{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,5]],"date-time":"2026-04-05T20:34:53Z","timestamp":1775421293878,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":44,"publisher":"ACM","license":[{"start":{"date-parts":[[2019,7,25]],"date-time":"2019-07-25T00:00:00Z","timestamp":1564012800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2019,7,25]]},"DOI":"10.1145\/3292500.3330676","type":"proceedings-article","created":{"date-parts":[[2019,7,26]],"date-time":"2019-07-26T13:17:26Z","timestamp":1564147046000},"page":"2032-2040","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":25,"title":["Combining Decision Trees and Neural Networks for Learning-to-Rank in Personal Search"],"prefix":"10.1145","author":[{"given":"Pan","family":"Li","sequence":"first","affiliation":[{"name":"University of Illinois at Urbana-Champaign &amp; Google Inc., Urbana, IL, USA"}]},{"given":"Zhen","family":"Qin","sequence":"additional","affiliation":[{"name":"Google Inc., Mountain View, CA, USA"}]},{"given":"Xuanhui","family":"Wang","sequence":"additional","affiliation":[{"name":"Google Inc., Mountain View, CA, USA"}]},{"given":"Donald","family":"Metzler","sequence":"additional","affiliation":[{"name":"Google Inc., Mountain View, CA, USA"}]}],"member":"320","published-online":{"date-parts":[[2019,7,25]]},"reference":[{"key":"e_1_3_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/1148170.1148177"},{"key":"e_1_3_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/3209978.3209985"},{"key":"e_1_3_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/3018661.3018712"},{"key":"e_1_3_2_2_4_1","doi-asserted-by":"publisher","DOI":"10.1023\/A:1010933404324"},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/1102351.1102363"},{"key":"e_1_3_2_2_6_1","volume-title":"Proceedings of the Learning to Rank Challenge. 25--35","author":"Burges Christopher","year":"2011","unstructured":"Christopher Burges , Krysta Svore , Paul Bennett , Andrzej Pastusiak , and Qiang Wu . 2011 . Learning to rank using an ensemble of lambda-gradient models . In Proceedings of the Learning to Rank Challenge. 25--35 . Christopher Burges, Krysta Svore, Paul Bennett, Andrzej Pastusiak, and Qiang Wu. 2011. Learning to rank using an ensemble of lambda-gradient models. In Proceedings of the Learning to Rank Challenge. 25--35."},{"key":"e_1_3_2_2_7_1","first-page":"23","article-title":"From RankNet to LambdaRank to LambdaMART: An overview","volume":"11","author":"Burges Christopher JC","year":"2010","unstructured":"Christopher JC Burges . 2010 . From RankNet to LambdaRank to LambdaMART: An overview . Learning , Vol. 11 , 23 -- 581 (2010), 81. Christopher JC Burges. 2010. From RankNet to LambdaRank to LambdaMART: An overview. Learning , Vol. 11, 23--581 (2010), 81.","journal-title":"Learning"},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"crossref","unstructured":"Christopher J Burges Robert Ragno and Quoc V Le. 2007. Learning to rank with nonsmooth cost functions. In Advances in Neural Information Processing Systems. 193--200. Christopher J Burges Robert Ragno and Quoc V Le. 2007. Learning to rank with nonsmooth cost functions. In Advances in Neural Information Processing Systems. 193--200.","DOI":"10.7551\/mitpress\/7503.003.0029"},{"key":"e_1_3_2_2_9_1","volume-title":"Proceedings of the Learning to Rank Challenge . 1--24","author":"Chapelle Olivier","year":"2011","unstructured":"Olivier Chapelle and Yi Chang . 2011 . Yahoo! learning to rank challenge overview . In Proceedings of the Learning to Rank Challenge . 1--24 . Olivier Chapelle and Yi Chang. 2011. Yahoo! learning to rank challenge overview. In Proceedings of the Learning to Rank Challenge . 1--24."},{"key":"e_1_3_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/2988450.2988454"},{"key":"e_1_3_2_2_11_1","volume-title":"Search engines: Information retrieval in practice","author":"Croft W Bruce","unstructured":"W Bruce Croft , Donald Metzler , and Trevor Strohman . 2010. Search engines: Information retrieval in practice . Vol. 283 . Addison-Wesley Reading . W Bruce Croft, Donald Metzler, and Trevor Strohman. 2010. Search engines: Information retrieval in practice. Vol. 283. Addison-Wesley Reading."