{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,14]],"date-time":"2026-03-14T21:40:22Z","timestamp":1773524422688,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":34,"publisher":"ACM","license":[{"start":{"date-parts":[[2018,2,2]],"date-time":"2018-02-02T00:00:00Z","timestamp":1517529600000},"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":[[2018,2,2]]},"DOI":"10.1145\/3159652.3159660","type":"proceedings-article","created":{"date-parts":[[2018,2,6]],"date-time":"2018-02-06T18:12:23Z","timestamp":1517940743000},"page":"441-449","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":46,"title":["Extreme Multi-label Learning with Label Features for Warm-start Tagging, Ranking & Recommendation"],"prefix":"10.1145","author":[{"given":"Yashoteja","family":"Prabhu","sequence":"first","affiliation":[{"name":"Indian Institute of Technology Delhi, New Delhi, India"}]},{"given":"Anil","family":"Kag","sequence":"additional","affiliation":[{"name":"Microsoft Research and AI, Bangalore, India"}]},{"given":"Shilpa","family":"Gopinath","sequence":"additional","affiliation":[{"name":"Samsung Research, Bangalore, India"}]},{"given":"Kunal","family":"Dahiya","sequence":"additional","affiliation":[{"name":"Indian Institute of Technology Delhi, New Delhi, India"}]},{"given":"Shrutendra","family":"Harsola","sequence":"additional","affiliation":[{"name":"Microsoft Research and AI, Bangalore, India"}]},{"given":"Rahul","family":"Agrawal","sequence":"additional","affiliation":[{"name":"Microsoft Research and AI, Bangalore, India"}]},{"given":"Manik","family":"Varma","sequence":"additional","affiliation":[{"name":"Microsoft Research and AI & Indian Institute of Technology Delhi, Bangalore, India"}]}],"member":"320","published-online":{"date-parts":[[2018,2,2]]},"reference":[{"key":"e_1_3_2_1_1_1","unstructured":"{n. d.}. Apache Mahout. https:\/\/mahout.apache.org. ({n. d.}).  {n. d.}. Apache Mahout. https:\/\/mahout.apache.org. ({n. d.})."},{"key":"e_1_3_2_1_2_1","unstructured":"{n. d.}. Mrec recommender systems library. http:\/\/mendeley.github.io\/mrec. ({n. d.}).  {n. d.}. Mrec recommender systems library. http:\/\/mendeley.github.io\/mrec. ({n. d.})."},{"key":"e_1_3_2_1_3_1","unstructured":"{n. d.}. Phrase2vec. https:\/\/github.com\/zseymour\/phrase2vec. ({n. d.}).  {n. d.}. Phrase2vec. https:\/\/github.com\/zseymour\/phrase2vec. ({n. d.})."},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/1557019.1557029"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/2488388.2488391"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/3018661.3018741"},{"key":"e_1_3_2_1_7_1","unstructured":"K. Bhatia H. Jain P. Kar M. Varma and P. Jain. 2015. Sparse Local Embeddings for Extreme Multi-label Classification. In NIPS.   K. Bhatia H. Jain P. Kar M. Varma and P. Jain. 2015. Sparse Local Embeddings for Extreme Multi-label Classification. In NIPS."},{"key":"e_1_3_2_1_8_1","unstructured":"K. Bhatia H. Jain Y. Prabhu and M. Varma. {n. d.}. The Extreme Classification Repository: Multi-label Datasets & Code. ({n. d.}). http:\/\/manikvarma.org\/ downloads\/XC\/XMLRepository.html  K. Bhatia H. Jain Y. Prabhu and M. Varma. {n. d.}. The Extreme Classification Repository: Multi-label Datasets & Code. ({n. d.}). http:\/\/manikvarma.org\/ downloads\/XC\/XMLRepository.html"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/1772690.1772717"},{"key":"e_1_3_2_1_10_1","unstructured":"M. Ciss\u00e9 N. Usunier T. Arti\u00e8res and P. Gallinari. 2013. Robust Bloom Filters for Large MultiLabel Classification Tasks. In NIPS.   M. Ciss\u00e9 N. Usunier T. Arti\u00e8res and P. Gallinari. 2013. Robust Bloom Filters for Large MultiLabel Classification Tasks. In NIPS."},{"key":"e_1_3_2_1_11_1","volume":"200","author":"Fan R. E.","unstructured":"R. E. Fan , K. W. Chang , C. J. Hsieh , X. R. Wang , and C. J. Lin. 200 8. LIBLINEAR: A library for large linear classification. JMLR (2008). R. E. Fan, K. W. Chang, C. J. Hsieh, X. R. Wang, and C. J. Lin. 2008. LIBLINEAR: A library for large linear classification. JMLR (2008).","journal-title":"J. Lin."},{"key":"e_1_3_2_1_12_1","volume-title":"Proceedings of KDD Cup","author":"Gantner Z.","year":"2011","unstructured":"Z. Gantner , L. Drumond , C. Freudenthaler , and L. Schmidt-Thieme . 2012. Personalized Ranking for Non-Uniformly Sampled Items . In Proceedings of KDD Cup 2011 . 231--247. Z. Gantner, L. Drumond, C. Freudenthaler, and L. Schmidt-Thieme. 2012. Personalized Ranking for Non-Uniformly Sampled Items. In Proceedings of KDD Cup 2011. 231--247."},{"key":"e_1_3_2_1_13_1","unstructured":"D. Hsu S. Kakade J. Langford and T. Zhang. 2009. Multi-Label Prediction via Compressed Sensing. In NIPS.   D. Hsu S. Kakade J. Langford and T. Zhang. 2009. Multi-Label Prediction via Compressed Sensing. In NIPS."