{"id":"https://openalex.org/W2084617605","doi":"https://doi.org/10.1109/icacci.2013.6637255","title":"Weighted semantic fusion of text and content for image retrieval","display_name":"Weighted semantic fusion of text and content for image retrieval","publication_year":2013,"publication_date":"2013-08-01","ids":{"openalex":"https://openalex.org/W2084617605","doi":"https://doi.org/10.1109/icacci.2013.6637255","mag":"2084617605"},"language":"en","primary_location":{"id":"doi:10.1109/icacci.2013.6637255","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icacci.2013.6637255","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 International Conference on Advances in Computing, Communications and Informatics (ICACCI)","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/A5091742776","display_name":"Nidhi Goel","orcid":"https://orcid.org/0000-0002-5194-0188"},"institutions":[{"id":"https://openalex.org/I110166357","display_name":"University of Delhi","ror":"https://ror.org/04gzb2213","country_code":"IN","type":"education","lineage":["https://openalex.org/I110166357"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Nidhi Goel","raw_affiliation_strings":["Department of Computer Science, University Of Delhi, Delhi, India","Department of Computer Science, University of Delhi, New Delhi, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University Of Delhi, Delhi, India","institution_ids":["https://openalex.org/I110166357"]},{"raw_affiliation_string":"Department of Computer Science, University of Delhi, New Delhi, India","institution_ids":["https://openalex.org/I110166357"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5104049208","display_name":"Priti Sehgal","orcid":null},"institutions":[{"id":"https://openalex.org/I110166357","display_name":"University of Delhi","ror":"https://ror.org/04gzb2213","country_code":"IN","type":"education","lineage":["https://openalex.org/I110166357"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Priti Sehgal","raw_affiliation_strings":["Department of Computer Science, Keshav Mahavidyalaya, University Of Delhi, Delhi, India","Department of Computer Science, University of Delhi, New Delhi, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Keshav Mahavidyalaya, University Of Delhi, Delhi, India","institution_ids":["https://openalex.org/I110166357"]},{"raw_affiliation_string":"Department of Computer Science, University of Delhi, New Delhi, India","institution_ids":["https://openalex.org/I110166357"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5091742776"],"corresponding_institution_ids":["https://openalex.org/I110166357"],"apc_list":null,"apc_paid":null,"fwci":0.5443,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.71507868,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"11","issue":null,"first_page":"681","last_page":"687"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9998999834060669,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9998999834060669,"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":0.9991999864578247,"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/T11439","display_name":"Video Analysis and Summarization","score":0.9695000052452087,"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/computer-science","display_name":"Computer science","score":0.790603756904602},{"id":"https://openalex.org/keywords/wordnet","display_name":"WordNet","score":0.7010130882263184},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.6854314804077148},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.6648229956626892},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.6265542507171631},{"id":"https://openalex.org/keywords/semantic-gap","display_name":"Semantic gap","score":0.6244993209838867},{"id":"https://openalex.org/keywords/semantic-similarity","display_name":"Semantic similarity","score":0.6041857004165649},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5102980136871338},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5088608264923096},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5041083097457886},{"id":"https://openalex.org/keywords/content-based-image-retrieval","display_name":"Content-based image retrieval","score":0.4666936993598938},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.4643455147743225},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.442952036857605},{"id":"https://openalex.org/keywords/semantic-matching","display_name":"Semantic matching","score":0.4388345181941986},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40277838706970215},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3498821258544922},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09725505113601685}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.790603756904602},{"id":"https://openalex.org/C157659113","wikidata":"https://www.wikidata.org/wiki/Q533822","display_name":"WordNet","level":2,"score":0.7010130882263184},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.6854314804077148},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.6648229956626892},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.6265542507171631},{"id":"https://openalex.org/C86034646","wikidata":"https://www.wikidata.org/wiki/Q474311","display_name":"Semantic