{"id":"https://openalex.org/W1959228470","doi":"https://doi.org/10.1109/cvpr.2015.7299167","title":"Sense discovery via co-clustering on images and text","display_name":"Sense discovery via co-clustering on images and text","publication_year":2015,"publication_date":"2015-06-01","ids":{"openalex":"https://openalex.org/W1959228470","doi":"https://doi.org/10.1109/cvpr.2015.7299167","mag":"1959228470"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2015.7299167","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2015.7299167","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","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/A5016095713","display_name":"Xinlei Chen","orcid":"https://orcid.org/0000-0001-8271-5023"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Xinlei Chen","raw_affiliation_strings":["Carnegie Mellon University","Carnegie Mellon Univ (USA)"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University","institution_ids":["https://openalex.org/I74973139"]},{"raw_affiliation_string":"Carnegie Mellon Univ (USA)","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039096905","display_name":"Alan Ritter","orcid":null},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alan Ritter","raw_affiliation_strings":["Ohio State university","Ohio State University - USA"],"affiliations":[{"raw_affiliation_string":"Ohio State university","institution_ids":["https://openalex.org/I52357470"]},{"raw_affiliation_string":"Ohio State University - USA","institution_ids":["https://openalex.org/I52357470"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101761266","display_name":"Abhinav Gupta","orcid":"https://orcid.org/0000-0002-3646-2421"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Abhinav Gupta","raw_affiliation_strings":["Carnegie Mellon University","Carnegie Mellon Univ (USA)"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University","institution_ids":["https://openalex.org/I74973139"]},{"raw_affiliation_string":"Carnegie Mellon Univ (USA)","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102921433","display_name":"Tom M. Mitchell","orcid":"https://orcid.org/0000-0001-7373-0301"},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]},{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tom Mitchell","raw_affiliation_strings":["Ohio State university","Carnegie Mellon Univ (USA)"],"affiliations":[{"raw_affiliation_string":"Ohio State university","institution_ids":["https://openalex.org/I52357470"]},{"raw_affiliation_string":"Carnegie Mellon Univ (USA)","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5016095713"],"corresponding_institution_ids":["https://openalex.org/I74973139"],"apc_list":null,"apc_paid":null,"fwci":3.1821,"has_fulltext":false,"cited_by_count":26,"citation_normalized_percentile":{"value":0.94511304,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"24","issue":null,"first_page":"5298","last_page":"5306"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9991999864578247,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9991999864578247,"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":0.9986000061035156,"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":0.9968000054359436,"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/polysemy","display_name":"Polysemy","score":0.7751967310905457},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6912602782249451},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6871445178985596},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6124517917633057},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5773150324821472},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.544620931148529},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4694124162197113},{"id":"https://openalex.org/keywords/phrase","display_name":"Phrase","score":0.4408959150314331},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4250425398349762},{"id":"https://openalex.org/keywords/noun","display_name":"Noun","score":0.4170560836791992},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.07506665587425232}],"concepts":[{"id":"https://openalex.org/C2780276568","wikidata":"https://www.wikidata.org/wiki/Q191928","display_name":"Polysemy","level":2,"score":0.7751967310905457},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6912602782249451},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6871445178985596},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6124517917633057},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5773150324821472},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.544620931148529},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4694124162197113},{"id":"https://openalex.org/C2776224158","wikidata":"https://www.wikidata.org/wiki/Q187931","display_name":"Phrase","level":2,"score":0.4408959150314331},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4250425398349762},{"id":"https://openalex.org/C121934690","wikidata":"https://www.wikidata.org/wiki/Q1084","display_name":"Noun","level":2,"score":0.4170560836791992},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.07506665587425232},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/cvpr.2015.7299167","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2015.7299167","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.906.9694","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.906.9694","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cv-foundation.org/openaccess/content_cvpr_2015/papers/Chen_Sense_Discovery_via_2015_CVPR_paper.