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2008.22"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939756"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/1401890.1401944"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/2566486.2567970"},{"key":"e_1_3_2_1_18_1","volume":"201","author":"Mikolov T.","unstructured":"T. Mikolov , I. Sutskever , K. Chen , G. Corrado , and J. Dean. 201 3. Distributed Representations of Words and Phrases and their Compositionality. CoRR abs\/1310.4546 (2013). T. Mikolov, I. Sutskever, K. Chen, G. Corrado, and J. Dean. 2013. Distributed Representations of Words and Phrases and their Compositionality. CoRR abs\/1310.4546 (2013).","journal-title":"J. Dean."},{"key":"e_1_3_2_1_19_1","unstructured":"P. Mineiro and N. Karampatziakis. 2015. Fast Label Embeddings for Extremely Large Output Spaces. In ECML.  P. Mineiro and N. Karampatziakis. 2015. Fast Label Embeddings for Extremely Large Output Spaces. In ECML."},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"crossref","unstructured":"N. Natarajan and I. Dhillon. 2014. Inductive Matrix Completion for Predicting Gene-Disease Associations. In Bioinformatics.  N. Natarajan and I. Dhillon. 2014. Inductive Matrix Completion for Predicting Gene-Disease Associations. In Bioinformatics.","DOI":"10.1093\/bioinformatics\/btu269"},{"key":"e_1_3_2_1_21_1","volume-title":"Glove: Global Vectors for Word Representation. In EMNLP. 1532--1543.","author":"Pennington J.","year":"2014","unstructured":"J. Pennington , R. Socher , and C. D. Manning . 2014 . Glove: Global Vectors for Word Representation. In EMNLP. 1532--1543. J. Pennington, R. Socher, and C. D. Manning. 2014. Glove: Global Vectors for Word Representation. In EMNLP. 1532--1543."},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/2623330.2623651"},{"key":"e_1_3_2_1_23_1","volume-title":"SIGIR Workshop on Information Retrieval in Advertising.","author":"Raghavan H.","unstructured":"H. Raghavan and R. Iyer . 2008. Evaluating vector-space and probabilistic models for query to ad matching . In SIGIR Workshop on Information Retrieval in Advertising. H. Raghavan and R. Iyer. 2008. Evaluating vector-space and probabilistic models for query to ad matching. In SIGIR Workshop on Information Retrieval in Advertising."},{"key":"e_1_3_2_1_24_1","volume-title":"BPR: Bayesian Personalized Ranking from Implicit Feedback. In UAI.","author":"Rendle S.","year":"2009","unstructured":"S. Rendle , C. Freudenthaler , Z. Gantner , and L. Schmidt-Thieme . 2009 . BPR: Bayesian Personalized Ranking from Implicit Feedback. In UAI. S. Rendle, C. Freudenthaler, Z. Gantner, and L. Schmidt-Thieme. 2009. BPR: Bayesian Personalized Ranking from Implicit Feedback. In UAI."},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/2567948.2577348"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/1526709.1526725"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3097987"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.5591\/978-1-57735-516-8\/IJCAI11-460"},{"key":"e_1_3_2_1_29_1","unstructured":"J. Weston A. Makadia and H. Yee. 2013. Label Partitioning For Sublinear Ranking. In ICML.   J. Weston A. Makadia and H. Yee. 2013. Label Partitioning For Sublinear Ranking. In ICML."},{"key":"e_1_3_2_1_30_1","unstructured":"C. Xu D. Tao and C. Xu. 2013. A Survey on Multi-view Learning. CoRR (2013).  C. Xu D. Tao and C. Xu. 2013. A Survey on Multi-view Learning. CoRR (2013)."},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3098083"},{"key":"e_1_3_2_1_32_1","unstructured":"I. E. H. Yen X. Huang K. Zhong P. Ravikumar and I. S. Dhillon. 2016. PDSparse: A Primal and Dual Sparse Approach to Extreme Multiclass and Multilabel Classification. In ICML.   I. E. H. Yen X. Huang K. Zhong P. Ravikumar and I. S. Dhillon. 2016. PDSparse: A Primal and Dual Sparse Approach to Extreme Multiclass and Multilabel Classification. In ICML."},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2015.12.025"},{"key":"e_1_3_2_1_34_1","unstructured":"Y. Zhang and J. G. Schneider. 2011. Multi-Label Output Codes using Canonical Correlation Analysis. In AISTATS.  Y. Zhang and J. G. Schneider. 2011. Multi-Label Output Codes using Canonical Correlation Analysis. In AISTATS."}],"event":{"name":"WSDM 2018: The Eleventh ACM International Conference on Web Search and Data Mining","location":"Marina Del Rey CA USA","acronym":"WSDM 2018","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data","SIGIR ACM Special Interest Group on Information Retrieval"]},"container-title":["Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3159652.3159660","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3159652.3159660","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T02:26:11Z","timestamp":1750213571000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3159652.3159660"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,2,2]]},"references-count":34,"alternative-id":["10.1145\/3159652.3159660","10.1145\/3159652"],"URL":"https:\/\/doi.org\/10.1145\/3159652.3159660","relation":{},"subject":[],"published":{"date-parts":[[2018,2,2]]},"assertion":[{"value":"2018-02-02","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}