{"id":"https://openalex.org/W1604214119","doi":"https://doi.org/10.1109/itw.2006.1633788","title":"Compressing with Collapsible Tries","display_name":"Compressing with Collapsible Tries","publication_year":2006,"publication_date":"2006-05-25","ids":{"openalex":"https://openalex.org/W1604214119","doi":"https://doi.org/10.1109/itw.2006.1633788","mag":"1604214119"},"language":"en","primary_location":{"id":"doi:10.1109/itw.2006.1633788","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itw.2006.1633788","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2006 IEEE Information Theory Workshop","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/A5029039590","display_name":"Alberto Apostolico","orcid":null},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]},{"id":"https://openalex.org/I138689650","display_name":"University of Padua","ror":"https://ror.org/00240q980","country_code":"IT","type":"education","lineage":["https://openalex.org/I138689650"]}],"countries":["IT","US"],"is_corresponding":true,"raw_author_name":"A. Apostolico","raw_affiliation_strings":["DEI, Universit\u00e0 di Padova, Padova, Italy","IIC, College of Computing, Georgia Institute of Technology, Atlanta, GA, USA"],"affiliations":[{"raw_affiliation_string":"DEI, Universit\u00e0 di Padova, Padova, Italy","institution_ids":["https://openalex.org/I138689650"]},{"raw_affiliation_string":"IIC, College of Computing, Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023771318","display_name":"Yongwook Choi","orcid":"https://orcid.org/0000-0003-4017-9669"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yong Wook Choi","raw_affiliation_strings":["Department of Computer Sciences, Purdue University, West Lafayette, IN, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Sciences, Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5029039590"],"corresponding_institution_ids":["https://openalex.org/I130701444","https://openalex.org/I138689650"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0603282,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"92","last_page":"96"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11269","display_name":"Algorithms and Data Compression","score":0.9998000264167786,"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/T11269","display_name":"Algorithms and Data Compression","score":0.9998000264167786,"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/T11697","display_name":"Numerical Methods and Algorithms","score":0.989300012588501,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.9830999970436096,"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/lossy-compression","display_name":"Lossy compression","score":0.7801215052604675},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7349137663841248},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6216968297958374},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5859665274620056},{"id":"https://openalex.org/keywords/iterated-function","display_name":"Iterated function","score":0.5462926030158997},{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.5315135717391968},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5260260701179504},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5208030939102173},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.5012972354888916},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.4492173194885254},{"id":"https://openalex.org/keywords/parsing","display_name":"Parsing","score":0.42099729180336},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.40080687403678894},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.3686354160308838},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2160777747631073},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1632871925830841}],"concepts":[{"id":"https://openalex.org/C165021410","wikidata":"https://www.wikidata.org/wiki/Q55564","display_name":"Lossy compression","level":2,"score":0.7801215052604675},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7349137663841248},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6216968297958374},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5859665274620056},{"id":"https://openalex.org/C140479938","wikidata":"https://www.wikidata.org/wiki/Q5254619","display_name":"Iterated function","level":2,"score":0.5462926030158997},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.5315135717391968},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5260260701179504},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5208030939102173},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.5012972354888916},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.4492173194885254},{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.42099729180336},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.40080687403678894},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.3686354160308838},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2160777747631073},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1632871925830841},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C194257627","wikidata":"https://www.wikidata.org/wiki/Q211554","display_name":"Amplifier","level":3,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","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/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/itw.2006.1633788","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itw.2006.1633788","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2006 IEEE Information Theory Workshop","raw_type":"proceedings-article"},{"id":"pmh:oai:www.research.unipd.it:11577/1557539","is_oa":false,"landing_page_url":"http://hdl.handle.net/11577/1557539","pdf_url":null,"source":{"id":"https://openalex.org/S4377196283","display_name":"Research Padua  Archive (University of Padua)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I138689650","host_organization_name":"University of Padua","host_organization_lineage":["https://openalex.org/I138689650"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1508845689","https://openalex.org/W1547966682","https://openalex.org/W1570353109","https://openalex.org/W1897100168","https://openalex.org/W1990653637","https://openalex.org/W2070475775","https://openalex.org/W2077770566","https://openalex.org/W2093011562","https://openalex.org/W2099111195","https://openalex.org/W2107745473","https://openalex.org/W2109985619","https://openalex.org/W2122962290","https://openalex.org/W2151219842","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2547124190","https://openalex.org/W2385628723","https://openalex.org/W2888954728","https://openalex.org/W2552401318","https://openalex.org/W108076602","https://openalex.org/W3180760233","https://openalex.org/W4384342390","https://openalex.org/W3035703949","https://openalex.org/W4247601675","https://openalex.org/W1033938421"],"abstract_inverted_index":{"Lossy":[0],"variants":[1],"of":[2,6,23,49,84,100,111,122,131],"the":[3,12,24,38,55,61,69,101,106,112,117,146,149],"Ziv-Lempel":[4],"family":[5],"encoders":[7],"are":[8,27,92,152],"built":[9],"traditionally":[10],"around":[11],"iterated":[13],"quest":[14],"for":[15,76],"best":[16],"matches":[17],"within":[18],"an":[19],"assigned":[20],"fidelity.":[21],"Most":[22],"resulting":[25],"algorithms":[26],"inherently":[28],"superlinear":[29],"and":[30,35,95,120,129,134],"not":[31,153],"easy":[32],"to":[33,115],"implement":[34],"analyze.":[36],"On":[37],"other":[39],"hand,":[40],"it":[41,58],"is":[42,114,141],"well":[43],"known":[44],"that":[45,57,77,148],"any":[46],"lossy":[47],"scheme":[48],"low":[50,86],"computational":[51],"complexity":[52],"must":[53],"have":[54],"drawback":[56],"cannot":[59],"yield":[60],"minimal":[62],"distortion":[63],"which":[64,90,140],"can":[65],"be":[66],"achieved":[67],"by":[68,98,105,145],"optimal":[70],"data":[71],"compression":[72],"algorithm":[73,119],"specifically":[74],"tailored":[75],"case.":[78],"This":[79],"paper":[80,113],"concentrates":[81],"on":[82],"parses":[83],"guaranteed":[85],"time":[87],"performance,":[88],"in":[89],"phrases":[91],"all":[93],"distinct":[94],"generated":[96],"mechanically":[97],"self-correlations":[99],"source":[102],"set":[103],"forth":[104],"parsing":[107],"process.":[108],"The":[109],"goal":[110],"describe":[116],"basic":[118],"some":[121],"its":[123],"variants,":[124],"show":[125],"their":[126],"good":[127],"performance":[128],"latitude":[130],"practical":[132],"applicability,":[133],"possibly":[135],"stimulate":[136],"in-depth":[137],"analytical":[138],"treatment,":[139],"made":[142],"particularly":[143],"hard":[144],"fact":[147],"underlying":[150],"processes":[151],"stationary.":[154]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