},{"key":"e_1_3_2_2_12_1","first-page":"5","article-title":"Introduction to information retrieval","volume":"151","author":"Manning Christopher D","year":"2008","unstructured":"Christopher D Manning , Prabhakar Raghavan , and Hinrich Schutza . 2008 . Introduction to information retrieval . An Introduction To Information Retrieval , Vol. 151 , 177 (2008), 5 . Christopher D Manning, Prabhakar Raghavan, and Hinrich Schutza. 2008. Introduction to information retrieval. An Introduction To Information Retrieval , Vol. 151, 177 (2008), 5.","journal-title":"An Introduction To Information Retrieval"},{"key":"e_1_3_2_2_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/3077136.3080832"},{"key":"e_1_3_2_2_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/1571941.1572021"},{"key":"e_1_3_2_2_15_1","doi-asserted-by":"publisher","DOI":"10.5555\/945365.964285"},{"key":"e_1_3_2_2_16_1","volume-title":"Greedy function approximation: a gradient boosting machine. Annals of statistics","author":"Friedman Jerome H","year":"2001","unstructured":"Jerome H Friedman . 2001. Greedy function approximation: a gradient boosting machine. Annals of statistics ( 2001 ), 1189--1232. Jerome H Friedman. 2001. Greedy function approximation: a gradient boosting machine. Annals of statistics (2001), 1189--1232."},{"key":"e_1_3_2_2_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/2505515.2505665"},{"key":"e_1_3_2_2_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/2866571"},{"key":"e_1_3_2_2_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/582415.582418"},{"key":"e_1_3_2_2_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/1150402.1150429"},{"key":"e_1_3_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/3018661.3018699"},{"key":"e_1_3_2_2_23_1","volume-title":"A primer of real analytic functions","author":"Krantz Steven G","unstructured":"Steven G Krantz and Harold R Parks . 2002. A primer of real analytic functions . Springer Science & Business Media . Steven G Krantz and Harold R Parks. 2002. A primer of real analytic functions .Springer Science & Business Media."},{"key":"e_1_3_2_2_24_1","volume-title":"Nature","volume":"521","author":"LeCun Yann","year":"2015","unstructured":"Yann LeCun , Yoshua Bengio , and Geoffrey Hinton . 2015 . Deep learning . Nature , Vol. 521 , 7553 (2015), 436. Yann LeCun, Yoshua Bengio, and Geoffrey Hinton. 2015. Deep learning. Nature , Vol. 521, 7553 (2015), 436."},{"key":"e_1_3_2_2_25_1","volume-title":"Salvatore Orlando, Raffaele Perego, Nicola Tonellotto, and Rossano Venturini.","author":"Lettich Francesco","year":"2018","unstructured":"Francesco Lettich , Claudio Lucchese , Franco Maria Nardini , Salvatore Orlando, Raffaele Perego, Nicola Tonellotto, and Rossano Venturini. 2018 . Parallel Traversal of Large Ensembles of Decision Trees. IEEE Transactions on Parallel and Distributed Systems ( 2018). Francesco Lettich, Claudio Lucchese, Franco Maria Nardini, Salvatore Orlando, Raffaele Perego, Nicola Tonellotto, and Rossano Venturini. 2018. Parallel Traversal of Large Ensembles of Decision Trees. IEEE Transactions on Parallel and Distributed Systems (2018)."},{"key":"e_1_3_2_2_26_1","unstructured":"Pan Li Arya Mazumdar and Olgica Milenkovic. 2017. Efficient Rank Aggregation via Lehmer Codes. In Artificial Intelligence and Statistics . 450--459. Pan Li Arya Mazumdar and Olgica Milenkovic. 2017. Efficient Rank Aggregation via Lehmer Codes. In Artificial Intelligence and Statistics . 450--459."},{"key":"e_1_3_2_2_27_1","volume-title":"Mcrank: Learning to rank using multiple classification and gradient boosting. In Advances in Neural Information Processing Systems. 897--904.","author":"Li Ping","year":"2008","unstructured":"Ping Li , Qiang Wu , and Christopher J Burges . 2008 . Mcrank: Learning to rank using multiple classification and gradient boosting. In Advances in Neural Information Processing Systems. 897--904. Ping Li, Qiang Wu, and Christopher J Burges. 2008. Mcrank: Learning to rank using multiple classification and gradient boosting. In Advances in Neural Information Processing Systems. 897--904."