{"id":"https://openalex.org/W1963700693","doi":"https://doi.org/10.1145/2009916.2010074","title":"Graph-cut based tag enrichment","display_name":"Graph-cut based tag enrichment","publication_year":2011,"publication_date":"2011-07-24","ids":{"openalex":"https://openalex.org/W1963700693","doi":"https://doi.org/10.1145/2009916.2010074","mag":"1963700693"},"language":"en","primary_location":{"id":"doi:10.1145/2009916.2010074","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2009916.2010074","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval","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/A5014825654","display_name":"Xueming Qian","orcid":"https://orcid.org/0000-0002-3173-6307"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Xueming Qian","raw_affiliation_strings":["School of Information and Communication Engineering, Xi'an, SD, China"],"affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, Xi'an, SD, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024965898","display_name":"Xian\u2010Sheng Hua","orcid":"https://orcid.org/0000-0002-8232-5049"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xian-Sheng Hua","raw_affiliation_strings":["Microsoft Research Asia, Beijing, RI, USA","Microsoft Research Asia, Beijing, RI, USA#TAB#"],"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia, Beijing, RI, USA","institution_ids":["https://openalex.org/I1290206253"]},{"raw_affiliation_string":"Microsoft Research Asia, Beijing, RI, USA#TAB#","institution_ids":["https://openalex.org/I1290206253"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5014825654"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.0303,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.78362721,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1111","last_page":"1112"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9994000196456909,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9994000196456909,"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":0.9983999729156494,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9807999730110168,"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/graph","display_name":"Graph","score":0.6750489473342896},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6680094599723816},{"id":"https://openalex.org/keywords/cut","display_name":"Cut","score":0.57658851146698},{"id":"https://openalex.org/keywords/maximum-flow-problem","display_name":"Maximum flow problem","score":0.4425412118434906},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3167755603790283},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.28559350967407227},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.25492721796035767},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2215016484260559},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.18656468391418457},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.184919536113739}],"concepts":[{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6750489473342896},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6680094599723816},{"id":"https://openalex.org/C5134670","wikidata":"https://www.wikidata.org/wiki/Q1626444","display_name":"Cut","level":4,"score":0.57658851146698},{"id":"https://openalex.org/C157469704","wikidata":"https://www.wikidata.org/wiki/Q2585642","display_name":"Maximum flow problem","level":2,"score":0.4425412118434906},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3167755603790283},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.28559350967407227},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.25492721796035767},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2215016484260559},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.18656468391418457},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.184919536113739}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2009916.2010074","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2009916.2010074","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320333993","display_name":"Microsoft Research Asia","ror":"https://ror.org/0300m5276"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":4,"referenced_works":["https://openalex.org/W2113137767","https://openalex.org/W2156344194","https://openalex.org/W2161258050","https://openalex.org/W2913081710"],"related_works":["https://openalex.org/W2144748970","https://openalex.org/W2052826996","https://openalex.org/W2377700283","https://openalex.org/W76454513","https://openalex.org/W2120804060","https://openalex.org/W2126789858","https://openalex.org/W2766968478","https://openalex.org/W2557991469","https://openalex.org/W2186701437","https://openalex.org/W2392188817"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"a":[3,14],"graph":[4,15,24,32],"cut":[5],"based":[6,62],"tag":[7,63],"enrichment":[8,64],"approach":[9],"is":[10,25,41],"proposed.":[11],"We":[12],"build":[13],"for":[16,48],"each":[17,37],"image":[18],"with":[19,26,36],"its":[20],"initial":[21],"tags.":[22],"The":[23],"two":[27],"terminals.":[28],"Nodes":[29],"of":[30,58],"the":[31,45,49,56,59],"are":[33],"full":[34],"connected":[35],"other.":[38],"Min-cut/max-flow":[39],"algorithm":[40],"utilized":[42],"to":[43],"find":[44],"relevant":[46],"tags":[47],"image.":[50],"Experiments":[51],"on":[52],"Flickr":[53],"dataset":[54],"demonstrate":[55],"effectiveness":[57],"proposed":[60],"graph-cut":[61],"approach.":[65]},"counts_by_year":[{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}