{"id":"https://openalex.org/W1920307396","doi":"https://doi.org/10.17562/pb-47-3","title":"Exploration on Effectiveness and Efficiency of Similar Sentence Matching","display_name":"Exploration on Effectiveness and Efficiency of Similar Sentence Matching","publication_year":2013,"publication_date":"2013-06-30","ids":{"openalex":"https://openalex.org/W1920307396","doi":"https://doi.org/10.17562/pb-47-3","mag":"1920307396"},"language":"en","primary_location":{"id":"doi:10.17562/pb-47-3","is_oa":false,"landing_page_url":"https://doi.org/10.17562/pb-47-3","pdf_url":null,"source":{"id":"https://openalex.org/S4210186437","display_name":"Polibits","issn_l":"1870-9044","issn":["1870-9044","2395-8618"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Polibits","raw_type":"journal-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/A5100749023","display_name":"Yanhui Gu","orcid":"https://orcid.org/0000-0002-8838-3186"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yanhui Gu","raw_affiliation_strings":["University of Tokyo, Meguro, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Tokyo, Meguro, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013188461","display_name":"Zhenglu Yang","orcid":"https://orcid.org/0000-0001-9528-965X"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Zhenglu Yang","raw_affiliation_strings":["University of Tokyo, Meguro, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Tokyo, Meguro, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103572929","display_name":"Miyuki Nakano","orcid":null},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Miyuki Nakano","raw_affiliation_strings":["University of Tokyo, Meguro, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Tokyo, Meguro, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056438865","display_name":"Masaru Kitsuregawa","orcid":"https://orcid.org/0000-0003-4027-2994"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masaru Kitsuregawa","raw_affiliation_strings":["University of Tokyo, Meguro, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Tokyo, Meguro, Japan","institution_ids":["https://openalex.org/I74801974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I74801974"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.05737851,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"47","issue":null,"first_page":"23","last_page":"29"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9994999766349792,"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/T10028","display_name":"Topic Modeling","score":0.9994999766349792,"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/T12016","display_name":"Web Data Mining and Analysis","score":0.9980000257492065,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.996399998664856,"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/sentence","display_name":"Sentence","score":0.5700326561927795},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.55042564868927},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.40263456106185913},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.35675323009490967},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2568261921405792},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.15452444553375244}],"concepts":[{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.5700326561927795},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.55042564868927},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.40263456106185913},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.35675323009490967},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2568261921405792},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.15452444553375244}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.17562/pb-47-3","is_oa":false,"landing_page_url":"https://doi.org/10.17562/pb-47-3","pdf_url":null,"source":{"id":"https://openalex.org/S4210186437","display_name":"Polibits","issn_l":"1870-9044","issn":["1870-9044","2395-8618"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Polibits","raw_type":"journal-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.401.6326","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.401.6326","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://polibits.gelbukh.com/2013_47/Exploration on Effectiveness and Efficiency of Similar Sentence Matching.pdf","raw_type":"text"},{"id":"pmh:oai:redalyc.org:402640461004","is_oa":false,"landing_page_url":"https://www.redalyc.org/articulo.oa?id=402640461004","pdf_url":null,"source":{"id":"https://openalex.org/S4377196100","display_name":"Redalyc (Universidad Aut\u00f3noma del Estado de M\u00e9xico)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I179647637","host_organization_name":"Universidad Aut\u00f3noma del Estado de M\u00e9xico","host_organization_lineage":["https://openalex.org/I179647637"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Polibits (M\u00e9xico) Vol.47","raw_type":"art\u00edculo cient\u00edfico"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W113724690","https://openalex.org/W156841640","https://openalex.org/W183505048","https://openalex.org/W589522266","https://openalex.org/W1566018662","https://openalex.org/W1591155856","https://openalex.org/W1647671624","https://openalex.org/W1983578042","https://openalex.org/W2001496424","https://openalex.org/W2038281398","https://openalex.org/W2045929671","https://openalex.org/W2103296194","https://openalex.org/W2120779048","https://openalex.org/W2121184547","https://openalex.org/W2127675794","https://openalex.org/W2131409447","https://openalex.org/W2134206624","https://openalex.org/W2156124259","https://openalex.org/W2165654401","https://openalex.org/W2253781894","https://openalex.org/W2534712034","https://openalex.org/W2756560861"],"related_works":["https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W2382290278","https://openalex.org/W2350741829","https://openalex.org/W2130043461","https://openalex.org/W2530322880"],"abstract_inverted_index":{"Abstract\u2014Similar":[0],"sentence":[1,62,68,95],"matching":[2],"is":[3,148],"an":[4],"essential":[5],"issue":[6,31],"for":[7],"many":[8],"applications,":[9],"such":[10,37],"as":[11],"text":[12],"summarization,":[13],"image":[14],"extraction,":[15],"social":[16],"media":[17],"retrieval,":[18,159],"question-answer":[19],"model,":[20],"and":[21,58,75,110,146],"so":[22],"on.":[23],"A":[24],"number":[25],"of":[26,36,120,137],"studies":[27],"have":[28],"investigated":[29],"this":[30,52,88],"in":[32,60],"recent":[33],"years.":[34],"Most":[35],"techniques":[38,132],"focus":[39,47],"on":[40,48,100],"effectiveness":[41,57,119,145],"issues":[42],"but":[43],"only":[44],"a":[45,66,84],"few":[46],"efficiency":[49,59,126,147],"issues.":[50],"In":[51],"paper,":[53],"we":[54,70,90,102,128],"address":[55],"both":[56],"the":[61,78,105,118,125,135,138,144],"similarity":[63,96,139],"matching.":[64],"For":[65],"given":[67],"collection,":[69],"determine":[71],"how":[72],"to":[73,83,133],"effectively":[74],"efficiently":[76],"identify":[77],"top-k":[79],"semantically":[80],"similar":[81],"sentences":[82],"query.":[85],"To":[86],"achieve":[87],"goal,":[89],"first":[91],"study":[92],"several":[93,130],"representative":[94],"measurement":[97],"strategies,":[98],"based":[99],"which":[101],"deliberately":[103],"choose":[104],"optimal":[106],"ones":[107],"through":[108],"cross-validation":[109],"dynamically":[111],"weight":[112],"tuning.":[113],"The":[114,141],"experimental":[115],"evaluation":[116],"demonstrates":[117],"our":[121],"strategy.":[122],"Moreover,":[123],"from":[124],"aspect,":[127],"introduce":[129],"optimization":[131],"improve":[134],"performance":[136],"computation.":[140],"trade-off":[142],"between":[143],"further":[149],"explored":[150],"by":[151],"conducting":[152],"extensive":[153],"experiments.":[154],"Index":[155],"Terms\u2014String":[156],"matching,":[157],"information":[158],"natural":[160],"language":[161],"processing.":[162]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}