},{"key":"e_1_3_2_2_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/3041021.3054192"},{"key":"e_1_3_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.1561\/1500000016"},{"key":"e_1_3_2_2_30_1","volume-title":"Proceedings of SIGIR 2007 workshop on learning to rank for information retrieval","volume":"310","author":"Liu Tie-Yan","year":"2007","unstructured":"Tie-Yan Liu , Jun Xu , Tao Qin , Wenying Xiong , and Hang Li . 2007 . Letor: Benchmark dataset for research on learning to rank for information retrieval . In Proceedings of SIGIR 2007 workshop on learning to rank for information retrieval , Vol. 310 . ACM Amsterdam, The Netherlands. Tie-Yan Liu, Jun Xu, Tao Qin, Wenying Xiong, and Hang Li. 2007. Letor: Benchmark dataset for research on learning to rank for information retrieval. In Proceedings of SIGIR 2007 workshop on learning to rank for information retrieval , Vol. 310. ACM Amsterdam, The Netherlands."},{"key":"e_1_3_2_2_31_1","doi-asserted-by":"publisher","DOI":"10.1145\/3077136.3080642"},{"key":"e_1_3_2_2_32_1","unstructured":"Llew Mason Jonathan Baxter Peter L Bartlett and Marcus R Frean. 2000. Boosting algorithms as gradient descent. In Advances in Neural Information Processing Systems. 512--518. Llew Mason Jonathan Baxter Peter L Bartlett and Marcus R Frean. 2000. Boosting algorithms as gradient descent. In Advances in Neural Information Processing Systems. 512--518."},{"key":"e_1_3_2_2_33_1","volume-title":"Neural Models for Information Retrieval. arXiv preprint arXiv:1705.01509","author":"Mitra Bhaskar","year":"2017","unstructured":"Bhaskar Mitra and Nick Craswell . 2017. Neural Models for Information Retrieval. arXiv preprint arXiv:1705.01509 ( 2017 ). Bhaskar Mitra and Nick Craswell. 2017. Neural Models for Information Retrieval. arXiv preprint arXiv:1705.01509 (2017)."},{"key":"e_1_3_2_2_34_1","doi-asserted-by":"publisher","DOI":"10.1613\/jair.614"},{"key":"e_1_3_2_2_36_1","doi-asserted-by":"publisher","DOI":"10.1109\/BigData.2017.8257910"},{"key":"e_1_3_2_2_37_1","doi-asserted-by":"publisher","DOI":"10.1145\/290941.291008"},{"key":"e_1_3_2_2_38_1","volume-title":"International Conference on Machine Learning .","author":"Si Si","year":"2017","unstructured":"Si Si , Huan Zhang , Sathiya Keerthi , Druv Mahajan , Inderjit Dhillon , and Cho-Jui Hsieh . 2017 . Gradient boosted decision trees for high dimensional sparse output . In International Conference on Machine Learning . Si Si, Huan Zhang, Sathiya Keerthi, Druv Mahajan, Inderjit Dhillon, and Cho-Jui Hsieh. 2017. Gradient boosted decision trees for high dimensional sparse output. In International Conference on Machine Learning ."},{"key":"e_1_3_2_2_39_1","doi-asserted-by":"publisher","DOI":"10.1145\/3124749.3124754"},{"key":"e_1_3_2_2_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/2911451.2911537"},{"key":"e_1_3_2_2_41_1","doi-asserted-by":"publisher","DOI":"10.1145\/3159652.3159732"},{"key":"e_1_3_2_2_42_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10791-009-9112-1"},{"key":"e_1_3_2_2_43_1","doi-asserted-by":"publisher","DOI":"10.1145\/1277741.1277809"},{"key":"e_1_3_2_2_44_1","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939677"},{"key":"e_1_3_2_2_45_1","doi-asserted-by":"publisher","DOI":"10.1145\/3038912.3052648"}],"event":{"name":"KDD '19: The 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","location":"Anchorage AK USA","acronym":"KDD '19","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data"]},"container-title":["Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery &amp; Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3292500.3330676","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3292500.3330676","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T01:02:09Z","timestamp":1750208529000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3292500.3330676"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7,25]]},"references-count":44,"alternative-id":["10.1145\/3292500.3330676","10.1145\/3292500"],"URL":"https:\/\/doi.org\/10.1145\/3292500.3330676","relation":{},"subject":[],"published":{"date-parts":[[2019,7,25]]},"assertion":[{"value":"2019-07-25","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}