{"id":"https://openalex.org/W2514079225","doi":"https://doi.org/10.1145/2970398.2970416","title":"A Unified Energy-based Framework for Learning to Rank","display_name":"A Unified Energy-based Framework for Learning to Rank","publication_year":2016,"publication_date":"2016-09-09","ids":{"openalex":"https://openalex.org/W2514079225","doi":"https://doi.org/10.1145/2970398.2970416","mag":"2514079225"},"language":"en","primary_location":{"id":"doi:10.1145/2970398.2970416","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2970398.2970416","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2016 ACM International Conference on the Theory of Information Retrieval","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/A5101972978","display_name":"Yi Fang","orcid":"https://orcid.org/0000-0001-6572-4315"},"institutions":[{"id":"https://openalex.org/I16269868","display_name":"Santa Clara University","ror":"https://ror.org/03ypqe447","country_code":"US","type":"education","lineage":["https://openalex.org/I16269868"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yi Fang","raw_affiliation_strings":["Santa Clara University, Santa Clara, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Santa Clara University, Santa Clara, CA, USA","institution_ids":["https://openalex.org/I16269868"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023578096","display_name":"Mengwen Liu","orcid":"https://orcid.org/0000-0001-8006-5995"},"institutions":[{"id":"https://openalex.org/I72816309","display_name":"Drexel University","ror":"https://ror.org/04bdffz58","country_code":"US","type":"education","lineage":["https://openalex.org/I72816309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mengwen Liu","raw_affiliation_strings":["Drexel University, Philadelphia, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Drexel University, Philadelphia, CA, USA","institution_ids":["https://openalex.org/I72816309"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.08109142,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"171","last_page":"180"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9966999888420105,"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":0.9966999888420105,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9961000084877014,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.9926999807357788,"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":0.7116767168045044},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.6986441612243652},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6553926467895508},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.5884411334991455},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.5862689018249512},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5758864283561707},{"id":"https://openalex.org/keywords/pointwise","display_name":"Pointwise","score":0.5439162254333496},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.5323788523674011},{"id":"https://openalex.org/keywords/learning-to-rank","display_name":"Learning to rank","score":0.5249742865562439},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09096625447273254}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7116767168045044},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.6986441612243652},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6553926467895508},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.5884411334991455},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.5862689018249512},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5758864283561707},{"id":"https://openalex.org/C2777984123","wikidata":"https://www.wikidata.org/wiki/Q9248237","display_name":"Pointwise","level":2,"score":0.5439162254333496},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.5323788523674011},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.5249742865562439},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09096625447273254},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2970398.2970416","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2970398.2970416","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2016 ACM International Conference on the Theory of Information Retrieval","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.8700000047683716}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W10021998","https://openalex.org/W68132019","https://openalex.org/W1530210183","https://openalex.org/W1708221419","https://openalex.org/W2004804665","https://openalex.org/W2009077327","https://openalex.org/W2047221353","https://openalex.org/W2091158010","https://openalex.org/W2108862644","https://openalex.org/W2115096495","https://openalex.org/W2124914669","https://openalex.org/W2127661044","https://openalex.org/W2129245267","https://openalex.org/W2136163184","https://openalex.org/W2140310134","https://openalex.org/W2142537246","https://openalex.org/W2143331230","https://openalex.org/W2148862211","https://openalex.org/W2149427297","https://openalex.org/W2150721099","https://openalex.org/W2157364932","https://openalex.org/W2159545104","https://openalex.org/W2161914416","https://openalex.org/W2164452159","https://openalex.org/W2182304831","https://openalex.org/W2276256113","https://openalex.org/W2319974058","https://openalex.org/W2542898981","https://openalex.org/W2605998369","https://openalex.org/W2616465717","https://openalex.org/W2997591727","https://openalex.org/W3004985245","https://openalex.org/W4285719527","https://openalex.org/W4300415226"],"related_works":["https://openalex.org/W2767338541","https://openalex.org/W2112815677","https://openalex.org/W2606864227","https://openalex.org/W2429267751","https://openalex.org/W3089328091","https://openalex.org/W3216317163","https://openalex.org/W2011472225","https://openalex.org/W3000057026","https://openalex.org/W3048565508","https://openalex.org/W3163984363"],"abstract_inverted_index":{"Learning":[0,60,91],"to":[1,32,61,82,88,116],"Rank":[2,62],"(L2R)":[3],"has":[4],"emerged":[5],"as":[6],"one":[7],"of":[8,35,59,96,155,192],"the":[9,17,36,94,98,134,151,175,183,190,193],"core":[10],"machine":[11],"learning":[12,115,153],"techniques":[13],"for":[14,163],"IR.":[15],"On":[16],"other":[18],"hand,":[19],"Energy-Based":[20],"Models":[21],"(EBMs)":[22],"capture":[23],"dependencies":[24],"between":[25],"variables":[26],"by":[27,150],"associating":[28],"a":[29,56],"scalar":[30],"energy":[31,77,99],"each":[33],"configuration":[34],"variables.":[37],"They":[38],"have":[39,105],"produced":[40],"impressive":[41],"results":[42],"in":[43,68,133],"many":[44],"computer":[45],"vision":[46],"and":[47,85,128,188],"speech":[48],"recognition":[49],"tasks.":[50,165],"In":[51,73],"this":[52,74],"paper,":[53],"we":[54,119,157],"introduce":[55,167],"unified":[57],"view":[58],"that":[63,102],"integrates":[64],"various":[65,122],"L2R":[66,124,139],"approaches":[67],"an":[69,76],"energy-based":[70,135,161,170],"ranking":[71,164,171],"framework.":[72,136,177],"framework,":[75],"function":[78],"associates":[79],"low":[80],"energies":[81,87],"desired":[83,103],"documents":[84,104],"high":[86],"undesired":[89],"results.":[90],"is":[92],"essentially":[93],"process":[95,154],"shaping":[97],"surface":[100],"so":[101],"lower":[106],"energies.":[107],"The":[108,178],"proposed":[109,176,194],"framework":[110],"yields":[111],"new":[112,138,169],"insights":[113],"into":[114],"rank.":[117],"First,":[118],"show":[120],"how":[121],"existing":[123,146],"models":[125,140,162,172],"(pointwise,":[126],"pairwise,":[127],"listwise)":[129],"can":[130,141,158],"be":[131,142],"cast":[132],"Second,":[137],"constructed":[143],"based":[144,173],"on":[145,174,182],"EBMs.":[147],"Furthermore,":[148],"inspired":[149],"intuitive":[152],"EBMs,":[156],"devise":[159],"novel":[160],"We":[166],"several":[168],"experiments":[179],"are":[180],"conducted":[181],"public":[184],"LETOR":[185],"4.0":[186],"benchmarks":[187],"demonstrate":[189],"effectiveness":[191],"models.":[195]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}