{"id":"https://openalex.org/W2902334880","doi":"https://doi.org/10.1109/icmew.2018.8551530","title":"Compact Web Video Summarization Via Supervised Learning","display_name":"Compact Web Video Summarization Via Supervised Learning","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2902334880","doi":"https://doi.org/10.1109/icmew.2018.8551530","mag":"2902334880"},"language":"en","primary_location":{"id":"doi:10.1109/icmew.2018.8551530","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmew.2018.8551530","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Multimedia & Expo Workshops (ICMEW)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5101398880","display_name":"Yang Wang","orcid":"https://orcid.org/0000-0001-9447-1791"},"institutions":[{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yang Wang","raw_affiliation_strings":["Microsoft AI & Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft AI & Research","institution_ids":["https://openalex.org/I4210164937"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101936635","display_name":"Bo Han","orcid":"https://orcid.org/0000-0001-6282-5428"},"institutions":[{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Bo Han","raw_affiliation_strings":["Microsoft AI & Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft AI & Research","institution_ids":["https://openalex.org/I4210164937"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068283932","display_name":"Darui Li","orcid":null},"institutions":[{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Darui Li","raw_affiliation_strings":["Microsoft AI & Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft AI & Research","institution_ids":["https://openalex.org/I4210164937"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109226002","display_name":"Kit Thambiratnam","orcid":null},"institutions":[{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Kit Thambiratnam","raw_affiliation_strings":["Microsoft AI & Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft AI & Research","institution_ids":["https://openalex.org/I4210164937"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210164937"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"19","issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11439","display_name":"Video Analysis and Summarization","score":1.0,"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":1.0,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9988999962806702,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9969000220298767,"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/thumbnail","display_name":"Thumbnail","score":0.9698303937911987},{"id":"https://openalex.org/keywords/automatic-summarization","display_name":"Automatic summarization","score":0.8965781927108765},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8572922945022583},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.6133068799972534},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.550815224647522},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.5145451426506042},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.4961641728878021},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.4641498327255249},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43058058619499207},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3978150486946106},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32237932085990906},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.22900977730751038}],"concepts":[{"id":"https://openalex.org/C160174412","wikidata":"https://www.wikidata.org/wiki/Q873806","display_name":"Thumbnail","level":3,"score":0.9698303937911987},{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.8965781927108765},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8572922945022583},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6133068799972534},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.550815224647522},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.5145451426506042},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4961641728878021},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.4641498327255249},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43058058619499207},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3978150486946106},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32237932085990906},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.22900977730751038},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icmew.2018.8551530","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmew.2018.8551530","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Multimedia & Expo Workshops (ICMEW)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.7599999904632568}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1904325426","https://openalex.org/W1924343884","https://openalex.org/W1958932515","https://openalex.org/W1990089425","https://openalex.org/W2094998392","https://openalex.org/W2103908291","https://openalex.org/W2115857089","https://openalex.org/W2120645068","https://openalex.org/W2131081720","https://openalex.org/W2139009685","https://openalex.org/W2144933361","https://openalex.org/W2150471402","https://openalex.org/W2161969291","https://openalex.org/W2163605009","https://openalex.org/W2515770085","https://openalex.org/W2963220254","https://openalex.org/W6640109428","https://openalex.org/W6677302653","https://openalex.org/W6681106510","https://openalex.org/W6681240974","https://openalex.org/W6684191040","https://openalex.org/W6726453277"],"related_works":["https://openalex.org/W2011506639","https://openalex.org/W137154299","https://openalex.org/W2095080241","https://openalex.org/W2501702011","https://openalex.org/W2908847257","https://openalex.org/W2512435841","https://openalex.org/W4298160414","https://openalex.org/W402673672","https://openalex.org/W3046127589","https://openalex.org/W4287704324"],"abstract_inverted_index":{"Ever":[0],"growing":[1],"consumption":[2],"of":[3,42,93],"online":[4],"videos":[5],"from":[6],"search,":[7],"recommendation,":[8],"and":[9,28],"sharing":[10],"has":[11],"generated":[12],"a":[13,39,100,114],"strong":[14],"demand":[15],"on":[16,99],"compact":[17,40],"summarization,":[18],"to":[19,22,50,84],"allow":[20],"users":[21],"quickly":[23],"understand":[24],"the":[25,30,51,55,75,82,87,106,110],"video":[26,102],"content":[27],"make":[29],"whether-to-watch":[31],"decision.":[32],"This":[33],"paper":[34],"explores":[35],"achieving":[36],"this":[37,71],"using":[38],"set":[41,95],"four":[43],"thumbnails,":[44],"via":[45],"supervised":[46],"learning":[47],"methods.":[48],"Due":[49],"ubiquitous":[52],"disagreements":[53],"among":[54],"thumbnail":[56,94],"sets":[57],"preferred":[58],"by":[59,113],"different":[60],"labelers,":[61],"there":[62],"exists":[63],"no":[64],"unique":[65],"ground":[66],"truth":[67],"set.":[68],"To":[69],"address":[70],"problem,":[72],"we":[73],"propose":[74],"pair":[76,92],"wise":[77],"ranking":[78],"method,":[79],"which":[80],"trains":[81],"model":[83],"best":[85],"predict":[86],"user":[88],"preference":[89],"over":[90],"each":[91],"candidates.":[96],"Experimental":[97],"results":[98],"large":[101,115],"dataset":[103],"showed":[104],"that":[105],"proposed":[107],"method":[108],"outperforms":[109],"existing":[111],"schemes":[112],"margin.":[116]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}