乐胖代购免代理版

{"id":"https://openalex.org/W2054634810","doi":"https://doi.org/10.1145/1386352.1386375","title":"Clip based video summarization and ranking","display_name":"Clip based video summarization and ranking","publication_year":2008,"publication_date":"2008-07-07","ids":{"openalex":"https://openalex.org/W2054634810","doi":"https://doi.org/10.1145/1386352.1386375","mag":"2054634810"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1145/1386352.1386375","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-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/A5100602494","display_name":"Yue Gao","orcid":"https://orcid.org/0000-0002-4971-590X"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"funder","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yue Gao","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080722708","display_name":"Qionghai Dai","orcid":"https://orcid.org/0000-0001-7043-3061"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"funder","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiong-Hai Dai","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.212,"has_fulltext":true,"fulltext_origin":"ngrams","cited_by_count":19,"citation_normalized_percentile":{"value":0.757968,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":87,"max":88},"biblio":{"volume":"315","issue":null,"first_page":"135","last_page":"140"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T11439","display_name":"Video Analysis and Summarization","score":0.9999,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11439","display_name":"Video Analysis and Summarization","score":0.9999,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11309","display_name":"Music and Audio Processing","score":0.9974,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9895,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/clips","display_name":"CLIPS","score":0.6871027},{"id":"https://openalex.org/keywords/similarity-measure","display_name":"Similarity measure","score":0.5939244},{"id":"https://openalex.org/keywords/affinity-propagation","display_name":"Affinity propagation","score":0.525891},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.48510993}],"concepts":[{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.8006879},{"id":"https://openalex.org/C197657726","wikidata":"https://www.wikidata.org/wiki/Q174733","display_name":"Bipartite graph","level":3,"score":0.7456233},{"id":"https://openalex.org/C2778739407","wikidata":"https://www.wikidata.org/wiki/Q165372","display_name":"CLIPS","level":2,"score":0.6871027},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6613447},{"id":"https://openalex.org/C2776517306","wikidata":"https://www.wikidata.org/wiki/Q29017317","display_name":"Similarity measure","level":2,"score":0.5939244},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5688474},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.56438196},{"id":"https://openalex.org/C109659709","wikidata":"https://www.wikidata.org/wiki/Q3407504","display_name":"Affinity propagation","level":5,"score":0.525891},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.49533525},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.48510993},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42279625},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41513455},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.37071562},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.27044845},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1688093},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.13470742},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.13009265},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10637459},{"id":"https://openalex.org/C104047586","wikidata":"https://www.wikidata.org/wiki/Q5033439","display_name":"Canopy clustering algorithm","level":4,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1145/1386352.1386375","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":22,"referenced_works":["https://openalex.org/W1604419323","https://openalex.org/W1978977266","https://openalex.org/W1983388991","https://openalex.org/W2045029957","https://openalex.org/W2047196850","https://openalex.org/W2095380808","https://openalex.org/W2110963300","https://openalex.org/W2114456882","https://openalex.org/W2116955522","https://openalex.org/W2119586176","https://openalex.org/W2123807687","https://openalex.org/W2136625207","https://openalex.org/W2138738320","https://openalex.org/W2144577430","https://openalex.org/W2145196253","https://openalex.org/W2149723790","https://openalex.org/W2156044652","https://openalex.org/W2158207955","https://openalex.org/W2165232124","https://openalex.org/W2171947771","https://openalex.org/W2222512263","https://openalex.org/W2296428857"],"related_works":["https://openalex.org/W4389760904","https://openalex.org/W4242223894","https://openalex.org/W3148229873","https://openalex.org/W2417253731","https://openalex.org/W2366403280","https://openalex.org/W2350469024","https://openalex.org/W2150160875","https://openalex.org/W2112028398","https://openalex.org/W2091301346","https://openalex.org/W1495108544"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"present":[4],"a":[5,19,34,48,53,67],"new":[6],"algorithm":[7,39],"for":[8,40],"video":[9,22,134],"clip":[10,20,41,117],"summarization":[11],"and":[12,25,52,83,144],"ranking,":[13],"which":[14],"is":[15,92,138],"mainly":[16],"based":[17,21,139],"on":[18,140],"similarity":[23,42,97],"measure":[24,95],"the":[26,72,79,84,88,96,108,132,141,145,158],"affinity":[27,123],"propagation":[28],"clustering":[29],"(AP)":[30],"algorithm.":[31,160],"We":[32],"propose":[33],"proportional":[35],"max-weighted":[36,89],"bipartite":[37,69,90],"matching":[38,91],"measure.":[43],"This":[44,101],"method":[45,102],"first":[46],"generates":[47],"basic":[49],"frame":[50,81],"set":[51,57],"corresponding":[54],"proportion":[55,85],"value":[56],"from":[58],"each":[59,150],"clip.":[60],"Then":[61,87],"it":[62],"models":[63],"two":[64,99,111],"clips":[65,112,119,126],"as":[66],"weighted":[68],"graph,":[70],"where":[71],"weight":[73],"values":[74],"are":[75,120,154],"determined":[76],"by":[77],"both":[78],"direct":[80],"similarities":[82],"values.":[86],"employed":[93],"to":[94,156],"between":[98],"clips.":[100],"achieves":[103],"good":[104],"retrieval":[105],"performance":[106],"when":[107],"length":[109],"of":[110,149],"varies":[113],"greatly.":[114],"With":[115],"these":[116],"similarities,":[118],"clustered":[121],"using":[122],"propagation.":[124],"The":[125],"in":[127],"one":[128],"cluster":[129,142],"generally":[130],"describe":[131],"same":[133],"event.":[135,151],"Video":[136],"ranking":[137],"size":[143],"average":[146],"information":[147],"entropy":[148],"Experimental":[152],"results":[153],"given":[155],"illustrate":[157],"proposed":[159]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W2054634810","counts_by_year":[{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":2},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":2}],"updated_date":"2025-03-23T12:20:27.914990","created_date":"2016-06-24"}