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.49000000953674316,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":58,"referenced_works":["https://openalex.org/W234105","https://openalex.org/W82130502","https://openalex.org/W86887328","https://openalex.org/W140130170","https://openalex.org/W1508977358","https://openalex.org/W1512387364","https://openalex.org/W1515999713","https://openalex.org/W1532325895","https://openalex.org/W1578226009","https://openalex.org/W1599287875","https://openalex.org/W1880262756","https://openalex.org/W1964763677","https://openalex.org/W1971220772","https://openalex.org/W1974578407","https://openalex.org/W1989684337","https://openalex.org/W2002754212","https://openalex.org/W2050712820","https://openalex.org/W2080289064","https://openalex.org/W2081580037","https://openalex.org/W2081613070","https://openalex.org/W2101210369","https://openalex.org/W2104411075","https://openalex.org/W2107698128","https://openalex.org/W2108598243","https://openalex.org/W2110988483","https://openalex.org/W2114473842","https://openalex.org/W2123053055","https://openalex.org/W2125323310","https://openalex.org/W2127292559","https://openalex.org/W2127978399","https://openalex.org/W2128393760","https://openalex.org/W2130337399","https://openalex.org/W2132914434","https://openalex.org/W2133576408","https://openalex.org/W2139346960","https://openalex.org/W2147676727","https://openalex.org/W2148675068","https://openalex.org/W2149056056","https://openalex.org/W2154485288","https://openalex.org/W2154744205","https://openalex.org/W2161969291","https://openalex.org/W2165538724","https://openalex.org/W2168356304","https://openalex.org/W2247412337","https://openalex.org/W2253079677","https://openalex.org/W4206165639","https://openalex.org/W4213009331","https://openalex.org/W4231510805","https://openalex.org/W6600011375","https://openalex.org/W6603374121","https://openalex.org/W6603544577","https://openalex.org/W6629638141","https://openalex.org/W6634576794","https://openalex.org/W6639619044","https://openalex.org/W6680914768","https://openalex.org/W6682444636","https://openalex.org/W6683235044","https://openalex.org/W6691742942"],"related_works":["https://openalex.org/W2119532295","https://openalex.org/W2564102342","https://openalex.org/W2369308426","https://openalex.org/W2546942002","https://openalex.org/W2970216048","https://openalex.org/W2382607599","https://openalex.org/W2376234264","https://openalex.org/W2467263758","https://openalex.org/W2000105152","https://openalex.org/W1842194570"],"abstract_inverted_index":{"We":[0,97,119],"present":[1],"a":[2,17,28,45,99,123],"co-clustering":[3],"framework":[4],"that":[5,126],"can":[6,60],"be":[7],"used":[8],"to":[9,62,67],"discover":[10],"multiple":[11,80],"semantic":[12,57,84],"and":[13,39,69,85],"visual":[14,41,64,86],"senses":[15,65,81],"of":[16,108,115],"given":[18],"Noun":[19],"Phrase":[20],"(NP).":[21],"Unlike":[22],"traditional":[23],"clustering":[24],"approaches":[25],"which":[26],"assume":[27],"one-to-one":[29],"mapping":[30,47,93],"between":[31,48,94],"the":[32,35,40,49,79,92,95],"clusters":[33],"in":[34,82],"text-based":[36],"feature":[37,87],"space":[38],"space,":[42,88],"we":[43],"adopt":[44],"one-to-many":[46],"two":[50],"spaces.":[51],"This":[52],"is":[53],"primarily":[54],"because":[55],"each":[56],"sense":[58,128],"(concept)":[59],"correspond":[61],"different":[63],"due":[66],"viewpoint":[68],"appearance":[70],"variations.":[71],"Our":[72],"structure-EM":[73],"style":[74],"optimization":[75],"not":[76],"only":[77],"extracts":[78],"both":[83],"but":[89],"also":[90,121],"discovers":[91],"senses.":[96],"introduce":[98],"challenging":[100],"dataset":[101],"(CMU":[102],"Polysemy-30)":[103],"for":[104,130],"this":[105],"problem":[106],"consisting":[107],"30":[109],"NPs":[110],"(\u223c5600":[111],"labeled":[112],"instances":[113],"out":[114],"\u223c22K":[116],"total":[117],"instances).":[118],"have":[120],"conducted":[122],"large-scale":[124],"experiment":[125],"performs":[127],"disambiguation":[129],"\u223c2000":[131],"NPs.":[132]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":9},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":2}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
