{"id":"https://openalex.org/W2890470451","doi":"https://doi.org/10.1109/qomex.2018.8463396","title":"Extended Features using Machine Learning Techniques for Photo Liking Prediction","display_name":"Extended Features using Machine Learning Techniques for Photo Liking Prediction","publication_year":2018,"publication_date":"2018-05-01","ids":{"openalex":"https://openalex.org/W2890470451","doi":"https://doi.org/10.1109/qomex.2018.8463396","mag":"2890470451"},"language":"en","primary_location":{"id":"doi:10.1109/qomex.2018.8463396","is_oa":false,"landing_page_url":"https://doi.org/10.1109/qomex.2018.8463396","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 Tenth International Conference on Quality of Multimedia Experience (QoMEX)","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/A5037783940","display_name":"Steve G\u00f6ring","orcid":"https://orcid.org/0000-0001-6810-6969"},"institutions":[{"id":"https://openalex.org/I119449181","display_name":"Technische Universit\u00e4t Ilmenau","ror":"https://ror.org/01weqhp73","country_code":"DE","type":"education","lineage":["https://openalex.org/I119449181"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Steve Goring","raw_affiliation_strings":["Dept. of Audio Visual Technology, Technische Universitt, Ilmenau, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Audio Visual Technology, Technische Universitt, Ilmenau, Germany","institution_ids":["https://openalex.org/I119449181"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001388816","display_name":"Konstantin Brand","orcid":null},"institutions":[{"id":"https://openalex.org/I119449181","display_name":"Technische Universit\u00e4t Ilmenau","ror":"https://ror.org/01weqhp73","country_code":"DE","type":"education","lineage":["https://openalex.org/I119449181"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Konstantin Brand","raw_affiliation_strings":["Dept. of Audio Visual Technology, Technische Universitt, Ilmenau, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Audio Visual Technology, Technische Universitt, Ilmenau, Germany","institution_ids":["https://openalex.org/I119449181"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008559961","display_name":"Alexander Raake","orcid":"https://orcid.org/0000-0002-9357-1763"},"institutions":[{"id":"https://openalex.org/I119449181","display_name":"Technische Universit\u00e4t Ilmenau","ror":"https://ror.org/01weqhp73","country_code":"DE","type":"education","lineage":["https://openalex.org/I119449181"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Alexander Raake","raw_affiliation_strings":["Dept. of Audio Visual Technology, Technische Universitt, Ilmenau, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Audio Visual Technology, Technische Universitt, Ilmenau, Germany","institution_ids":["https://openalex.org/I119449181"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I119449181"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9993000030517578,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9993000030517578,"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/T12650","display_name":"Aesthetic Perception and Analysis","score":0.9955999851226807,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11165","display_name":"Image and Video Quality Assessment","score":0.9818000197410583,"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":0.7903825044631958},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.661703884601593},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6562743186950684},{"id":"https://openalex.org/keywords/usable","display_name":"USable","score":0.6376491189002991},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.610217809677124},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.472149133682251},{"id":"https://openalex.org/keywords/predictive-modelling","display_name":"Predictive modelling","score":0.4418966770172119},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.415926456451416},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.12947872281074524}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7903825044631958},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.661703884601593},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6562743186950684},{"id":"https://openalex.org/C2780615836","wikidata":"https://www.wikidata.org/wiki/Q2471869","display_name":"USable","level":2,"score":0.6376491189002991},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.610217809677124},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.472149133682251},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.4418966770172119},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.415926456451416},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.12947872281074524}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/qomex.2018.8463396","is_oa":false,"landing_page_url":"https://doi.org/10.1109/qomex.2018.8463396","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 Tenth International Conference on Quality of Multimedia Experience (QoMEX)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.4699999988079071,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1460922575","https://openalex.org/W1511924373","https://openalex.org/W1554338108","https://openalex.org/W1614298861","https://openalex.org/W1913628733","https://openalex.org/W2039355801","https://openalex.org/W2059934139","https://openalex.org/W2063948594","https://openalex.org/W2081418425","https://openalex.org/W2101234009","https://openalex.org/W2135347478","https://openalex.org/W2183341477","https://openalex.org/W2239239723","https://openalex.org/W2325939864","https://openalex.org/W2472257696","https://openalex.org/W2473166878","https://openalex.org/W2951818954","https://openalex.org/W2953320089","https://openalex.org/W6675354045","https://openalex.org/W6686164453","https://openalex.org/W6720996711","https://openalex.org/W6983682869"],"related_works":["https://openalex.org/W2982321410","https://openalex.org/W2392004567","https://openalex.org/W2046296964","https://openalex.org/W2940029036","https://openalex.org/W4388292429","https://openalex.org/W2756595502","https://openalex.org/W2010789764","https://openalex.org/W2187233292","https://openalex.org/W4389422031","https://openalex.org/W2219281195"],"abstract_inverted_index":{"Today":[0],"several":[1],"photo":[2,48],"platforms":[3],"provide":[4],"thousands":[5],"of":[6,22,84,104,125,140,148],"new":[7],"pictures,":[8],"it":[9],"becomes":[10],"ambitious":[11],"to":[12,136],"find":[13],"highly":[14],"appealing":[15],"or":[16,35],"like-able":[17],"photos":[18,86],"within":[19],"such":[20],"loads":[21],"data.":[23],"Here,":[24],"automatic":[25],"liking":[26,49,119,141],"prediction":[27,138],"can":[28,151],"support":[29],"users":[30],"in":[31,38],"handling":[32],"their":[33],"pictures":[34,156],"improve":[36,137],"ranking":[37],"sharing":[39],"platforms.":[40],"We":[41,75,143],"describe":[42],"a":[43,80,123],"machine":[44],"learning":[45,65],"approach":[46],"for":[47,118,159],"prediction.":[50,160],"Our":[51],"features":[52,107,113,133,149],"are":[53,134,157],"based":[54,87],"on":[55,88],"various":[56],"techniques,":[57],"e.g.":[58],"natural":[59],"language":[60],"processing/sentiment":[61],"analysis,":[62],"pre-trained":[63],"deep":[64],"networks,":[66],"social":[67,111],"network":[68,112],"analysis":[69],"and":[70,108],"extended":[71],"previously":[72],"reported":[73],"features.":[74],"conduct":[76],"large-scale":[77],"experiments":[78,99],"using":[79],"collected":[81],"dataset":[82],"consisting":[83],"80k":[85],"two":[89],"main":[90],"categories":[91],"from":[92,155],"500px":[93],"with":[94],"different":[95],"settings.":[96],"In":[97],"our":[98,105],"we":[100,121,128],"analyzed":[101],"the":[102,115],"impact":[103],"newly":[106],"found":[109],"that":[110,130,150],"have":[114],"strongest":[116],"influence":[117],"prediction,":[120],"achived":[122],"boost":[124],"15%.":[126],"Furthermore,":[127],"show":[129],"all":[131],"implemented":[132],"able":[135],"accuracy":[139],"rates.":[142],"additionally":[144],"analyze":[145],"which":[146],"groups":[147],"be":[152],"derived":[153],"directly":[154],"usable":[158]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2021,"cited_by_count":3},{"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"}
