/C97212296","wikidata":"https://www.wikidata.org/wiki/Q338047","display_name":"Context-free grammar","level":3,"score":0.5728128552436829},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5727603435516357},{"id":"https://openalex.org/C53893814","wikidata":"https://www.wikidata.org/wiki/Q7378909","display_name":"Rule-based machine translation","level":2,"score":0.5340491533279419},{"id":"https://openalex.org/C146810361","wikidata":"https://www.wikidata.org/wiki/Q32271","display_name":"Parsing expression grammar","level":5,"score":0.5114620923995972},{"id":"https://openalex.org/C26022165","wikidata":"https://www.wikidata.org/wiki/Q8091","display_name":"Grammar","level":2,"score":0.49571382999420166},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46290409564971924},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.4592665433883667},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.43678414821624756},{"id":"https://openalex.org/C67621940","wikidata":"https://www.wikidata.org/wiki/Q3113340","display_name":"L-attributed grammar","level":4,"score":0.34586265683174133},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3307533860206604},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.13177692890167236},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3374135.3385266","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3374135.3385266","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3374135.3385266","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 ACM Southeast Conference","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3374135.3385266","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3374135.3385266","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3374135.3385266","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 ACM Southeast Conference","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.7900000214576721,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G4713059963","display_name":null,"funder_award_id":"FA8750","funder_id":"https://openalex.org/F4320332180","funder_display_name":"Defense Advanced Research Projects Agency"}],"funders":[{"id":"https://openalex.org/F4320332180","display_name":"Defense Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3030153168.pdf","grobid_xml":"https://content.openalex.org/works/W3030153168.grobid-xml"},"referenced_works_count":27,"referenced_works":["https://openalex.org/W1482538754","https://openalex.org/W1965215112","https://openalex.org/W1975613061","https://openalex.org/W1998235220","https://openalex.org/W2004758563","https://openalex.org/W2006599089","https://openalex.org/W2019413183","https://openalex.org/W2023206235","https://openalex.org/W2040713190","https://openalex.org/W2055869448","https://openalex.org/W2077186307","https://openalex.org/W2124479173","https://openalex.org/W2156796546","https://openalex.org/W2164548001","https://openalex.org/W2165876984","https://openalex.org/W2183366530","https://openalex.org/W2528833921","https://openalex.org/W2608787653","https://openalex.org/W2614322402","https://openalex.org/W2622101508","https://openalex.org/W2950518979","https://openalex.org/W3030153168","https://openalex.org/W3099023595","https://openalex.org/W4235611032","https://openalex.org/W4236682217","https://openalex.org/W4285719527","https://openalex.org/W4400064739"],"related_works":["https://openalex.org/W2153803459","https://openalex.org/W1557335907","https://openalex.org/W4286266684","https://openalex.org/W1963896666","https://openalex.org/W2055334547","https://openalex.org/W3202319462","https://openalex.org/W152266133","https://openalex.org/W2086184235","https://openalex.org/W2073788202","https://openalex.org/W3013382169"],"abstract_inverted_index":{"All":[0],"non-statistical":[1],"context-free":[2,46,77],"parsers":[3,47],"are":[4,203],"plagued":[5],"by":[6,48],"a":[7,50,88,111,137,142,147,219],"worst":[8],"case":[9],"parse":[10],"time,":[11],"O(|G|xn3),":[12],"linear":[13],"in":[14,22,96,126],"the":[15,18,42,54,70,92,100,108,204,210,244,252],"size":[16,123,153],"of":[17,45,53,72,91,104,139,152,243],"grammar,":[19],"|G|,":[20],"which":[21,98,115,202,222,225],"many":[23],"applications":[24],"can":[25,232],"cause":[26],"major":[27],"slowdowns":[28],"[6].":[29],"In":[30],"this":[31,127,194],"paper,":[32],"we":[33,83,160],"pursue":[34],"general":[35],"purpose":[36],"pre-processing":[37],"intended":[38],"to":[39,57,65,183,209,251],"speed":[40],"up":[41],"run":[43,119,214],"time":[44,120],"selecting":[49],"smaller":[51],"fragment":[52],"grammar":[55,105,122,151],"prior":[56],"parsing.":[58],"Our":[59,130],"work":[60,131],"provides":[61],"an":[62,81],"ad-hoc":[63],"method":[64],"perform":[66],"subgrammar":[67],"selection,":[68],"increasing":[69],"practicality":[71],"parsing":[73,165,186],"with":[74],"very":[75,195],"large":[76],"grammars.":[78],"We":[79,216],"present":[80],"algorithm":[82,94,179],"call":[84],"'Terminal-tree":[85],"filtering'":[86],"(TTF),":[87],"new":[89,117],"variant":[90],"'b-filtering'":[93],"presented":[95],"[6],":[97],"finds":[99],"same":[101,196],"filtered":[102],"set":[103],"rules":[106],"as":[107],"'b-filter'":[109],"for":[110],"given":[112],"input,":[113],"but":[114],"achieves":[116],"state-of-the-art":[118],"and":[121,229,235],"performance":[124,134],"within":[125],"problem":[128],"space.":[129],"boasts":[132],"remarkable":[133],"boosts":[135],"across":[136],"range":[138],"workloads,":[140],"including":[141],"10-20":[143],"fold":[144],"speedup":[145],"on":[146,188],"real":[148],"world":[149],"English":[150,191],"|G|":[154],"\u2248":[155,169],"115,":[156],"000,":[157],"000.":[158],"Furthermore,":[159],"achieve":[161],"far":[162],"greater":[163],"scale,":[164],"sentences":[166],"using":[167],"grammars":[168],"10":[170],"times":[171,187],"larger":[172],"than":[173],"those":[174],"previously":[175],"studied.":[176],"The":[177],"TTF":[178,245],"filters":[180],"quickly":[181],"enough":[182],"provide":[184,218],"feasible":[185],"our":[189],"example":[190],"grammar.":[192],"On":[193],"test":[197],"suite":[198],"[6]":[199],"'s":[200],"algorithms,":[201],"broadest,":[205],"most":[206],"recent":[207],"contributions":[208],"field,":[211],"demonstrate":[212],"unacceptable":[213],"times.":[215],"also":[217],"theoretical":[220],"analysis":[221],"elucidates":[223],"under":[224,239],"conditions":[226],"worst-case":[227,240],"behavior":[228,231],"best-case":[230],"be":[233],"expected,":[234],"show":[236,247],"that":[237],"even":[238],"performance,":[241],"variants":[242],"still":[246],"some":[248],"empirical":[249],"advantages":[250],"b-filter.":[253]},"counts_by_year":[{"year":2020,"cited_by_count":1}],"updated_date":"2026-05-04T08:30:34.212998","created_date":"2025-10-10T00:00:00"}