{"id":"https://openalex.org/W2797146061","doi":"https://doi.org/10.1145/3178876.3186176","title":"Better Caching in Search Advertising Systems with Rapid Refresh Predictions","display_name":"Better Caching in Search Advertising Systems with Rapid Refresh Predictions","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2797146061","doi":"https://doi.org/10.1145/3178876.3186176","mag":"2797146061"},"language":"en","primary_location":{"id":"doi:10.1145/3178876.3186176","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3178876.3186176","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 World Wide Web Conference on World Wide Web - WWW '18","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3178876.3186176","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5068512236","display_name":"Conglong Li","orcid":null},"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":"Conglong Li","raw_affiliation_strings":["Carnegie Mellon University, Pittsburgh, PA, USA"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085479490","display_name":"David G. Andersen","orcid":null},"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":"David G. Andersen","raw_affiliation_strings":["Carnegie Mellon University, Pittsburgh, PA, USA"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086820941","display_name":"Qiang Fu","orcid":"https://orcid.org/0000-0002-5821-7267"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]},{"id":"https://openalex.org/I4210108985","display_name":"Bellevue Hospital Center","ror":"https://ror.org/01ky34z31","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1283621791","https://openalex.org/I4210086933","https://openalex.org/I4210108985"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qiang Fu","raw_affiliation_strings":["Microsoft, Bellevue, WA, USA"],"affiliations":[{"raw_affiliation_string":"Microsoft, Bellevue, WA, USA","institution_ids":["https://openalex.org/I1290206253","https://openalex.org/I4210108985"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077856625","display_name":"Sameh Elnikety","orcid":"https://orcid.org/0000-0003-3478-2824"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sameh Elnikety","raw_affiliation_strings":["Microsoft Research, Redmond, WA, USA"],"affiliations":[{"raw_affiliation_string":"Microsoft Research, Redmond, WA, USA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040302174","display_name":"Yuxiong He","orcid":"https://orcid.org/0000-0003-0478-8854"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuxiong He","raw_affiliation_strings":["Microsoft Research, Redmond, WA, USA"],"affiliations":[{"raw_affiliation_string":"Microsoft Research, Redmond, WA, USA","institution_ids":["https://openalex.org/I1290206253"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5068512236"],"corresponding_institution_ids":["https://openalex.org/I74973139"],"apc_list":null,"apc_paid":null,"fwci":1.1699,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.80822039,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1875","last_page":"1884"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11478","display_name":"Caching and Content Delivery","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T11478","display_name":"Caching and Content Delivery","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T12288","display_name":"Optimization and Search Problems","score":0.9896000027656555,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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":0.8477864265441895},{"id":"https://openalex.org/keywords/cache","display_name":"Cache","score":0.7762606143951416},{"id":"https://openalex.org/keywords/revenue","display_name":"Revenue","score":0.6727532148361206},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4814276397228241},{"id":"https://openalex.org/keywords/reuse","display_name":"Reuse","score":0.47601157426834106},{"id":"https://openalex.org/keywords/profit","display_name":"Profit (economics)","score":0.4401143789291382},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.4315013885498047},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3921319842338562},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.25101804733276367},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2351541817188263},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.21588623523712158},{"id":"https://openalex.org/keywords/finance","display_name":"Finance","score":0.12212580442428589}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8477864265441895},{"id":"https://openalex.org/C115537543","wikidata":"https://www.wikidata.org/wiki/Q165596","display_name":"Cache","level":2,"score":0.7762606143951416},{"id":"https://openalex.org/C195487862","wikidata":"https://www.wikidata.org/wiki/Q850210","display_name":"Revenue","level":2,"score":0.6727532148361206},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4814276397228241},{"id":"https://openalex.org/C206588197","wikidata":"https://www.wikidata.org/wiki/Q846574","display_name":"Reuse","level":2,"score":0.47601157426834106},{"id":"https://openalex.org/C181622380","wikidata":"https://www.wikidata.org/wiki/Q26911","display_name":"Profit (economics)","level":2,"score":0.4401143789291382},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.4315013885498047},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3921319842338562},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.25101804733276367},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2351541817188263},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.21588623523712158},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.12212580442428589},{"id":"https://openalex.org/C175444787","wikidata":"https://www.wikidata.org/wiki/Q39072","display_name":"Microeconomics","level":1,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3178876.3186176","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3178876.3186176","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 World Wide Web Conference on World Wide Web - WWW '18","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3178876.3186176","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3178876.3186176","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 World Wide Web Conference on World Wide Web - WWW '18","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.4300000071525574}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W16735613","https://openalex.org/W1539242655","https://openalex.org/W1678356000","https://openalex.org/W1990129631","https://openalex.org/W1995857012","https://openalex.org/W2028083097","https://openalex.org/W2074694452","https://openalex.org/W2075279061","https://openalex.org/W2076618162","https://openalex.org/W2095020907","https://openalex.org/W2096227226","https://openalex.org/W2106591686","https://openalex.org/W2110679325","https://openalex.org/W2116105010","https://openalex.org/W2137151464","https://openalex.org/W2139230733","https://openalex.org/W2149126260","https://openalex.org/W2152628009","https://openalex.org/W2162979096","https://openalex.org/W2168006621","https://openalex.org/W2759677617"],"related_works":["https://openalex.org/W2384475851","https://openalex.org/W2000444236","https://openalex.org/W2353602216","https://openalex.org/W2367078749","https://openalex.org/W2381798600","https://openalex.org/W1910583078","https://openalex.org/W2351618306","https://openalex.org/W4379260874","https://openalex.org/W4390923437","https://openalex.org/W2772061786"],"abstract_inverted_index":{"To":[0,77],"maximize":[1,78],"profit":[2,157,195],"and":[3,9,58,152,186,192],"connect":[4],"users":[5],"to":[6,19,46,56,63,93,96,110,140,146,198],"relevant":[7],"products":[8],"services,":[10],"search":[11,171],"advertising":[12,172],"systems":[13],"use":[14],"sophisticated":[15],"machine":[16,33],"learning":[17,34],"algorithms":[18],"estimate":[20],"the":[21,41,49,83,98,116,141,165,181,188,193,199],"revenue":[22,75,85,108,183],"expectations":[23],"of":[24,26,40,48],"thousands":[25],"matching":[27],"ad":[28],"listings":[29],"per":[30],"query.":[31],"These":[32],"computations":[35],"constitute":[36],"a":[37,128,148,153,168],"substantial":[38],"part":[39],"operating":[42],"cost,":[43,66],"e.g.,":[44],"10%":[45],"30%":[47],"total":[50],"gross":[51],"revenues.":[52],"It":[53],"is":[54,91],"desirable":[55],"cache":[57,154,178,203],"reuse":[59],"previous":[60],"computation":[61,100],"results":[62],"reduce":[64],"this":[65],"but":[67],"caching":[68],"introduces":[69],"approximation":[70],"which":[71],"comes":[72],"with":[73,122],"potential":[74],"loss.":[76],"cost":[79,189],"savings":[80,190],"while":[81],"minimizing":[82],"overall":[84],"impact,":[86],"an":[87],"intelligent":[88],"refresh":[89,97,105,113,134,150],"policy":[90,151],"required":[92],"decide":[94],"when":[95],"cached":[99],"results.":[101],"The":[102],"state-of-the-art":[103,200],"manually-tuned":[104,201],"heuristic":[106],"uses":[107],"history":[109],"assign":[111],"different":[112],"frequencies.":[114],"Using":[115],"gradient":[117],"boosting":[118],"regression":[119],"tree":[120],"algorithm":[121],"well":[123],"selected":[124],"features,":[125],"we":[126],"introduce":[127],"rapid":[129],"prediction":[130],"framework":[131],"that":[132,175],"provides":[133],"decisions":[135],"at":[136],"higher":[137,156],"accuracy":[138],"compared":[139,197],"heuristic.":[142],"This":[143],"enables":[144],"us":[145],"build":[147],"prediction-based":[149],"achieving":[155],"without":[158],"manual":[159],"parameter":[160],"tuning.":[161],"Simulations":[162],"conducted":[163],"on":[164],"logs":[166],"from":[167],"major":[169],"commercial":[170],"system":[173],"show":[174],"our":[176],"proposed":[177],"design":[179],"reduces":[180],"negative":[182],"impact":[184],"(0.07x),":[185],"improves":[187],"(1.41x)":[191],"net":[194],"(1.50~1.70x)":[196],"heuristic-based":[202],"design.":[204]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2}],"updated_date":"2026-03-12T06:13:28.667946","created_date":"2025-10-10T00:00:00"}