gap","level":4,"score":0.6244993209838867},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.6041857004165649},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5102980136871338},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5088608264923096},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5041083097457886},{"id":"https://openalex.org/C2780052074","wikidata":"https://www.wikidata.org/wiki/Q1128648","display_name":"Content-based image retrieval","level":4,"score":0.4666936993598938},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4643455147743225},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.442952036857605},{"id":"https://openalex.org/C2778493491","wikidata":"https://www.wikidata.org/wiki/Q7449072","display_name":"Semantic matching","level":3,"score":0.4388345181941986},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40277838706970215},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3498821258544922},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09725505113601685},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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":1,"locations":[{"id":"doi:10.1109/icacci.2013.6637255","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icacci.2013.6637255","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 International Conference on Advances in Computing, Communications and Informatics (ICACCI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.7099999785423279,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W44998722","https://openalex.org/W54352306","https://openalex.org/W188684257","https://openalex.org/W952141055","https://openalex.org/W1581562409","https://openalex.org/W1647729745","https://openalex.org/W1659833910","https://openalex.org/W1959533457","https://openalex.org/W1975449500","https://openalex.org/W2033673972","https://openalex.org/W2037567114","https://openalex.org/W2044091084","https://openalex.org/W2059962959","https://openalex.org/W2067491864","https://openalex.org/W2068986612","https://openalex.org/W2101042689","https://openalex.org/W2103318667","https://openalex.org/W2111993661","https://openalex.org/W2117805756","https://openalex.org/W2124456931","https://openalex.org/W2125022748","https://openalex.org/W2127270609","https://openalex.org/W2127563440","https://openalex.org/W2130660124","https://openalex.org/W2132201434","https://openalex.org/W2142549486","https://openalex.org/W2150119873","https://openalex.org/W2156736253","https://openalex.org/W2315956820","https://openalex.org/W2950225692","https://openalex.org/W4298098184","https://openalex.org/W6601825389","https://openalex.org/W6636975626","https://openalex.org/W6640984990","https://openalex.org/W6677712588","https://openalex.org/W6678660682","https://openalex.org/W6680882069","https://openalex.org/W6682146179"],"related_works":["https://openalex.org/W2043952800","https://openalex.org/W2047143235","https://openalex.org/W2957377172","https://openalex.org/W2165693052","https://openalex.org/W2164877079","https://openalex.org/W2569513598","https://openalex.org/W2113471940","https://openalex.org/W2907883452","https://openalex.org/W101928771","https://openalex.org/W2251695880"],"abstract_inverted_index":{"The":[0,87,113,127,152],"performance":[1],"of":[2,157],"image":[3,45,73],"retrieval":[4,46,125],"(IR)":[5],"systems":[6],"improves":[7],"by":[8,78],"reducing":[9],"the":[10,14,18,24,30,44,51,68,71,79,85,90,95,124,132,142,148,162],"semantic":[11,52,64,143],"gap":[12,144],"between":[13,70,89],"low-level":[15],"features":[16],"and":[17,35,48,74,105],"high-level":[19],"concepts.":[20],"Research":[21],"results":[22,47],"in":[23],"recent":[25],"years":[26],"show":[27],"that":[28,131],"combining":[29],"two":[31,114],"modalities":[32,115],"(text":[33],"based":[34],"content":[36,99],"based)":[37],"even":[38],"with":[39],"simple":[40],"fusion":[41],"strategies":[42],"alleviates":[43],"also":[49,146],"reduces":[50,141],"gap.":[53],"In":[54],"this":[55],"paper,":[56],"we":[57],"propose":[58],"a":[59],"new":[60],"approach":[61,129],"called":[62],"weighted":[63],"similarity,":[65],"which":[66],"assesses":[67],"semantics":[69,133],"query":[72,76],"textual":[75],"provided":[77],"user":[80],"as":[81],"an":[82,136],"input":[83],"to":[84,122],"system.":[86],"similarity":[88],"keywords":[91],"has":[92],"been":[93],"measured":[94],"using":[96,108,119,161],"WordNet.":[97],"For":[98],"matching,":[100],"color":[101],"feature":[102],"is":[103,106,159],"extracted":[104],"represented":[107],"Fuzzy":[109],"Color":[110],"Histogram":[111],"(FCH).":[112],"are":[116],"fused":[117],"together":[118],"reordering":[120],"technique":[121],"improve":[123],"results.":[126],"proposed":[128,163],"shows":[130],"learned":[134],"at":[135],"early":[137],"stage":[138],"not":[139],"only":[140],"but":[145],"decreases":[147],"computation":[149],"time":[150],"largely.":[151],"Mean":[153],"Average":[154],"precision":[155],"(MAP)":[156],"0.4311":[158],"achieved":[160],"approach.":[164]},"counts_by_year":[{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
