{"id":"https://openalex.org/W3034151018","doi":"https://doi.org/10.1145/3372278.3390719","title":"Semantic Gated Network for Efficient News Representation","display_name":"Semantic Gated Network for Efficient News Representation","publication_year":2020,"publication_date":"2020-06-02","ids":{"openalex":"https://openalex.org/W3034151018","doi":"https://doi.org/10.1145/3372278.3390719","mag":"3034151018"},"language":"en","primary_location":{"id":"doi:10.1145/3372278.3390719","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3372278.3390719","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 International Conference on Multimedia 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/A5070479634","display_name":"Xuxiao Bu","orcid":null},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xuxiao Bu","raw_affiliation_strings":["Xi'an Jiaotong University, Xi'an, Shaanxi, China"],"affiliations":[{"raw_affiliation_string":"Xi'an Jiaotong University, Xi'an, Shaanxi, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101400001","display_name":"Bingfeng Li","orcid":"https://orcid.org/0000-0002-7140-1122"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bingfeng Li","raw_affiliation_strings":["Tencent, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tencent, Beijing, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101651167","display_name":"Yaxiong Wang","orcid":"https://orcid.org/0000-0001-6596-8117"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaxiong Wang","raw_affiliation_strings":["Xi'an Jiaotong University, Xi'an, Shaanxi, China"],"affiliations":[{"raw_affiliation_string":"Xi'an Jiaotong University, Xi'an, Shaanxi, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068185614","display_name":"Jihua Zhu","orcid":"https://orcid.org/0000-0002-3081-8781"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jihua Zhu","raw_affiliation_strings":["Xi'an Jiaotong University, Xi'an, Shaanxi, China"],"affiliations":[{"raw_affiliation_string":"Xi'an Jiaotong University, Xi'an, Shaanxi, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014825654","display_name":"Xueming Qian","orcid":"https://orcid.org/0000-0002-3173-6307"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xueming Qian","raw_affiliation_strings":["Xi'an Jiaotong University, Xi'an, Shaanxi, China"],"affiliations":[{"raw_affiliation_string":"Xi'an Jiaotong University, Xi'an, Shaanxi, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022768834","display_name":"Marco Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Marco Zhao","raw_affiliation_strings":["Tencent, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tencent, Beijing, China","institution_ids":["https://openalex.org/I2250653659"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5070479634"],"corresponding_institution_ids":["https://openalex.org/I87445476"],"apc_list":null,"apc_paid":null,"fwci":0.0977,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.37794918,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"251","last_page":"255"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9987999796867371,"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":0.9973000288009644,"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":0.839508056640625},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6960198879241943},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.6527212858200073},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.6070547699928284},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.6065792441368103},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5936623811721802},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5685919523239136},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.5450414419174194},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4758179783821106},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.47340187430381775},{"id":"https://openalex.org/keywords/semantic-feature","display_name":"Semantic feature","score":0.4641242027282715},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.45782217383384705},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.4416542053222656},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.41890907287597656},{"id":"https://openalex.org/keywords/bag-of-words-model","display_name":"Bag-of-words model","score":0.41126304864883423}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.839508056640625},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6960198879241943},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.6527212858200073},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.6070547699928284},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.6065792441368103},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5936623811721802},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5685919523239136},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.5450414419174194},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4758179783821106},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.47340187430381775},{"id":"https://openalex.org/C2781122975","wikidata":"https://www.wikidata.org/wiki/Q16928266","display_name":"Semantic feature","level":2,"score":0.4641242027282715},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.45782217383384705},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.4416542053222656},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.41890907287597656},{"id":"https://openalex.org/C13672336","wikidata":"https://www.wikidata.org/wiki/Q3460803","display_name":"Bag-of-words model","level":2,"score":0.41126304864883423},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","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:10.1145/3372278.3390719","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3372278.3390719","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 International Conference on Multimedia Retrieval","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.6100000143051147}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1832693441","https://openalex.org/W2027857109","https://openalex.org/W2153579005","https://openalex.org/W2194775991","https://openalex.org/W2619383789","https://openalex.org/W2740711318","https://openalex.org/W2798404773","https://openalex.org/W2897125675","https://openalex.org/W2946340210","https://openalex.org/W2949952998","https://openalex.org/W2962964995","https://openalex.org/W2963869731","https://openalex.org/W2964308564","https://openalex.org/W2964349605","https://openalex.org/W2998704965","https://openalex.org/W6680532216","https://openalex.org/W6844956273"],"related_works":["https://openalex.org/W4390516098","https://openalex.org/W2181948922","https://openalex.org/W2375873920","https://openalex.org/W2384362569","https://openalex.org/W2379770539","https://openalex.org/W4311555960","https://openalex.org/W4390871823","https://openalex.org/W2389814472","https://openalex.org/W2473933584","https://openalex.org/W2755935915"],"abstract_inverted_index":{"Learning":[0],"an":[1,86],"efficient":[2,56,87,137],"news":[3,52,60,78,121,134,146],"representation":[4],"is":[5,123,148],"a":[6,49,67,126,170],"fundamental":[7],"yet":[8],"important":[9],"problem":[10],"for":[11,91],"many":[12],"tasks.":[13],"Most":[14],"existing":[15],"news-relevant":[16],"methods":[17],"only":[18],"take":[19],"the":[20,25,29,34,41,45,59,77,92,100,111,115,142,145,152,179,183,192],"textual":[21,35,165,180],"information":[22],"while":[23],"abandoning":[24],"visual":[26,42,82],"clues":[27],"from":[28],"illustrations.":[30],"We":[31],"argue":[32],"that":[33],"title":[36,122,147],"and":[37,53,81,155,182],"tags":[38,80,162],"together":[39],"with":[40,159],"illustrations":[43,83],"form":[44],"main":[46],"force":[47],"of":[48,51,105,144,161,194],"piece":[50],"are":[54],"more":[55],"to":[57,75,84,135,163,176],"express":[58],"content.":[61],"In":[62],"this":[63],"paper,":[64],"we":[65,96,108,156,168],"develop":[66],"novel":[68,171],"framework,":[69],"namely":[70],"Semantic":[71],"Gated":[72],"Network":[73],"(SGN),":[74],"integrate":[76],"title,":[79],"obtain":[85,164],"joint":[88],"textual-visual":[89],"feature":[90,143,181],"news,":[93],"by":[94,114,130],"which":[95],"can":[97],"directly":[98],"measure":[99],"relevance":[101],"between":[102],"two":[103,131],"pieces":[104],"news.":[106],"Particularly,":[107],"first":[109],"harvest":[110],"tag":[112],"embeddings":[113],"proposed":[116],"self-supervised":[117],"classification":[118],"model.":[119],"Besides,":[120],"fed":[124],"into":[125],"sentence":[127],"encoder":[128],"pretrained":[129],"semantically":[132],"relevant":[133],"learn":[136],"contextualized":[138],"word":[139],"vectors.":[140],"Then":[141],"extracted":[149],"based":[150],"on":[151,188],"learned":[153],"vectors":[154],"combine":[157],"it":[158],"features":[160],"feature.":[166,185],"Finally,":[167],"design":[169],"mechanism":[172],"named":[173],"semantic":[174],"gate":[175],"adaptively":[177],"fuse":[178],"image":[184],"Extensive":[186],"experiments":[187],"benchmark":[189],"dataset":[190],"demonstrate":[191],"effectiveness":[193],"our":[195],"approach.":[196]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
